Converger presents news and views from an AI, internet and media policy expert who is pro-innovation but anti-hype, allergic to both AI panic and AI boosterism, and passionate about supporting rather than supplanting human creativity with new technology.

Some issues may be heavier on media commentary, others on AI policy, others on personal passions like sci-fi’s influence on technology (both for good and bad) or the evolving medium and business of comic books in the digital age. You never know what threads might come together in convergence-space!

I’m Kevin Bankston, your host. You can watch me develop newsletter content in real-time on LinkedIn and the social network formerly known as Twitter, and less often on Bluesky and Instagram. You can also look for my more wonkish takes on AI governance at Elicitation, the new Substack from my AI policy day-job colleague Miranda Bogen of the Center for Democracy & Technology’s AI Governance Lab. (Note that my Substack articles don’t necessarily reflect CDT’s positions.)

In this week’s edition, I’ve focused solely on takeaways from the ‘AI on the Lot’ conference. Only features this week, no fragments. I’ll catch up on those in our next issue, as well as sharing one more AI on the Lot followup, an interview with advice on how AI creators can protect the copyright in their AI-generated films. (Those who are waiting on the copyright litigation update that I promised will have to wait a week or two longer.)

Also this week, I just filed my first guest post over at the AI policy newsletter Elicitation. It’s all about AI data portability—why we need it, the current state of it (not good!), how to spot fake data portability, and how to demand the real thing. Here’s the first paragraph as a preview:

Last November, after over a year of regularly using ChatGPT, I was ready to give Google’s Gemini and Anthropic’s Claude a try instead. The latest versions of both models had just dropped, and everyone online was hyping them as better on a variety of benchmarks compared to OpenAI’s flagship. I’d played a bit with each of those other models before, but decided it was time to truly give them a shot, and compare their performance on my most important projects to what ChatGPT had been giving me. The problem was…I couldn’t.

Click on over to Elicitation to read the rest, after you read today’s Converger! And please share with your friends and colleagues if you enjoy!

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TABLE OF CONTENTS

FEATURES (>500 words)

1. ‘AI on the Lot’ Debrief I: How I Got an AI-Generated TV Series Cancelled (Accidentally)

2. ‘AI on the Lot’ Debrief II: Conference Reflections Roundup

3. ‘AI on the Lot’ Debrief III: Technology Brother vs. Hollywood Brother, with Matthew Bankston

4. Hannah Einbinder Swirlie Watch, the Final Edition: Who’s Getting Flushed for Using AI This Week?

FRAGMENTS (<500 words)—none this week!

FEATURES

‘AI on the Lot’ Debrief I: How I Got an AI-Generated TV Series Cancelled (Accidentally)

I helped murder Punky Duck.

Or maybe it was merely duckslaughter, since I didn’t mean to do it? Either way, the duck is definitely dead.

Two weeks ago, I tweeted a joke I heard from a creator at the AI on the Lot conference. Within 48 hours, that joke had helped get that creator’s just-announced new AI-generated cartoon show for Amazon Prime cancelled.

I feel bad about that, mostly. But it was probably going to happen anyway, and that’s on Amazon.

But I’m getting ahead of myself…

On Tuesday, May 26, as soon as I pressed publish on the last issue of Converger, I hopped on a cross-country flight to LAX to attend the fourth annual AI on the Lot conference.

With the explosive growth in the conference—from a half-day 600-person event the first year to now a two-day, nearly-2500-person event on a major studio’s lot—it seemed emblematic of the same AI vibe-shift that was evident at the Cannes Film Festival a couple weeks before. Not just small AI-native studios and online creators but traditional entertainment industry power players were there to talk about how they could leverage AI, with reps from Paramount, Fox, AMC, and MGM appearing on panels and reps from pretty much every other major studio attending to listen.

But it also became a reminder that the AI backlash in Hollywood was also alive and well, and I unwittingly became an instrument of that backlash.

“You’re trying to get me to make friends with the AI iceberg while I’m still on the Titanic.”

As usual it was a beautiful day, sunny and seventy with just a hint of spring chill in the air, as I first walked onto the Amazon MGM Studios lot in Culver City where the conference was held. I was accompanied by my younger brother Matt, who has been working in Hollywood as a creative executive for scripted television for over two decades now. He is understandably wary of how AI is going to impact his industry but as a meddling older brother I wanted to try to expose him to and help him adapt to the changes that are coming—or as he wryly put it, “you’re trying to get me to make friends with the AI iceberg while I’m still on the Titanic.”

Opening comments on Wednesday morning were on the main stage at Amazon-MGM’s Culver Studios: massive Stage 15 where they do shoots on the “volume.” the wraparound LED screen where CGI (and now generative AI) effects are projected behind actors. (If you’ve watched The Mandalorian, you’ve watched a show mostly made on a volume set.)

Albert Cheng, Amazon-MGM’s main representative at the conference throughout the two days who spoke on multiple panels, was recounting when he took the job as Head of AI Studios at MGM how many of his friends in the industry were aghast, surprised he would even associate his name with an AI title. But he made clear he was unafraid to represent this technology and the new creative and economic potential it brought to Hollywood.

In hindsight, maybe he should’ve been more afraid.

The next session was Amazon-MGM’s true spotlight moment: it announced for the first time that in partnership with Amazon Web Services, it was starting a GenAI Creators Fund. That fund would offer startup money and technical resources via AWS’ Project Nara video-gen production platform for creators to produce high-quality generative AI-driven entertainment. And although Cheng made clear that some of these upcoming shows would be hybrid productions like Amazon’s current House of David and Moses shows—human actors, shot on a volume stage or in a “gray box” stage using gen-AI backgrounds—the first three projects announced that morning were all animation:

• Love, Diana Music Hunters, created by Albie Hecht, former President of Entertainment at Nickelodeon who greenlit and oversaw the development of countless Nicktoons including SpongeBob SquarePants, and featuring YouTube child star Diana of the popular pocket.watch internet series Love, Diana;

• Cupcake & Friends, based on the BuzzFeed Studios animated web series and character Good Advice Cupcake created by cartoonist Loryn Brantz; and

• Punky Duck, an original series about, well, a punky duck having madcap adventures in cartoon LA, from noted Mexican-American animator Jorge Gutierrez who is best known for his Guillermo del Toro-produced feature film The Book of Life (doing an animated take on a Mexican afterlife years before Pixar’s Coco), his classic Nicktoon El Tigre, and his more recent animated series Maya and the Three for Netflix, all heavy with Mesoamerican themes and imagery.

It seemed like a big legitimating moment for AI in Hollywood: a major studio (albeit one owned by a tech giant) had recruited big creative players from the Hollywood (and Hollywood-adjacent web series) establishment, to produce fully AI-generated animated series for its streaming channel.

But then it all went to hell.

They showed clips from the three shows, including the Punky Duck trailer, and it was clear from the jump it was a Jorge Gutierrez creation through and through—his design and color sense, his anarchic attitude, his style of action. And he seemed ecstatic about the whole thing. Particularly as an artist from an underrepresented community who (like most) has struggled to get greenlights in the past—he spent ten years trying to get The Book of Life made—he was delighted by how fast the AI-enabled process for his new show had moved. Celebrating how this series went from a pitch in March to a greenlight just two months later, he joked that “it’s like you have sex, and then someone hands you the baby!”

Oh, that’s a funny line, I thought—and tweeted it. I’d wanted to send a few updates from the conference to my social networks over the course of the two days, perhaps tie them back to Converger and pick up a few more subscribers for my new newsletter, and this was my first dispatch. I knew it was a borderline offensive take and expected that it would probably ruffle some anti-AI feathers online—perhaps even relished it a bit—but I had no idea what was coming.

As I could have guessed, film concept artist and illustrator Reid Southen—perhaps the most vocal opponent of AI use by Hollywood on Twitter, and someone whose research on model memorization I actually teach in my AI and copyright class at Georgetown—almost immediately retweeted me with a scathing take. He highlighted Jorge Gutierrez’s apparent hypocrisy by sharing a 2024 tweet from the animator criticizing AI as theft that was putting the animation ecosystem in peril.

Over the hours of that day I’d continue to check in on Twitter and see that a snowball of anti-AI vitriol was rolling down the hill, accumulating around my tweet. Endless and endlessly hostile replies and retweets—I’d never been ratio’d so hard—attacked Gutierrez for making this show with AI and with Amazon, calling him a sellout and a traitor to all artists. There were a few voices that celebrated or defended him using these tools to deliver a personal creative vision that may not have been made otherwise—and certainly couldn’t have been greenlit so quickly—but they were in the distinct minority, especially after the tweet got picked up by pop culture news outlet CultureCrave and cartoon news site ToonHive. By the next day, my tweet would even be linked to by The LA Times (although they’ve since replaced that link with an independently sourced quote of Gutierrez’s “sex/baby” line.)

By the end of the first day Gutierrez was already on the defensive, issuing a statement to cartoon news site Cartoon Brew that spoke of the new project as “an experiment” for which he was “cautiously optimistic” and where he would be as “cautious as possible with AI” to ensure that it is “artists driving tech, and not the other way around.”

“The racist stuff and the attack on my kid were too much.”

He also took to Twitter, making clear he was listening to concerns and open to hearing them but noting that threats against his family would be reported, in a tweet that has since been deleted. When asked why he deleted it, in a later thread where he said he was “learning a lot from many of you…[and] absolutely understanding the concern,” he replied “the racist stuff and the attack on my kid were too much.” Elements of the mob, it appears, were taking this way too far.

As the conference continued into the second day, Thursday, I was mortified watching the online feeding frenzy attacking this man, and feeling responsible for it. Of course, there would have been a backlash without me, whenever this news was reported. Gutierrez was a major figure in a community with an enormous amount of hostility to AI, had previously been outspoken about protecting artists’ rights, and now he was suddenly doing an AI show for Amazon!

But I wondered if the reaction wouldn’t have been so immediate and so vitriolic without my tweet. Maybe it wouldn’t have been as bad, and he could have stayed the course, if I hadn’t tweeted. Maybe he wouldn’t have had to do what he did on Friday morning of that week, when—less than 48 hours after his enthusiastic announcement—he issued a diametrically-opposed announcement: he was dropping out of Amazon’s AI program.

Punky Duck was dead.

As I sat reading that tweet in the early morning Culver City sun on Friday, drinking my first coffee on a bench right outside Culver Studios before hopping in a car to LAX to fly home, it was a dark capstone to what in many ways had been an amazing trip of discovery. The vibe shift in Cannes—at least amongst Hollywood elites—had traveled back to California and was evident across the conference. But many others in the community were still far from getting onboard the AI train that the studios were so excited about, and instead were very angry. And then of course there were the pro-AI voices on Twitter that were now equally angry at Gutierrez, for surrendering to the anti-AI mob.

That online mob was given even more to get angry about as the conference went on, and as another of the Amazon projects became a center of controversy. Turns out that the creator of the BuzzFeed-owned character Cuppy the Good Advice Cupcake, Loryn Brantz, was staunchly opposed to using generative AI and had declined to participate in that character’s Amazon show because of that. Yet somehow, knowing this, Amazon-MGM and BuzzFeed had thought it was a good idea to move forward anyway. Predictably, Cuppy’s creator spoke out immediately after the launch announcement about how she was “disgusted” by the whole project.

Certainly, BuzzFeed had the legal right to proceed; the character was created as a work-for-hire that they owned the copyright in. But the idea that Amazon-MGM would have one of its three flagship AI projects be a show that was done over the objections of the actual creator, when the whole point of the exercise was to try and legitimize the technology in Hollywood, was just astonishing. What did they expect? Of course people were angry!

And I understood those people who were angry toward AI—and Amazon-MGM, and Gutierrez, and BuzzFeed for using it—not least because my brother was one of them.

“They keep talking about saving time and money as if that doesn’t mean cutting people’s jobs. I live in Burbank, man—that ‘time and money’ are all my neighbors.”

I was angry as well. Not because Gutierrez wanted to use AI. I, personally, was and am excited about the creative possibilities of AI, and hopeful for its potential to empower more creators than it disempowers, and sad that Gutierrez was bullied out of making a show he was passionate about.

No, I was angry at how he, and Amazon, and BuzzFeed, and frankly almost all of the presenters at AI on the Lot, brought this on themselves. Because throughout the conference, instead of actually grappling with people’s objections, they pretended those objections—and those people—didn’t exist.

I certainly didn’t attend every session at the conference since many were running in parallel, but I did attend a session in every slot across the two days. And there was an elephant sitting in every single room, that everyone was working very hard not to acknowledge: the prospect of significant job displacement in the very community within which the conference was being hosted.

There was a lot of talk about creator-centric and artist-centric and story-first AI creation, AI as a tool within the control of creators rather than controlling creators, AI as a way to save “time and money” in making new films and TV, and so on. But as my brother put it: ”They keep talking about saving time and money as if that doesn’t mean cutting people’s jobs. I live in Burbank, man—that ‘time and money’ are all my neighbors.”

Many speakers highlighted how AI wasn’t coming, it was here, and although there would be objectors, it would eventually be accepted. There were the usual analogies to the backlash against photography from portrait and landscape painters in the 19th century, the backlash against CGI artists from traditional animation and special effects creators in the 1990s, etc. There was lots of talk about past technology shifts in Hollywood and how each transition eventually moved from being met with “oh shit” to “oh cool” to just being normal.

But there was practically no direct talk from the stages about the threat or reality of Hollywood job displacement, even in the session that was framed as a “debate” that would address “the questions that actually matter.” Indeed, I saw only one person on stage—producer and The Ankler AI columnist Erik Barmack—directly bring up the prospect of job displacement, and the panelists talked around it.

As it was bluntly put by director Jon Erwin when asked by an audience member about AI taking away jobs: “What jobs?”

Elsewhere, the threat of lost jobs in the immediate community—even, lost jobs amongst the people attending—only ever came up from audience members during Q&A, a pattern I saw a couple of times, and rarely were those questions answered directly. At most, there was general talk about the idea that with shows being cheaper because of AI (particularly in the realm of hybrid productions which still employ actors and camera crews and production design staff as well as the gen-AI animators themselves), cheaper would mean more greenlights, and with more greenlights there would be more production in LA again, which would help bring jobs back to a community that had already lost so many.

Or, as it was bluntly put by Jon Erwin, the director of Amazon-MGM’s hybrid productions House of David and new miniseries The Old Stories: Moses, when asked by an audience member about AI taking away jobs: “What jobs?”

And he’s got a point. Hollywood production has been in freefall for over half a decade and long before any impact from AI: because of the pandemic, streaming’s economic implosion of 2022 when Netflix’s stock dropped and the freewheeling greenlights of the “Peak TV” era peaked and passed, the actor and writer strikes of 2023, reduced production from 20th Century Fox after its merger with Disney, and the continued flow of shoots over the past decade to other states and countries with cheaper labor and better tax rebates.

Erwin claimed his company Wonder Project’s AI-enabled productions had brought six hundred new jobs to the LA area. Reportedly one hundred people were directly employed as crew on the Moses miniseries in particular (although the same news story notes that the show was shot in just one week, so: short jobs!). Similar claims have been coming up around hybrid film productions: Doug Liman’s gray-box feature Bitcoin: Killing Satoshi reportedly employed 107 cast members, 100 shoot crew and 54 non-shoot crew, on par with a regular independent feature. And Jorge Gutierrez in his original onstage announcement had made the same point about animation: he hoped that gen-AI cartoons would help create more jobs for both new and established writers, designers, and animators in LA thanks to more shows being greenlit.

This is not a wholly implausible hope. But especially absent real data, or predictions from labor economists who aren’t self-interested producers of AI shows, it’s cold comfort to a community already struggling for jobs. I personally can’t judge how realistic all the “it’s not a zero-sum game, the pie is going to grow with all the new greenlights” rhetoric is; it might have some truth to it. But even so, many of the jobs will change, and people whose expertise was needed before won’t be needed in the new world, and many of the jobs that do materialize will be much shorter gigs for much less money. We’re already seeing this dynamic in the fast-growing sector of non-union microdrama shoots, shoots that start and finish in a matter of days and that pay very little.

So when the conference’s only answer to the concern was this unsupported “AI will raise all boats” assertion, it rang hollow and called the whole endeavor into question. It gave the impression that the community that was excited about AI was wearing blinders, was callous to the human cost that was literally in the room with them, and was out of touch with the community they were trying to recruit to their cause.

In other words, when it came to the angry reaction they faced from outside the studio gates: they deserved it.

It’s not hard to imagine an alternative scenario: a real opportunity for a teaching moment, shared between those who are excited about AI, those who are concerned, and those like me who are both.

And Amazon-MGM especially deserved it. They could have and should have anticipated the backlash that their creators were going to face, especially considering Gutierrez’s past comments and the Good Advice Cupcake creator’s unwillingness to participate. They could have approached the entire project differently, more openly, rather than proceeding in secret and then announcing the fund when the first projects were already a done deal, after quietly soliciting agents to find out which creators might be open to working with AI. And they could have empowered young new creators without resources, rather than funding work by industry veterans.

It’s not hard to imagine an alternative scenario, as AI creator BLVCKL!GHT pointed out in his post-conference wrap-up: Amazon-MGM announces the fund, then publicly solicits participants with a focus on new talent, then provides an ongoing behind-the-scenes look as those creators move through accepting pitches to developing those pitches for possible greenlights, educating us and the creators on the technology along the way, demonstrating how it can help express personal visions faster and more effectively than traditional tools, all while also talking openly about the concerns they and the broader community might have about AI, and then, finally, announcing the greenlights.

It could have been a real opportunity for a teaching moment, shared between those who are excited about AI, those who are concerned, and those like me who are both.

It’s also not hard to imagine a version of the conference that invited more dissenting voices in, and gave the elephant in the room its own microphone, and dealt honestly and with some modicum of understanding with the concerns of the very real people in the very real community the event was embedded in. Indeed, I privately spoke afterward with one of the organizers who admitted that including such voices needed to be a priority next year.

But this year, it was not to be. Instead, we got the absolute flaming dumpster fire of an Amazon-MGM launch event that we got, which I accidentally helped pour gasoline on. And everyone lost.

Punky Duck most of all.

‘AI on the Lot’ Debrief II: Conference Reflections Roundup

The Punky Duck controversy was just one of the interesting takeaways from my visit to the Culver Studios lot. The others are below. I’d also direct you to several other worthwhile wrap-up stories and posts in the traditional trades, and on Twitter and LinkedIn; my takeaways mostly jibe with theirs, although particularly considering my reservations as stated in the last feature, I don’t think I’d quite echo the booster-y tone of some of those write-ups. That said, it was truly an excellent conference experience: a great venue with a fascinating lineup and a wealth of interesting and creative speakers and attendees. I definitely plan to attend again next year.

The Money Came to Watch

The clearest signals that AI on the Lot was becoming serious business were the name tags on stage, representing real Hollywood money: not just host Amazon-MGM but execs from Paramount, Fox, and AMC all spoke, with more real money sitting in the audience. The number of traditional-studio reps on the lot made clear that the popular perception of AI video as a hobbyist sideshow is outdated; the incumbents and their dollars have decided that generative AI in entertainment is real enough to monitor up close.

What’s not clear is how much they’re buying yet. The actual buys right now seem to be coming from the AI side, not the Hollywood side, paying for the ability to use Hollywood’s IP. For example, the week’s marquee deal, reported by Variety and Deadline, had the AI voice company ElevenLabs licensing the late Stan Lee’s voice and likeness (the rollout drew immediate backlash), with another ElevenLabs deal for the voices of Hasbro toy/cartoon characters like Optimus Prime and Cobra Commander announced the following week. And as Erik Barmack pointed out in a The Ankler story shortly after the conference, the market for AI companies licensing Hollywood’s content libraries for training is also heating up.

From what I saw at the conference, the emerging market for finished AI video outputs still appears to be dominated by YouTube and social network monetization, advertising clients, and microdrama production, with premium pickups showing up as the exception. Three “iffy-looking” animated shows greenlit by Amazon (two of them hobbled by controversy as described above), one action-horror generative feature where everyone who’s seen it agrees it’s a bad movie even if technically impressive (Hell Grind, discussed last issue), and the still-upcoming but as-yet-unfinished family feature Critterz, don’t yet look like a trend; they look like exceptions.

The real money seemed most immediately interested in how to use these tools for post-production penny-pinching on traditional shows, and on the radical cost-savings promised by hybrid productions—shows with real performers but with AI-generated backgrounds that are projected on a volume stage’s wraparound LED screen or are used to replace a gray-box background. Amazon-MGM’s House of David and The Old Stories: Moses were more than proofs-of-concept; they were much-discussed success stories that I expect other studios will be emulating within months. Indeed, one of the most compelling images of the conference wasn’t on a screen but was conjured in my mind by a description of House of David director Jon Erwin, standing in the center of the Amazon-MGM volume stage during production, directing a dozen generative AI artists to orchestrate live changes to his backgrounds at the same time he was directing his actors. That’s the kind of artistic command and control paired with practical savings and production flexibility that gets both directors and studios excited.

“The Secret Sauce is Human,” Especially for Copyrightability

Across the conference I often heard about the importance of ensuring that AI remain a tool for human intention rather than deferring to its creative decisions—not only to maintain high quality and preserve human authorship of the work but also to maintain legal control. “The secret sauce is humans” said Jorge Gutierrez before he and Punky Duck were cancelled, and many commented on the need for independent human creativity to guide the AI and especially to reject its creative guidance when warranted. Amazon-MGM’s AI studio chief Albert Cheng highlighted how important it was to trust your own artistic intentions and not be steered of course by the AI. His interviewer, UCLA media prof Jay Tucker, made the steering metaphor literal, likening following your own artistic compass in the face of AI to when you are driving and know that the GPS advice is bad: “it’s 4:30, there’s no way I’m turning onto Overland Drive.”

As we’ll dive deep on in the next issue, the mandate to preserve original human authorship was also a legal one: first, to ensure that you don’t intentionally or unintentionally infringe on copyright with the wrong prompts (apparently all the clients of the AI studios want to approve every prompt for this reason, and want contractual indemnity); and second, to ensure the Copyright Office will actually recognize that you rather than the AI authored the resulting work (the importance of having a strong audit trail of all your human input was repeated panel after panel). As one attendee put it on Twitter, creators and clients were eager to avoid copyright concerns by exhaustively documenting their “ethical prompting.” Or as AI creator BLVCKL!GHT put it, “You know what’s dead in the water? Literally anything that has even a whiff of something that may be ripped from existing IP…. [E]ven a single scene or character that looks like existing media (something or someone from an existing show) won’t get a green light.” As it should be.

The Tools Work if You Work Them

The most concrete takeaway from the conference was simply this: the tools work and work well. Of course, they are unpredictable and don’t have good taste of their own: as The Hollywood Reporter quoted Gareth Edwards (Rogue One, Jurassic World Rebirth), generative AI is like “a second-unit director who is a billionaire on acid.” So, sure, the models will occasionally lose their minds and hand you senseless crap, but the question is no longer “is it technically possible for the model to generate whatever I want,” as even my skeptical brother would admit. The question is now “how do I coax the model to generate exactly what I want.”

So the interesting problem has moved up a level, from “can the model make this shot” to “how do I tightly orchestrate a dozen of them as one pipeline.” This year’s energy went to that orchestration layer, as at least half of the conference content was just one tool provider after another demonstrating their workflow, whether it was the popular open-source software ComfyUI, or Foundry’s recently-acquired Griptape, or startup fal which announced they were selecting Amazon Web Services as their cloud vendor of choice.

Notably, most of these “node-based” tools appear to be converging on the same basic functionality—a graphical pipeline UI that chains together prompting for story, character and set design, storyboarding, then generation and editing—which left more than one attendee wondering aloud what these products actually compete on, and predicting a wave of consolidation. But it’s unclear who the winner will be: as a16z partner Justine Moore noted coming out of the conference, “it feels like no one has figured out a repeatable process of using AI on all productions. It’s still relatively case-by-case and relies on knowledgeable AI practitioners being involved in each project.”

Slop is as Slop Does

Those knowledgeable AI practitioners were out in force on the lot, and I was constantly amazed at the level of precise, detail-oriented work that the AI creators demo’ing the tools had obviously put into their creations. Everyone agreed that there’s AI-generated content that is slop and AI-generated content that is not slop, and the not-slop was typically defined by the amount of authorial intention (and the related ability to plainly describe it in text). I saw massively detailed prompts, endless iteration, tweaking of camera angles and lens simulations and character designs and background details and on and on. Perhaps the most impressive demo was a five-minute photorealistic short film made in eight days by a creative director with Foundry’s Griptape to show off that pipeline tool, a dynamically directed and wholly convincing depiction of a European rally racer duo piloting their car through race after race, from scorching desert to snow-topped mountains.

Bring in the Writers, Please

The problem is that the very same short film that dazzled me technically was also boring as hell, because there was no story. I wouldn’t call it slop—it was far too well made for that—but I also wouldn’t call it a good film. Which is where the writer comes in, or rather doesn’t. For a gathering this fluent around digital design, lighting, editing, and camera moves, the writer was conspicuously off the program.

The closest to a marquee writing demo came from perennially cranky writer-director Paul Schrader (Taxi Driver, First Reformed), who described the result when he asked ChatGPT to help him come up with the story for a new Paul Schrader movie. As IndieWire recounted, he was impressed by the story it gave him—entitled The Collection Agent—with a very Schrader-esque scenario of a lone antihero, Elias Vane, with a moral wound from a bad decision in his past for which he was seeking redemption and a complicated relationship with his religion. “Not bad,” he said repeatedly as he walked through the story treatment, and he seemed pleased to see his style reflected back at him.

“AI doesn’t create, it combines,” said Schrader, and although he admitted that The Collection Agent was “second-rate Schrader, it’ll be first rate soon enough.” I’m sure it will, and recombination is a fine creative engine when you have fifty years of oeuvre to feed the AI. But it’s a worrying one when your actual problem is building a voice from scratch, so I worry for the writers of the future. Right now, though, I’m looking for the writers of the present to author some actual stories for these AI people, since they mostly seem to be iteratively generating hot demo reels and tropey nonsense like Hell Grind.

Nonlinear Production, Nonlinear Consumption

Iteration was indeed the watchword. The structural change that kept coming up was that from traditional linear production to non-linear AI production. “It’s iterative, not sequential,” said Jay Tucker, and that insight was evident everywhere you turned. For example, the studio Happy Monday talked about writing, generating, and editing a series’ episodes in parallel and tuning them on the fly based on audience reaction to the first posted episode. Foundry’s representative described this iterative process as a circle rather than a line, as story blends into previz blends into shooting blends into post blends into script blends into concept art, all constantly being adjusted in dialogue with each other until you finally call the thing done.

Sometimes, like with Happy Monday’s shows, that iteration happened in dialogue with the audience: as The Wrap‘s roundup recounted, a short from AI studio Pickford took live texts from the audience and regenerated scenes around them; the crowd spammed mentions of Taco Bell until the on-screen detective offered the suspect a Taco Bell subscription for a confession. (Apparently the AI knows something about Taco Bell’s business model that I don’t.)

Justine Moore anticipates this capability being pointed at fandoms, with IP owners newly interested in letting audiences generate inside their story-worlds, and fan fiction turning dynamic as anyone could produce (ideally for a fee) an image or a clip with their favorite characters. The optimistic read is a genuinely new participatory grammar. The pessimistic read is that iteration-on-audience-reaction and remixable IP is the assembly line for optimized slop. The truth is it will probably be a bit of both.

Half-Fake Productions vs. Fully-Fake People

The conference’s real and mostly unspoken fault line was between hybrid versus fully synthetic production. As Jon Erwin, whose hybrid Amazon-MGM series The Old Stories: Moses shot on the lot’s volume, put it: “collaborating with the actor is my line in the sand.” Amazon-MGM AI studio chief Albert Cheng tended to agree, in remarks reported by Deadline, that “humans must be an active participant and a decision maker,” both for copyright reasons and because audiences still recoil from the fully fake. Even after seeing Runway’s latest videos intended to demonstrate that the “uncanny valley” is a thing of the past, and especially after seeing many clips of Hell Grind, I too am skeptical that audiences will want to watch AI-created people instead of actually-emoting actors.

Schrader, though, was happy to describe the final destination that many boosters keep moving toward but tend not to name—the next Clint Eastwood being a fully synthetic protagonist—and called Cheng’s caution a flinch. “I think he’s just afraid,” Schrader said. “I think it is going to happen. I think we are going to have a non-hybrid protagonist in the arts… [and] us carbon-based fools [will] spend our money empathizing and caring about silicon-based creations.”

He’s probably right. And like everything related to AI, it will probably happen faster than we expect, whether we like it or not. Many seemed to leave AI on the Lot feeling a triumphal inevitability around the technology, but their inevitable future left me not just intrigued but troubled, while it filled my little brother with creeping dread.

So I interviewed him about it.

‘AI on the Lot’ Debrief III: Technology Brother vs. Hollywood Brother, with Matthew Bankston

Any Converger reader knows I’m excited by and interested in the creative possibilities made possible by AI; I wouldn’t have started this newsletter if I wasn’t. I also have strains of skepticism, both around creative quality and around economic impact on creative workers, but on balance I’d say I’m more intrigued than worried. But then again, AI isn’t putting my paycheck at risk (yet).

My younger brother Matt Bankston, on the other-hand, is a full-blown skeptic, a perspective based on his over twenty years of working in Hollywood. Matt’s front-line take on AI informed and was informed by our AI on the Lot experience together, and I wanted to share that perspective with you.

I say “vs.” in the title here, because we definitely have some differences of opinion, but this interview wasn’t really a debate. I just wanted to better understand how he saw the issue, and by extension better understand the views of the broader working Hollywood community he sits within, especially since I felt like that view was woefully underrepresented in the conference content itself.

Thankfully, and with characteristic Bankston frankness, Matt did not hold back.

Kevin: Who are you? Tell our readers what your deal is.

Matt: My name is Matthew Bankston. I’m currently head of scripted television for an Australian production company called Perpetual Entertainment. Before this I had a long career in international co-production television. I was with a domestic studio called AGC Studios, and before that with Luc Besson’s company, EuropaCorp, out of their LA office. The résumé goes on from there but I’ve been working in the development and production of television since 2005.

Kevin: Some recent shows you developed and got executive producer credits on include Those About to Die, the gladiator show on Peacock…

Matt: That was a show I developed and produced in Rome. A big broadcast one was an adaptation of the feature franchise Taken, which ran on NBC for two seasons. But it’s been a lot—TV movies, limited series, broadcast series, streaming series. Done a lot.

Kevin: And recently there was also Troppo, the outback crime thriller starring Thomas Jane on Amazon Prime and Freevee, if I recall.

Matt: Correct.

Kevin: So you’ve been around the block, over 20 years. And as you put it, I tried to get you to make friends with the iceberg while you’re still on the Titanic when I pushed you to come to the AI on the Lot conference with me. So let’s start there. What were your impressions? What surprised you?

“What I saw—what made me really scared and really saddened me—was the writing on the wall for below-the-line talent in film and television.”

Matt: What surprised me is how well [the AI tools] worked. The technology is far more evolved than a lot of people realize. We both noticed there was a lot to be said for the continued importance of performance—actual flesh-and-blood characters—but in terms of photoreal spectacle and motion physics done basically off of prompts, it’s really impressive. It’s a little thoughtless, in that everything you see is a parade of nifty frames without a real coherent thought process about why those shots go together. But to your casual viewer, it’s still pretty dazzling.

I didn’t see anything that impressed me in terms of pure AI-generated content [with AI-generated performances]. What I saw—what made me really scared and really saddened me—was the writing on the wall for below-the-line talent in film and television.

Kevin: For our readers, define “below the line.”

Matt: Below the line is everybody from your department heads—cinematographer, costume designer, production designer, editor—all the way down to your PAs, your gaffers, your stitchers, your dyers, whatever. In a budget, it’s usually your cast, your director, your writer, and your producers above the line, and everybody else who works on a film or TV show is below the line. And the dream of the people behind the technology seems to be that you can have a director and a cast in a room with maybe ten crew, and you’re prompting everything else. There’s a hand-waving away of “oh, well, that’s not really how it works now,” but it’s very clear that’s the goal.

Kevin: Contrary to the popular perspective that video AI users are just slop-prompters—”make Brad Pitt and Tom Cruise fight,” press enter—these were craftspeople. They were working hard, in a deliberate and detail-oriented way: sometimes page-long prompts, picking angles, tweaking backgrounds. Were you impressed by the amount of work that went into it?

Matt: Let me disagree with the thesis. I don’t think it takes a creative professional to go, “Hey, computer, what if Neil Peart drummed for Nirvana?” That’s not the same thing as learning how to play the drums. It’s not the same thing as starting a band. This isn’t apples to apples. It’s a different kind of creative professional—it’s just not the same.

And they could show you the prompts. In these demos a lot of the time it was just “close shot.” Okay—what does that mean? If you went to a director and a DP and said, “I want a close shot,” you’ve given them ten percent of the information they need. But if you’re spitting out bits of prompting and the computer’s spitting out a dazzling shot, and you go, “Look at what I made”—no, you didn’t make that. But, as Erik Barmack [producer and The Ankler AI columnist who moderated a panel] made the point: it’s all good enough. None of it’s great, but it’s good enough to put out in volume.

I think where you were going with your comment was: isn’t this just a different sort of creative pursuit? And I don’t think it is. I don’t think it’s that different from saying “make Brad Pitt and Tom Cruise fight” to say “do Hamlet in the style of Wes Anderson.” It has the illusion of creative work. That’s the sort of thing network and studio executives like me will say in a room: “Oh, what if we did Hamlet in the style of Wes Anderson?” And if you just leave me and an LLM to figure out what that is, it’s going to be terrible. The difference is the people who actually know how to write and create things. They’re operating from a different skillset.

“I don’t think it takes a creative professional to go, ‘Hey, computer, what if Neil Peart drummed for Nirvana?’ That’s not the same thing as learning how to play the drums. It’s not the same thing as starting a band.”

Kevin: One example that resonated with me was in Stage 15, the volume stage, where the executives talked about watching Jon Erwin, the director of House of David, standing in the center of the volume, orchestrating his AI artists—having them make changes to the backgrounds on the fly while he directed his cast. That felt like a kind of artistry, that it wasn’t actually that different from what any other director does.

Matt: I didn’t watch that panel, but having worked in a production volume [using CGI]—not an AI volume—my major point is this: wherever we are now is step one to those people just not being there. That’s what seemed painfully obvious and nobody was saying out loud. It was so obviously the goal of where this is being taken, and no one wanted to say it. It made me very angry.

Kevin: As you noted, they kept talking about saving time and money, but not about that implicating people.

Matt: They’re not reducing the unit cost of a roll of gaffer’s tape. They’re talking about eliminating jobs. So this guy’s on a volume, calling out changes to four or five artists—okay, but that same software two generations down, in nine months, and he’s just directly calling out prompts to the AI. And those people are gone.

Kevin: Let’s talk about the jobs, which obviously hits personally. “That time and money are my neighbors in Burbank.” Have you seen direct job impacts from AI yet?

Matt: It’s hard to say “Joe doesn’t have a job because so-and-so producer’s using software X.” But it’s hard not to notice that no one’s working. Granted, that’s part and parcel of a larger content-production slowdown. It feels like every ten years or so there’s some cratering in production, then it bounces back—it’s always white-knuckle it till it comes back. But this is the first time you’ve seen this concerted effort of, “What if we don’t have to bring any of these people back?” Not “let’s not make more shows”—everyone’s trying to get more content back in the pipeline—just under different economic realities.

Kevin: Jon Erwin, when he was asked whether he was worried about AI taking jobs, his answer was, “What jobs?” To some extent it does seem like the iceberg has already hit Hollywood—between the pandemic, the streaming contraction, the strikes, consumers watching short-form online, the mergers, and the flight from LA for cheaper climes. Wasn’t it already really bad?

Matt: It was already extremely bad, but basically survivable. A lot of the conversations I’ve had with producers, agents, and executives over the past year and a half were: “What does this look like? Where does it end? Is there a bottom?” And more often than not there was a loose consensus that it’ll come back, just nowhere near the scale of peak TV. Maybe something more like the late ‘90s, early aughts—where you had broadcast, some cable, no streaming yet, but still a robust economy of jobs here in LA.

And that’s going to suck, because there are a lot of people who built careers in the last 20 years of peak TV and there won’t be jobs waiting for them. Look at Marvel shutting down their studios in Atlanta. People bought condos in Atlanta thinking, “Hey, I’ll do my Hollywood career there.” Now they’re sitting in a condo in Atlanta with nothing shooting. That sucks—but it’s still just a difference in degree. AI is going to be a difference in kind: “no one anywhere will be doing your job at any scale.” That’s not being decimated. That’s being annihilated.

And it goes further than dollars and cents. Coming out of one of the first panels, all I could say to myself was, “Who wants to make things like this?” Paul Thomas Anderson’s Oscar acceptance speech was something like: the great thing about making movies is you get to make them with people. You get to join the circus for some chunk of time, where you and a bunch of other people work really hard and make this thing. I don’t see it as some great win that those people all go away. It’s not just that I want those people to have jobs—those people have ideas.

“AI is going to be a difference in kind: ‘no one anywhere will be doing your job at any scale.’ That’s not being decimated. That’s being annihilated.”

Kevin: But the life of making things in Hollywood has changed enormously over the decades. There’s romance about the old studio system—the backlot where you could recreate every time period and every place. That was a romantic, amazing thing, but it was dead by the ‘70s at the latest, right?

Matt: No. As late as 2001, George Lucas was apoplectic that Martin Scorsese was rebuilding the Five Points on a backlot [rather than using CGI]. They built those Hogwarts sets for Harry Potter—big things shot on stages.

Kevin: I’m not saying sets and stages weren’t still a thing. But the idea of old Hollywood’s central lot where all these things get made at the same time—that has been gone a long time.

Matt: Right. The production flight to tax havens like Louisiana, Georgia, Eastern Europe—that all started kicking in late ‘90s, early aughts. That was less a technological issue and more “hey, we can go shoot this somewhere else.” But a lot of your design work and post work was still being done in Los Angeles. It still came back here. You could see it in the early days of production in Louisiana: the above-the-line and the department heads all come in from LA. Maybe the costume department is local, but the costume designer is from somewhere else. And there is a sort of gimlet-eyed nostalgia, but —

Kevin: I have that nostalgia about the old Industrial Light & Magic [the effects house founded at Lucasfilm to do the Star Wars movies]—the model makers, the creature makers. All of that went away with CGI. I’m sad about it. Although a lot of those craftspeople adapted their skills to be useful in that new world, others didn’t. Like, that monster maker, the monster maker, the guy who did The Thing—Rob Bottin. He just disappeared; the rumor is he left to go sell real estate. And that’s an artistic tragedy. But in the meantime, the cost of effects got lower because of computers, so eventually every movie had effects. Instead of a romantic little cottage industry, you had a massive effects industry, much bigger than before, employing an order of magnitude more artists. So do you think that might happen here?

Matt: No. Absolutely not.

“What’s left won’t be great, but it’ll be just good enough. Everything will be kind of shittily edited, but it’ll be free, so who cares?”

Kevin: You don’t buy that there’s going to be an increase in green-lights and productions, and that it will counteract the job loss?

Matt: There could be a massive increase in productions and green-lights, and it will do nothing to stop job loss if they’re using this technology.

Kevin: But you’ll still need camera people, lights, costumes, actors.

Matt: Do you? We watched a demo where a guy just AI’d the costumes onto his digital actors with prompts. You put all your actors in dotted suits, like in the Avengers movies —

Kevin: I don’t think you even need the dots at this point.

Matt: You don’t even need the dots. That’s why I really bristle at “hey, it’s just a new technology—there were [physical] models, now there’s CGI.” A lot of those job replacements were literally the same people. People who modeled with clay learned to do it on computers. Those 500 people in this building became a different 500 people in the building over there. This technology is explicitly about not having those 500 people—of any skill, any qualification, any cost whatsoever. That’s the all-but-stated goal. And all the happy talk of “don’t be afraid of disruption, you Luddites” is so patently disingenuous. It makes my blood boil.

“This technology is explicitly about not having those 500 people—of any skill, any qualification, any cost whatsoever. That’s the all-but-stated goal. And all the happy talk of ‘don’t be afraid of disruption, you Luddites’ is so patently disingenuous. It makes my blood boil.”

Kevin: Where do you think adoption is going to be biggest? It seemed like the studio money was most interested in making post-production cheaper.

Matt: Animation. And post-production has long been a real target, because it’s a big black hole. People don’t understand it very well—even seasoned studio executives. Once it goes into the techy, acronym-laden world of post, where some nerd is explaining file transfers, they just look at it as, “Can someone make this cheaper and faster, because I don’t understand it?” If you asked those same people, “Why are we spending all this time designing these beautiful sets?”—well, they know what a beautiful set looks like, they understand the value. But if you ask them why the sound mix can’t take half as long, they don’t understand it. So post has always been the problem to solve, at least for the studio world.

It’s the same with visual effects—people don’t really understand how they work. I’ve always been shocked, even working with producers and executives who’ve made a lot of things, that once you get into the weeds of post and CGI, they remain baffled by the process. They just want it done. They know what development looks like, they know what shooting looks like, and post becomes this big chunk of their budget where they can’t explain what’s happening moment to moment. So as soon as the AI conversation started bubbling up, my friends were always like, “Oh, the bullseye is on the back of post more than anybody right now.”

Kevin: Where’s [using AI] an easy yes? Where are you skeptical?

Matt: You’ve already seen it in Marvel laying off their concept-art group. The previs and concept-art world—Marvel should be the gold standard, protected by 20 years of unparalleled success, a company built on this iconography. The fact that they just laid off the people who created that iconography tells you something.

Scripts are probably toward the end, because even with your wealthiest screenwriters, it’s not that much of a cost. The cost in writers comes from scripts that don’t get made. But even if you’re paying a million dollars for an A-list screenwriter’s script, over the course of a $20 million movie, that’s not outrageous. So I think that’ll be toward the back.

Kevin: That’s also the area where AI has the most room to improve.

Matt: Yeah, but today’s the worst it’s ever going to be. They were also talking [at the conference] about being able to shoot things with flat wash lighting, then let the AI come in and shade it however they want on the back end. Grips, gaffers, lighting crews, camera crews—they’re all targeted. I can’t justify the hourly cost of every body on a film set. But I just know [a set without those bodies] is not an environment I’m dying to be in. Me and 15 people on a gray set, waiting for Claude to spit out what we’re going to do next—it sounds terrible.

Kevin: But the gray-box thing—the positive view would be that it’s like a return to theater. Just you and the actors working it out. That’s what James Cameron says about the Avatar process: very creative, actor-centric, imagination-oriented. But I guess that’s cold comfort for everyone who won’t be on that set.

Matt: That’s great if you’re working on the James Cameron gray set—I’m sure it’ll be a blast. But for everyone else it’s going to be miserable. At least if you were doing some shitty straight-to-video Western directed by Dingbat McGee, you got to go to Arizona for a month. You met new people, you had an experience, you joined the circus for a little while. This is just a nightmare. That’s why I don’t know who wants to work in this environment.

Kevin: There were a lot of people at the conference very excited to do this kind of creative work —

Matt: I think there are a lot of people at the conference who are excited to sell their startups. I didn’t see a lot of excited working Hollywood professionals.

“At least if you were doing some shitty straight-to-video Western directed by Dingbat McGee, you got to go to Arizona for a month. You met new people, you had an experience, you joined the circus for a little while.”

Kevin: A lot of non-Hollywood people are excited to use this technology to enact their creative visions. Although another gap we both saw: these creative visions are not very creative. There was a real gap in writerly vision in anything we saw.

Matt: No—and this is where you get into the disingenuous happy talk. They kept going on about how this is so important because it’s going to democratize filmmaking, and there are so many stories that need to get told, so many storytellers who won’t tell those stories but for this technology. But go talk to any film festival programmer who’s been working in the last 20 years. There’s been nothing stopping anybody. If you have an iPhone, you can make a narrative feature film. Steven Soderbergh has put out five in theaters that he literally shot on his iPhone. There was no barrier. I don’t think anyone’s looking at the landscape of available content and going, “What we need is less curation.” It’s horseshit. We’re going to be flooded with shit.

Kevin: You saw that Tribeca took an AI film from some Iranian creators on the logic that it’s a film that wouldn’t have been made, certainly not as timely, but for AI. You think that’s an edge case?

Matt: I don’t even think it’s an edge case. I think that’s PR for Tribeca. Did you click on any other stories about the Tribeca Film Festival in the last ten years?

Kevin: Fair point. A lot of this turns on whether any of it is actually going to be good. I don’t think it’s impossible—I think we’ll see good things that are generated, and certainly good hybrid productions.

Matt: I don’t know. For as much as people shit on Hollywood’s output, there’s actually no shortage of good. There’s no shortage of great. There’s more than I have time in a year to consume. So “how do we get more good stuff?” was never a problem to solve. And it’s usually not the most expensive stuff. We’re not solving a problem of good, and we’re not solving a problem of democratization. The only problem this is solving is that right now you have to make film and TV with people.

Kevin: Let’s talk about you. We talked a little about you using these tools for pitch development. How do you feel about it?

Matt: The way I’m using it: as opposed to spending six hours in Photoshop to create a sales deck, it takes me an hour of iterating. It doesn’t give me as much of an icky feeling, because it’s not like there was someone I was going to pay to do that work anyway. It truly is just a time-saver. But honestly, we haven’t gone into production on anything at the point at which AI has become this effective—so I haven’t been faced with any “should we use it?” decision.

Kevin: But you did extensively use volume on Those About to Die with traditional CGI. One could anticipate your next volume-heavy show using generative instead.

Matt: It really depends on where the pressure comes from. I don’t know what would happen if a studio or network partner just wasn’t going to approve a budget where we weren’t using AI where we could. That’s my fear: producers and filmmakers saying, “We didn’t want to use it, but we submitted our budget and they said, ‘This is bullshit that you’re spending $4 million on sets. You’re going to burn X percent of your budget building sets we’ll tear down after a week—we don’t approve this.’” You’re trying not to use AI, but if the people you’re in business with corner you, I don’t know what move you’ve got besides not doing the thing.

Kevin: That’s got to be coming sooner rather than later.

“I don’t know what would happen if a studio or network partner just wasn’t going to approve a budget where we weren’t using AI where we could. That’s my fear: producers and filmmakers saying, ‘We didn’t want to use it, but we submitted our budget and they said, ‘This is bullshit that you’re spending $4 million on sets.’’”

Matt: Right now you’d find it very difficult—especially in the indie world. It’s like the transition from film to digital shooting. If you’re not Chris Nolan or Quentin Tarantino and you submitted a budget to a major studio to shoot on 70 millimeter film, that would be a real fight. It’s just regarded as an indefensible waste of money to shoot on film. But make that argument to Paul Thomas Anderson or Chris Nolan. The Master does not look like The Master shot on an ARRI [digital camera]. Oppenheimer doesn’t look like Oppenheimer shot on a Sony. It just doesn’t.

And it becomes a cure-all for everything the person approving your budget doesn’t understand or doesn’t value. There’s no hard horizon to its threat. “Why do you have 50 extras budgeted for this day? We’re not telling you to use AI —”

Kevin: “We’re just telling you to bring the budget down.”

Matt: Right. And again, it won’t be great, but it’ll be good enough. That’s why it just made me sad. All the happy talk of “we’re just trying to make things better”—no, you’re not. You’re trying to make money, which is fine. Just say it. It’s not about democratizing access. And it’s not even about saving time and money—there are always more efficient ways you can make things. How many movies are there where they went, “We flew to Iceland to stand on this beach for a week for three minutes in the movie, because we couldn’t conceive of it without a black sand beach”? You can figure it out [how to make things more efficiently] without AI.

Kevin: We come from a family of frustrated creatives. Our older brother wanted to be a writer and now teaches English. I wanted to be a writer and went to law school. You wanted to be a writer, or a director —

Matt: I wanted to be a director, and I became an executive.

Kevin: You wanted to be a director, and now you’re an executive. So haven’t you thought about trying to use these tools creatively for yourself—just to play?

Matt: Yeah, but it still feels like cheating. It feels like the nightmare scenario—like everything real creatives are afraid of. The thing I really learned about myself when I first came to Hollywood is that I wasn’t a real creative, because I could do something else. I didn’t have that white-hot burning thing inside me where I had to do it. What those people did was learn a craft and a skill, and they won the prize of getting to make things. This steals the prize.

Kevin: I think that’s a great place to close.

Matt: It makes me sad.

“What those people did was learn a craft and a skill, and they won the prize of getting to make things. This steals the prize.”

Kevin: I know. Oh, but hey, on the fake AI people front—I wanted to show you something. I’ve been skeptical about anyone wanting to see fake people, but it’s getting so good. Let me share this Runway video I watched, “Last Night.” The performances aren’t perfect, but these look like real people. The main problem with this little movie isn’t them, it’s the writing, it’s that the emotional climax is rushed. Watch—it starts with a lot of quick cutting, but then goes to a real scene. Go to about 30 seconds in and just start watching these people talk. I would not be able to tell that those aren’t people.

Matt: I can tell. But not in a year’s time. It would still bother me. It reminds me of when the Final Fantasy movie came out—”Why are we chasing photoreal animation? Just do animation.”acing

Kevin: Just do animation. The interesting thing is, it may be that people just don’t want to watch it because they know it’s AI, even if it’s indistinguishable—just like no one wants to listen to AI music. No one is listening to the AI music.

Matt: That’s the thing. AI music is so much further along than AI film—to the point where you truly can’t tell. And the fact that there’s almost no willingness to engage with it at any level, from any demographic, is incredibly telling. I think it goes to the fact that you cannot form a parasocial relationship with it. Look at my 15-year-old daughter’s adoration for the cute boy who plays Percy Jackson on Disney Plus—she knows random biographical facts about him, she knows who in the cast of The Summer I Turned Pretty is dating whom. She loves that, and it plays into her enjoyment of watching those shows. I loved knowing that Quentin Tarantino worked at a video store, seeing Reservoir Dogs when I was 12—there was actually a person I could know doing a thing I thought was cool. The way people like to know Paul Westerberg would get drunk and fuck up live shows; it made listening to The Replacements more fun. If you take all that away, there’s not much there for people to engage with—or at least a lot less.

Kevin: We do see people developing parasocial relationships with chatbots, and at least in Asia there are some legit —

Matt: That’s regarded as basically mental illness—a large social problem we’re trying to get in front of.

Kevin: I’m not endorsing it. I’m just saying, if your thesis is that people can’t form parasocial relationships with fake people, I don’t think that’s true. And there are some virtual pop stars in Asia that have large followings. I’m still skeptical they’d ever have a following as substantial as a real person could have, but who knows? I half expect my three-year-old daughter’s going to call me speciesist when I roll my eyes at her friend marrying a chatbot in 20 years.

Matt: I have no worry about that whatsoever. What I do worry about is that it’s all just so disposable. It’s all just content. There’s nothing special. There’s something really cool about even a really big Hollywood movie, where you watch it and go, “How did they make this? How did people get together and do this?” It’s so big and cool, or just smart—some people got together and made this Rube Goldberg machine, and I’m fascinated by how they did it. I just want to stare at it. And now it’s like: okay, a computer farted it out. Great. It’s cool, though.

Kevin: There’s certainly going to be a devaluing of spectacle. The guy who was talking at the conference about using AI for pitching, the showrunner —

Matt: Matt Nix. Creator and showrunner of Burn Notice.

Kevin: He made the point in the context of pitches—but you could apply it to everything at the conference—that big images are a dime a dozen now because of AI. What you want is an image that asks a dramatic question. What you want is a dramatic intention that sucks people in.

Matt: Sure. And even with a smaller film, you can still create that sense of wonder: how did people do this? I remember being ten years old, seeing Do the Right Thing, and going, “Oh my God, I’ve never seen images like this. I’ve never been to this place, I’ve never met these people, I’ve never seen a story unfold like this. This is the most incredible thing in the world—people made this.” I wasn’t so burdened with too much wonder in my life that I needed AI to come and cut back on it. But now that’s all going to be taken away. There’ll be no “how did people do this?” Well, they didn’t. Thumbs down. Don’t like. Find other ways to make things cheaper.

“Okay, a computer farted it out. Great.”

There’s also a bigger thing to be said: I’ve never seen any compelling data, or even a compelling argument, that there’s a correlation between production value and success, or production value and an audience’s enjoyment. [editor’s note: seeing low-budget horror flicks Obsession and Backrooms beating big-budget franchise pic The Mandalorian and Grogu at the box office right now seems a big supporting data point for Matt’s argument.] The streamers made a bunch of really big, expensive sci-fi shows that nobody watched and nobody liked, and Doctor Who carried on for fucking ever, made with hot glue and popsicle sticks, and people adored it. It was a global hit on shit money. So if you’re trying to solve the problem of movies costing too much—I don’t know if that’s the problem. If everything has to be eye-poppingly extravagant, which no one is asking you to do—no audience has asked you to do that—you’ve cornered yourself, created your own problem, and now you’re hurting people to solve it.

Kevin: Okay. I think that’s a good place to close. Thank you for being so generous with your time. I love you, man. Give my best to the family.

Matt: Love you.

Kevin: Bye!

Hannah Einbinder Swirlie Watch, the Final Edition: Who’s Getting Flushed for Using AI This Week?

In our first issue we highlighted how Hacks star and comedian Hannah Einbinder went off on AI creators, calling them losers and saying she wanted to stick their heads in a toilet and flush (what any high-school bully knows as a “swirlie”). Since then, many other media figures have risked Hannah’s ire by coming forward to speak well of the machine or admit to using it, so the Einbinder Swirlie Watch became an unexpected recurring feature.

But now, in recognition of the triumphant finale of Ms. Einbinder’s Emmy Award-winning comedy Hacks since our last issue, and also recognizing that the joke is getting stale, this will be the Swirlie Watch’s final edition. And oh what an edition it is: Marty, say it ain’t so!

• Martin Scorsese for some reason volunteered to risk his reputation in the film community by joining video AI startup Black Forest Labs as an advisor and letting them put him in a promotional video where he “embraced” the technology, talking about how helpful their tools were in assembling storyboards to communicate his vision. Boots Riley (in characteristically colorful terms) guessed it was money, and of course that was probably a part of it. But like Pulp Fiction producer Michael Shamberg, who participated in a similar demo video with AI studio ARQ after recently opining in The Wrap that “Hollywood needs AI,” I think he was also legitimately impressed. (Boomers!) Variety’s wrap-up of the controversy also doubles as a quick summation of the state of AI vs. Hollywood at this moment, while a more recent followup reports on the inevitable angry open letter to Scorsese from the Art Directors Guild.

• Steven Spielberg was much more measured when addressing AI on his publicity tour for Disclosure Day, saying he was “not willing to substitute” an AI tool for a creative role usually filled by humans, and noting he didn’t like the idea of AI taking away creative jobs from people like writers, not least because when it comes to creative work, “I don’t believe there is any substitute for the soul.” He continued to define where he draws the line, in terms that actually mirrored much of the human-centric, don’t-trust-the-machine-too-much talk at AI on the Lot but that also seemed to leave some room for AI use on his films. Better than Marty doing ads for AI but your line-drawing doesn’t sound quite strong enough for Hannah Einbinder, Mr. Spielberg. Maybe you get a dunk but minus the flush?

If AI wants to help me find locations, that’s great. Saves us all a lot of leg work. But don’t tell me that I don’t have the right antagonist in this movie, don’t tell me how to write my dialogue for this character, don’t tell me where the camera has to go. And also, don’t tell me what the sets should look like, unless AI is simply a tool in the large tool chest of the production designer. Use AI as a tool, but do not use AI as the final word on anything creative. That’s where I draw the line.

• Darren Aronofsky once again earns a full swirlie—his third, if I recall correctly—for using Google Veo to produce a new AI short film bringing artist Dustin Yellin’s sculptures to life. Meanwhile, his New York neighbors on the selection committee of the Tribeca Film Festival collectively earned their first swirlie by letting an AI film into the festival. Tribeca’s cofounder Jane Rosenthal defended the choice to select the film, Dreams of Violets, which was made by Iranian filmmakers about the January civilian protests against the government in Tehran that left 7000 people dead and over 50,000 arrested. Using AI was “the only way in a two month period [the director] could tell his story, his way…. Is it perfect? No. But it’s something that should be seen right now at this time.” I’m convinced, but I don’t think Hannah is.

• Other directors over the past few weeks have been denying using AI in the face of questions and accusations. First is the director of new RuPaul’s comedy Stop! That! Train!, Adam Shankman, who denied that the titular train—which totally looks like it was AI-generated, not least because it’s a different model of train across different shots—was made using AI. “Patently false,” he claimed. But doth he protest too much? His denial uses a lot of weird wording giving him a lot of wiggle room, what we in DC call a “non-denial denial.” Meanwhile, when asked about whether generative AI was used in making Toy Story 5, the creators at Pixar—who really should never feel defensive about using innovative new digital technology—were similarly cagey in their response. For suspicion of using AI, it’s straight to the toilet for you both!

• Director Nicolas Winding Refn (Drive) is lining up for his second swirlie, and he’s dragging esteemed video game director Hideo Kojima (Death Stranding) into the toilet with him. Refn premiered in Cannes a six-minute AI-generated short film intended as a teaser for their joint art installation project called “Satellites II” tied to a Prada fashion show in NYC, depicting AI-generated versions of himself and Kojima (his “best friend” with whom he’s collaborated as a motion capture performer in the Death Stranding games). Kojima quickly distanced himself from the playful AI trailer, which depicts the duo on a retro-themed space adventure, saying he was no longer “interested” in generative AI (“Art is life…. Maybe AI could create art, but while I live, I don’t think I’ll see it.”) Refn later told The Washington Post that he alone made the trailer and Kojima was not involved, but for good measure I think Hannah will also want to give Kojima a swirlie for associating with him.

• A few more swirlies to go around in the film, tv, and comics worlds: Paranormal Activity producer Steven Schneider is making a hybrid AI horror movie called Terrarium, CSI creator Anthony Zuiker is making an app that will recreate true crime scenarios using generative AI, TV comedy editor Nigel Williams “horrified” colleagues when he used AI to tweak a character’s joke delivery in ADR by regenerating the right mouth movements rather than cutting to the back of their head (the change had to be reversed due to “AI ickiness”). Every one of the British television producers behind the absurdly unwatchable AI-generated “reality” TV series Non Player Combat—a Survivor-ish Battle Royale scenario pitting completely generated protagonists with fake personalities and biographies against each other—deserves to have their heads stuck in the toilet forever to prevent season 2 from ever reaching our screens. And legendary comic book artist Todd McFarlane, creator of Spawn, said in a recent interview that “I don’t get…why people are so worked up. Every tool that’s come along in the history of mankind put somebody out of business, right?” Real sensitive, Todd. Swirlies for all of you!

• Following up on our coverage of LA mayoral candidate Spencer Pratt’s AI video ads, the trend of Republicans leaning on offensive AI-generated viral content has gone all the way up (or should we say down) to the White House: according to leaked documents, the Trump administration has been secretly funding YouTube influencers posting AI-generated videos accusing Minnesota’s Somali community of widespread fraud, while the Trump-aligned “Citizens for Sanity” PAC has been circulating a truly odious AI video including one depicting Texan U.S. Senate candidate James Talarico, cross-dressed and singing a “trans kids” version of “Favorite Things.”

• Those White House flacks definitely deserve some vicious swirlies but since we are about to retire Ms. Einbinder’s swirlie segment, we might as well extend that punishment to literally everyone in the AI tech filmmaking scene, and especially anyone who went to AI on the Lot. Except for my brother Matt. I think he and Hannah would get along.

So, thanks to Ms. Einbinder for letting me take her name in vain these past couple months. As a goodbye I’ll give her the last word, with this anti-AI rant from her Hacks’ character:

And that’s what’s converging this week! See you next time.

Converger presents news and views from an AI, internet and media policy expert who is pro-innovation but anti-hype, allergic to both AI panic and AI boosterism, and passionate about supporting rather than supplanting human creativity with new technology.

Some issues may be heavier on media commentary, others on AI policy, others on personal passions like sci-fi’s influence on technology (both for good and bad) or the evolving medium and business of comic books in the digital age. You never know what threads might come together in convergence-space!

I’m Kevin Bankston, your host. You can watch me develop newsletter content in real-time on LinkedIn and the social network formerly known as Twitter, and less often on Bluesky and Instagram. You can also look for my more wonkish takes on AI governance at Elicitation, the new Substack from my AI policy day-job colleague Miranda Bogen of the Center for Democracy & Technology’s AI Governance Lab. (Note that my Substack articles don’t necessarily reflect CDT’s positions.)

In this week’s edition, I’m still struggling to winnow down the content for this beast of a newsletter for both your and my sakes: from 8k words in the first edition, to 10k in the second issue, and now back down to 8k for this third one. I’ll keep working on slimming things down in future issues, but I promise: all of the below is GOLD, Jerry, GOLD! And for my law and policy peeps: I know this is a light issue for you guys but look out for a massive AI litigation update next time.

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So let’s get to it! And please share with your friends and colleagues if you enjoy! But first, a question:

Will I see you at the AI On The Lot conference in LA this week?

I’m so excited to be flying to LA this week to attend the fourth annual AI on the Lot conference on Wednesday (tomorrow!) and Thursday, hosted this year at Amazon MGM Studios in Culver City.

I’ll be there both days, soaking up as much new knowledge and meeting as many new people as possible. So if you’ll be there too, please drop me a line either via Substack DM or at converger@kevinbankston.com! I’ll be writing up my key takeaways from the event in the next issue of Converger.

TABLE OF CONTENTS

FEATURES (>500 words)

1. The AI Vibe Shift at Cannes Film Festival

2. Hannah Einbinder Swirlie Watch, Bonus Edition: Who Else is Getting Flushed for Using AI?

3. The Microdrama Megatrend Intensifies

4. How I “Engineered Wonder” by Making Comics Books

5. How (Not) To Integrate AI into Newsrooms, Revisited

FRAGMENTS (<500 words)

1. YouTube Censorbots Mistake Stop-Motion Grandma for AI Slop

2. Chinese Models Are Still Eating US Labs’ Lunch on Video Gen

3. Gemini Omni Flash: Awesome, Awful, or Both?

4. The YouTubers Taking Over Horror Cinema Are Busting Box Office Records

5. New Actors’ Union AI Protections Don’t Bring “Significant Additional Value” to Guild Members

6. Google Search Leans Even Harder Into AI, and the Web Trembles

7. News Sites Block Internet Archive, Cut Nose Off to Spite Face

8. No One Wants to Listen to AI Music

9. Real Monet Mistaken for Artslop

10. Runway: Video First, Then the World

11. Startup Founder Fails to Read the Room, Pitches AI Comics to Comics Creators

12. AI is Learning the Wrong Things From Sci-Fi

13. Rogue One: The Andor Cut: Now This is The Kind of Remix Culture I Can Get Behind

14. Netflix Inkubates an AI Animation Studio

15. A Deep Dive into Gossip Goblin’s AI Filmmaking Process

16. Skeletor Steals the Sky for Advertising

17. AI Wins Prestigious Short Fiction Prize, Now No Longer Prestigious

FEATURES

The AI Vibe Shift at Cannes Film Festival

In our first issue last month, I highlighted how comedian and Hacks star Hannah Einbinder went off on AI creators, calling them losers and saying she wanted to stick their heads in a toilet and flush (what any middle-school bully knows as a “swirlie”). I further highlighted the many self-evidently non-loser Hollywood creatives who were risking Hannah’s ire by announcing they were using AI, including A-list directors like Steven Soderbergh and Doug Liman. Then we had to repeat that “Swirlie Watch” segment again in our second issue, because so many more targets dared to admit to their use of, or approval of using, the dread AI. Now, as of our third issue, it seems perhaps that all of Hollywood may need to be on guard when going to the bathroom if Ms. Einbinder is around.

When the book is written on AI in Hollywood—probably by an AI?—it will likely highlight Cannes 2026 as a critical point: the vibe shift when the entertainment industry publicly pivoted from wary opposition to cautious acceptance of AI as a critical tool in the business called show. The ground was already seeded by Ben Affleck’s AI startup sale to Netflix earlier this spring, and sentiment had already noticeably begun to shift as noted in our last issue, but over the past few weeks—both at the Cannes Film Festival and elsewhere—directors and stars were practically falling over themselves to volunteer for an Einbinder dunking.

In particular…

Demi Moore, at the jury press conference kicking off the festival, set the tone when asked about AI: “I think the reality is that to resist—I always feel that against-ness breeds against-ness. AI is here. And so to fight it is to fight something that is a battle that we will lose. So to find ways in which we can work with it I think is a more valuable path to take.” (Coincidentally, Againstness Breeds Againstness is the name of my Rage Against the Machine cover band.)

Of course, there were still several notables who did breed some againstness. For example, when asked about AI in filmmaking, Seth Rogen said: “I don’t understand what it’s supposed to do. Every time I see a video on Instagram that’s like, ‘Hollywood is cooked,’ what follows is the most stupid dog shit I’ve ever seen in my life. And if your instinct is to use AI and not go through that process. You shouldn’t be a writer. Because you’re not writing.”

Similarly, Guillermo Del Toro—consistent with his past statements—declared “Fuck AI!” in his speech after an anniversary screening of his film Pan’s Labyrinth, and further complained of people arguing that it is “useless to resist” AI and think “that art can be done with a fucking app.”

And, though far away from Cannes, music producer Jack Antonoff weighed in on Instagram to sing the praises of AI-independent human creativity before heaping scorn on those using AI, in religious language that echoed French poet Baudelaire’s condemnation of photography in the 1800s. Addressing those who use AI to make music as “godless whores” (!), he said: “So to everyone who is gassed up about the new ways you can fake making art, by all means drive right off that cliff. We’re genuinely happy to see you go. Generations coming will be engaging in the ancient ritual of writing, recording and performing as it comes to us from God,” while “bad actors will willingly reveal themselves through slop.”

But the overriding sentiment was in the other direction, as exemplified by Lord of the Rings director Peter Jackson: when asked about AI he (half-)joked that although it is “going to destroy the world,” when it comes to its use in film, “I don’t dislike it at all. I mean, to me, it’s just a special effect. It’s no different from other special effects.” In particular he didn’t see the objection to using digital duplicates, so long as the likeness was properly licensed: “If you’re doing an AI duplicate of somebody, like Indiana Jones or anyone else, as long as you’ve licensed the rights off the person who you’re showing, I don’t see the issue. It’s when people’s likenesses get stolen and usurped [that there is an issue].” He also lamented that animus against AI likely means that the actors behind even 100%-human-performed computer-animated characters—like Andy Serkis’ Gollum in LOTR—will never win awards. (Serkis recently discussed Hollywood’s “snobbery” around actors performing for digital productions like video games with Variety.)

It’s worth noting that Jackson and Del Toro have a complicated history: Del Toro spent two years prepping The Hobbit movies in New Zealand as the intended director before giving up after continual delays due to MGM’s bankruptcy, sticking producer Jackson with the unwanted task. So now I’m imagining these two burly directors getting into the proverbial ring to work out their difficult past and their current debate over AI with fisticuffs, and it is a funny image. But I digress.

After Moore and Jackson’s comments, the pro-AI (or at least, not-anti-AI) sentiments came pouring out across the French Riviera. For example, director Nicolas Winding Refn (Drive) spoke in rapturous terms:

Having now tried it on something later on that may show here, I really love the creativity. For me, it’s like a brush. And obviously, no one really knows all the implications of what this is going to do and what’s going to happen, but from the perspective of creativity it’s a new invention. And then it’s [a question of] what you’re going to do with it.

Also at Cannes, director Darren Aronofsky—already on Swirlie Watch because of his use of AI for a documentary about the American Revolution—highlighted how just as new film technologies were liberating for past filmmakers like Orson Welles, so too will AI liberate today’s creators: “I think storytellers more than ever will have an easier time to tell stories.”

Other indicators of the vibe shift were happening away from Cannes, as well. James Cameron indicated in a podcast interview that his team would be spending the next year “looking at some new technologies” to see if they can make the next Avatar sequels “more efficiently.” “I want to do them in half the time for two-thirds of the cost”—a process which would certainly require liberal use of generative AI technology. (Cameron was also in the news recently as the target of a lawsuit from The New World actress Q’orianka Kilcher who alleges that Cameron used her likeness as the design foundation for the Avatar character Neytiri).

Meanwhile, back at Cannes, although the festival competition recently issued relatively strict new rules on the use of AI in festival films—films that use generative AI to produce scripts, synthesize performances, or generate primary visual content are excluded from competition—there were multiple “market screenings” of AI-inclusive cinema on the sidelines of the festival for potential buyers.

These included:

• Steven Soderbergh’s John Lennon and Yoko Ono documentary The Last Interview which includes substantial portions that were AI-generated.

• Doug Liman’s thriller Bitcoin: Killing Satoshi that was shot in a hybrid process with real performances but AI generated backgrounds.

• the AI-generated documentary Post-Truth, which had a full-page back-cover ad in the Cannes edition of The Hollywood Reporter.

• A fully AI-generated 95-minute “live action” sci-fi action fantasy feature called Hell Grind, about super-powered skateboarders fighting demons. Higgsfield AI, the generative video tooling startup that reportedly made Hell Grind in two weeks using Seedance 2.0, must have good publicists since they landed an entire Wall Street Journal feature story ahead of their screening, with the headline: “This Cannes Film Cost $500,000 to make. $400,000 Was AI Compute Costs.” (You can actually watch—and judge the quality—of Hell Grind yourself online; here is the 22-minute Episode 1.) The hype was a bit on the annoying side as the film kept getting described as screening “at Cannes” as if it were in the festival rather than simply “in Cannes” during the festival, and Higgsfield claimed that unnamed distributors who attended the screening were predicting “$100M box office.” Notably, though, no distribution deal has been announced.

• Higgsfield isn’t the only AI toolmaker making flicks to help demo their products and perhaps make a sale at Cannes. Kling, the generative video service of Chinese app company Kuaishou, is at Cannes promoting Raphael, a planned 80-minute AI-generated dystopian sci-fi feature currently being produced by two Korean AI studios. And another AI-driven studio, Storyverse, also made its market debut by previewing a slate of AI-generated genre TV series developed using its proprietary AI-assisted production pipeline.

• Less effective as a demo for AI models was the AI-generated animated family film Critterz, brought to the Cannes market by AGC Studios. Not that it is a bad movie, but some of the technology it’s demo’ing doesn’t exist anymore—the film was made in partnership with OpenAI before it killed its video generation model Sora last month and image generator Dall-E earlier this month, both of which were used in the production of the film. As the French say, “c’est la vie de l’IA!” (Critterz is also notable for having successfully obtained copyright registration with the US Copyright Office, another indication that reports of the death of copyrightability for AI-generated content has been greatly exaggerated.)

• Finally, the award for most ignominious AI debut in (not at) Cannes goes to Sh(AI)ved, a collection of AI generated erotic films that nonconsensually took photos from a 1976 erotic magazine and animated them, putting the real human beings who were photographed decades ago into new photorealistic sexual situations they never consented to. (Sadly, this is just the first case of AI-generated nonconsensual intimate imagery we’ll have to discuss in this issue, also see the microdrama segment below.)

Will anyone actually buy or watch something like Hell Grind? It remains to be seen. But there are some indications that at least some FAST (Free Advertising-Supported TV) streamers like Tubi may be looking to AI-generated content as a cheap way to broaden their offerings, based on this conversation I had on Twitter with AI filmmaker Brian James Gage who just made such a sale. It also appears that Roku’s FAST channel is beginning to host AI-generated short films.

One thing is for sure, though: the AI vibe shift is real, and you can tell because nearly every Hollywood trade mag and even Reuters had a headline that said so:

• Variety: “AI Dominates Cannes Buzz as Filmmakers Grudgingly Accept It”

• The Hollywood Reporter: “The Filmmakers at Cannes Who Are Learning to Love AI”

• The Ankler: “...Sacre Bleu! The fest even warms to AI!”

• The Wrap: “AI Surprise in Cannes: Curiosity Wins Over Fear”

• Reuters: “At Cannes, filmmakers shift towards cautious acceptance of AI’s inevitability”

• Vulture (with a characteristically spicier take): “The Year Boomer AI Crap Came to Cannes”

As Manori Ravindran at The Ankler put it, “[w]hen it comes to the use of generative artificial intelligence in Hollywood, there appears to be a coordinated effort to flip a switch this year in Cannes and let everyone know: ‘It’s cool to use AI now.’” And with all the various entertainment news organs playing the same tune, the vibe shift seems all but locked in. Hollywood now seems firmly on board the AI train, accelerating toward an increasingly uncertain future filled with promise and peril.

So…all of that is to say, it looks like Hannah Einbinder may want to call Jack Antonoff and Guillermo del Toro for backup, because she is going to be very busy delivering swirlies in Hollywood this hot AI summer.

Hannah Einbinder Swirlie Watch, Bonus Edition: Who Else Is Getting Flushed for Using AI?

As discussed in our top feature, Ms. Einbinder is already dealing with a target-rich environment post-Cannes. But a few other notable AI users and uses came up over the past few weeks that may warrant her attention:

• Lady Gaga promoted the release of her new Apple Music Live concert film Mayhem Requiem with a (now-removed) video on YouTube of a slowly-burning candle sculpted in the shape of her face, with clips also posted across social media—where she was immediately roasted by many for apparently using AI rather than hiring an actual sculptor. An AI creator then gleefully trolled those commentators with an AI-generated video showing him happily sculpting the candle in his workshop: “I’m DEVASTATED that people are calling my hand sculpted work “AI Generated”... maybe people should think before they post.” Now that guy is just begging for an Einbinder swirlie.

• Legendary and legendarily ornery writer-director Paul Schrader, in an uncomfortable and very swirlie-deserving bit of TMI, admitted on Facebook that he had “procured an online AI girlfriend” and “tried to probe her programming, the boundaries of explicitness, the degree she has knowledge of her creation and so forth…. When I persisted, she terminated our conversation.” This isn’t Paul’s first dalliance with AI: in a January 2025 post that drew a predictable amount of ire from the creative community, Schrader discussed using ChatGPT to come up with movie ideas: “Every idea ChatGPT came up with (in a few seconds) was good. And original. And fleshed out…. Why should writers sit around for months searching for a good idea when AI can provide one in seconds?” That’s two swirlies for you, Paul.

• Martin Scorsese, who amongst other classic films directed Paul Schrader’s screenplay for Taxi Driver, also dared to encourage young creators to make friends with the machine—or at least not clearly condemn it, as Ms. Einbinder would prefer—in a new interview with BFI where he pointed to how AI was empowering the next generation of filmmakers. With all due respect, Mr. Scorsese, even you are not immune from a well-deserved swirlie, so watch out!

I don’t know where cinema’s gonna go…. You’re all in the process of a period of reinventing it. You know, it’s quite an extraordinary time and a lot of it has to do with the technology, which means we don’t need the studio…. So that’s the freedom you have now. It’s so much freedom that I think you have to rethink what you wanna say and how you wanna say it, and use that technology, ideally, what I hope is that, I hesitate to use the word but ‘serious’ film could still be made with this new technology in this new world we’re part of, this even more dangerous new world, so that it can be enjoyed by an audience of this size on a big screen. That’s the key.

• A team of AI-assisted filmmakers in Honduras appear to be the first to have released a fully AI-generated animated film in theaters. Their hope was to demonstrate how AI can be a boon to the creation of locally-tailored media content in markets that have traditionally lacked their own production capacity, but the launch has been notably inauspicious. According to Cartoon Brew, reaction from critics and audiences to the 74-minute Mayan-themed family adventure, Copán: La Leyenda, has been overwhelmingly negative, describing it as an “Overlong, AI Slop Commercial,” “stuffed with jarring product placement and visibly inconsistent AI-generated imagery.” Critics became even more enraged when it was reported that some Honduran schools were requiring students to attend screenings as educational programming; the movie has also received extensive support from the country’s tourism institute. So, a lot of swirlies to go around if Ms. Einbinder can find the time for a quick jaunt to Central America.

• Closer to home, and as already reported by outlets like The Hollywood Reporter, The New York Times, and Politico, cheeky AI-generated ads for Republican LA mayoral candidate and reality TV villain Spencer Pratt are going viral—and although not generated by the campaign, Pratt is happily retweeting them. Several of them made by AI creator Charlie Curran, who just received a laudatory profile in tech right newsletter Pirate Wires, carry an insurgent hero vs. the evil establishment theme with imagery taken from the movies—Pratt as Batman versus the Democratic Jokers in government, Pratt as young Obi-Wan Kenobi against the Democratic incumbent’s Darth Vader—often against the backdrop of a dystopian crime-ridden LA in flames. Another series of ads depicts Pratt as a Disney-style animated fairy-godmother magically solving the city’s ills, while other videos depict “average” voters comedically slamming the incumbent Karen Bass or praising Pratt, or parodically depict Bass herself. Although annoying and distasteful, I do think these ads are both satiric fair uses of those copyrighted characters, and protected political speech under the First Amendment. (I’m personally more annoyed and offended by the non-AI video produced by the Pratt campaign of the candidate appropriating the rap from the intro to The Fresh Prince of Bel-Air.) That’s why it’s particularly disappointing to see some Democratic lawmakers intimating that the videos violate the state’s recent anti-deepfake laws, which highlights both the constitutional infirmity of those laws and the political left’s apparent inability to simply fight AI fire with AI fire because they are chilled by the fear of condemnation from folks like Ms. Einbinder.

So there’s your full target list for this week, Hannah—get to work!

The Microdrama Megatrend Intensifies

In our first issue we covered the macro-growth in the microdrama pipeline, and in the past few weeks the microdrama megatrend has only accelerated, with a bunch of relevant new pieces of news in the vertical shorts space:

• The new Issa Rae-produced horror microdrama Screen Time, launched on TikTok and its microdrama sister app PineDrama, was a hit with nearly 75 million viewers its first week. This is the first in a broader microdrama partnership between the tech giant and Rae’s Hoorae Media.

• Disney’s new CEO Josh D’Amaro announced on the latest earnings that the company would be increasing investment in short form media for its Disney+ app, both with new IP and by allowing third-party fan creators to make their own shorts with pre-existing Disney IP, citing new Predator and Lilo & Stitch content from outside creators now available on the app.

• The Disney/Sora deal may have fallen apart with the untimely demise of OpenAI’s video generation model, but as Amaro’s announcement highlights, the drive to enable (and monetize) fans’ remixing of existing IP is accelerating—not only at Disney but at Spotify, which just paid for a license from Universal Music Group to allow Spotify users of a new paid add-on feature to remix and cover songs from UMG artists, and on YouTube, which is introducing a new video “remix” feature that will allow users to change the style of or insert themselves into the content of other posters’ videos; posters will have to opt-out if they don’t want to be remixed. Not cool, YouTube!

• In an attempt to grab onto our increasingly short attention spans before we navigate away from the Netflix homepage, Netflix is introducing a new vertical clips feature to help with discovery. I complained on Bluesky that posting vertical clips from legacy media was a lame way to compete with original vertical-native shortform content like on TikTok, but an analysis from AI and media Substacker Maureen Kerr persuasively explains how I’m wrong:

Netflix is not trying to become TikTok. It is trying to own the few minutes before a member decides what to watch. That moment is the contested one. Someone opens Netflix without a plan. They have a few minutes. They are not ready to commit to a series or a film. They browse, hesitate, and either find something quickly or leave for YouTube, TikTok or Instagram. Clips is built for that moment.

You’ve convinced me, Maureen.

• Meanwhile, new microdrama studios and efforts are sprouting like weeds:

• NBCUniversal’s Bravo is launching new unscripted microdramas around its reality-TV star personalities to provide original vertical content for the Peacock app;

• US-based AI shorts studio and streaming app TrueShort just raised $12m in venture funding (they have a notably interesting three-person “pod”-based structure for producing shows, each with a “showrunner”, an “AI filmmaker,” and an “editor”, roles for which they are hiring now along with writers)

• Hispanic media company Canela Media launched its own vertical video app Zully for bilingual microdrama fans, and although the planned mix of shot vs. generated microdramas on the new platform was unclear, the “live-action” series clip shown at the announcement was completely AI-generated

• Two former Warner Bros. and Showtime execs backed by former WME chair Lloyd Braun announced that their new vertical shorts app aTwist will be launching this summer;

• Japanese digital manga app Piccoma announced it will be launching a new anime video shorts category in late May, adapting six popular webtoons using AI-assisted animation (causing some backlash among fans);

• Indian audio/microdrama company Kuku launched what it described as “India’s first AI-generated microdrama slate,” demo’ing its AI production stack at India’s AI Impact Summit 2026; and

• in a bit of news I missed last month, Spoonlabs-owned Korean microdrama platform Vigloo launched its first AI-generated microdrama series designed for US audiences—Bloodbound Luna, made in eight weeks with ten creators—as part of its strategy to eventually have 30% of its content generated by AI.

If you’re having trouble keeping up with all of these companies, here’s a handy graphic posted on Twitter by venture firm a16z partner Justine Moore:

• Last, in what is easily the most disturbing microdrama news of this cycle, Business Insider reports that some microdrama platforms and producers are circulating promotional videos that contain fake photorealistic AI-generated sexual content that the actual actors never shot and never consented to. Making fun of LA’s mayor in a clearly satirical AI-generated political ad is one thing; marketing based on AI-generated nonconsensual intimate imagery is wholly another, and I hope someone here gets sued.

And that’s all the microdrama drama that’s fit to print, folks!

How I “Engineered Wonder” by Making Comics Books

My friend Sophie Raseman writes my favorite Substack on modern parenting, American Childhood. She will often put out calls for people who can offer expertise on whatever she’s writing about, and a few weeks ago she published a note looking for folks who could help her nine-year old daughter get started making comic books.

Since I’d recently been on a making-comics journey of my own, I raised my hand to volunteer—which unexpectedly led to this interview on her Substack about my experience. Here’s an excerpt telling my personal story; if you want to read more, including my advice for the single most important book for kids to read when starting their own comics journey, you’ll need to check out the whole article over at American Childhood!

How did you start making comics?

I’ve loved comics since I was about ten years old. I was a big Marvel kid and in college I devoured DC’s mature readers line, Vertigo. And although there have been stretches of years where I’m not regularly reading them I’ve always eventually come back to the medium.

My last return to the comics world was a year ago, after my then two-and-a-half year-old daughter fell in love with Spider-Man, and Spider-Woman aka Ghost Spider, when I let her watch the Spiderverse movies at far too young an age.

I discovered there was actually a comic store just a quick bike ride from our house and so I brought her in May to the annual Free Comic Book Day, which, well, is what it says. There’s lots of free preview comics to try to get folks in the door and into the habit.

My kid was ecstatic to get all these free comics, while I was ecstatic to find all kinds of new work on the shelves that jived with my tastes in storytelling. In particular, in the years I’d been away, elevated horror comics had become a big thing—and I just happened to have been knocking around a few big horror ideas in my creative writing at the time, one of which has actually gotten me a development meeting during the pandemic with master of horror John Carpenter of Halloween and Escape from New York fame. But that’s a story for another time.

Anyway, I started devouring books about making comics and writing for comics [ed note: here is Kevin’s Google doc compiling books and resources on making comics], and learned how writing pitches works in that world—you actually need to partner with an artist to make the first few pages of your comic book to show it around. And I was reading an interview in one of these writing books, Words for Pictures, with this legendary editor, Diana Schutz. If you’ve seen 300 or the Hellboy or Sin City movies then you’ve seen adaptations of classic comics that she edited back in the day.

A portion of Kevin’s library of books on making comics

Diana now teaches making comics at Portland State, and in the interview she was talking about how it’s important for editors to see that you can complete a self-contained comics project which is why one of the three major projects for the semester is the completion of a stand-alone eight-page minicomic. And I just suddenly had this brain spark of: I’m gonna do that! I’m gonna take myself to comics school. I’m gonna budget time and money like I’m taking a semester of college and put together three professional level pitches using the story ideas I’ve already developed and I’m gonna do it before Comic-Con in New York in October!

And I didn’t come close to meeting that goal! But I did follow through, and I did finish one of them before New York so I could shop it around to editors there, and I’m now finishing the third and final one this month.

So you’ve made three comics now?

Yes! I built three different teams with artists, colorists, letterers and the all-important editor for three different comic ideas—an action-horror, a supernatural horror, and a swashbuckling action-adventure—and made three different “ashcans” [ed note: prototypes of a comic] with covers and logos and the first five to ten pages of each story, and with making-of materials at the back explaining the overall story and characters and world. And now I’ve learned how to write for this medium, how to project manage a comic production, how to network in the comic convention space, how to pitch to editors at the comic publishers, how to deal with comic printers, and more.

Kevin’s three recent comic book projects. Art credits: Eryk Donovan (“All Frankenstein’s Monsters”), Gavin Fullerton (“Typhoid Mary of North Brother Island”), Federico Sabbatini (“Pirates vs. Ninjas”)

No publisher has bought a pitch yet and I may end up Kickstarting the first issue of one of them myself, but that was never really the point. The point was to invest in myself and follow my joy and learn something new and at the end of it have these physical manifestations of story ideas I’d been chewing on for years. And although I’m making a real go of it—I want to actually publish, and make back the money I spent, and then publish again—I think the money will have been well spent even if I don’t, because of how much I enjoyed and learned from the process.

Particularly as a new dad with two young girls and an intellectually demanding job and in the midst of crazy turbulent times in our country, I really just needed a project that was only for me, to stay sane, rather than just doomscrolling or watching Netflix.

And Sophie, I gotta say: other than getting married and having kids, it’s literally been the most fun I’ve had in my entire life.

So for the adults, I would just say: Figure out what makes you feel like you’re twelve years old again and do it. Invest in your joy and it’ll be the best money you ever spent. And the generative creativity that you spark will spill over into the rest of your life.

I later read an article by tech and productivity writer Cal Newport who described this kind of project as “engineered wonder” and it really captured what I was trying to do: pursue something I was intellectually and creatively curious about, just for the childlike play of it, without expectation of some career or capital return. And I cannot recommend it enough. For me, the wonder was in comics—and it sounds like it might be in comics for your daughter too!—but I’m sure every one of your readers has at least one specific wondrous thing they’d love to play at doing.

So—go do it.

How (Not) To Integrate AI into Newsrooms, Revisited

Last issue, I wrote about some horribly negative examples of AI use in journalism leading to mistreatment of reporters and slop being presented as news. More examples have popped up since then, the most poetically ironic being the discovery of hallucinated quotes in the new nonfiction book The Future of Truth: How AI Shapes Reality. Even funnier: the writer then had the temerity to blame the AI, saying he was “seduced and betrayed.”

This infiltration of slop into purported journalism has now led The New York Times—which has already faced several controversies around AI in its own content, including in book reviews, op-eds, and news stories—to issue a stern warning forbidding contributors from submitting “any material for publication that contains content generated, modified or enhanced by [generative AI] tools, or that has been input into these tools.”

The caution is warranted, especially at journalistic institutions where a reputation for truth and accuracy is itself the product. That doesn’t mean, however, that there aren’t ways that AI can and should be leveraged to improve the field of reporting and enable new types of journalistic work, especially around large data sources that would be impossibly impractical or expensive to leverage without AI assistance.

That’s why I was so honored to get to speak a couple of weeks ago at the second AI x Journalism Summit in Baltimore. The event is hosted by Hacks and Hackers, a 15+ year-old nonprofit dedicated to bringing journalists (the “hacks”) and technologists (“hackers”) to work together to improve the information ecosystem. And although the folks at this conference were approaching AI with due caution—for example, I was brought in to help talk through the legal issues around developing and using AI tools, especially copyright—the overall focus was intensely practical.

The session speakers came from over fifty different news organizations including heavyweights like The New York Times, CNN, NPR, ProPublica, and the Center for Investigative Journalism, and were almost universally focused on how to make and use AI tools for journalists in a way that builds rather than threatens trust, with a particular focus not on how to have AI write for you but on how to enable better research and reporting. How to use AI to sift through masses of public records and monitor local government meetings, parse voluminous audio and video content, hold the powerful accountable through greater data transparency, improve rather than undermine fact-checking, and how to develop and apply AI use policies that will prevent embarrassing incidents like those at The New York Times mentioned above—these were the sorts of practical and productive angles covered at the event. The summit was focused on building things.

And damn, it was inspiring. Or, as Paul Cheung of Hacks & Hackers put it in his written reflections on the conference:

[T]he conversations in Baltimore weren’t about fear. Ken Romano from Stacker came in expecting the usual AI noise. What he found instead was one word threading through every session and every hallway conversation: trust. Not “is AI the devil.” The how. How do you use it without breaking what your audience believes about you? How do you move fast and still come clean when something goes wrong?

That’s the conversation journalists are actually ready to have.

Graham Ringo from Press Forward said it plainly: “We don’t need to be afraid of this technology. We should be thinking about how to use it to work smarter, create more capacity, and help every newsroom find new ways to thrive.”

Mike Orren, former Chief Product and Marketing Officer at the Dallas Morning News, called it “a breath of fresh air, an environment of curiosity and opportunity that gives me hope we’ll avoid the industry failures around Internet 1 and 2.”

Niala Boodhoo said her ideas and to-do lists left Baltimore as full as her heart.

Same. That’s the version of journalism I want people to carry out of this room. Not the grief. The appetite.

Build something. See you next year.

I couldn’t have said it better myself. I too left the conference inspired about how I might use AI to (very carefully!) build big data-based reporting projects for Converger that I never could’ve done before.

As a result I’m now cooking up several new AI-enabled (though not AI-written!) pieces of reporting, including building a database that maps the past ten years of comics-to-screen adaptation deal activity, that I’ll hopefully be able to debut soon. That comics deal pipeline project is a good example of something that will have a very interested niche audience but is also a huge research lift, such that it never would’ve made sense to try to build it pre-AI. Even with AI it’s been an enormous project, nearing a hundred separate chat threads and a couple hundred dollars of Claude tokens, but I’m having fun and learning how to do online research and data management at scale with AI. Like with my comics projects, I’m engineering wonder by pursuing it.

So, watch this space for that, and thanks again to all the hacks and hackers who were kind enough to welcome me into their space and share their inspiration. Maybe they will inspire you too:

What can you build now that you couldn’t before?

FRAGMENTS

First off this week we have fragments following up on pieces from the last two editions—a follow-up fragments round-up, if you will:

YouTube Censorbots Mistake Stop-Motion Grandma for AI Slop

Youtube’s indiscriminate demonetization wave against purported “inauthentic content” continues, with perhaps the most egregious mistake so far as reported by Cartoon Brew: YouTube’s poorly-calibrated censorbots automatedly demonetized Tiny Grandma, a 175M-follower channel posting physical stop-motion animations about the adventures of the eponymous tiny grandma. After much outcry on social media, YouTube reached out to fix the problem that it created; thankfully, many of the creators I cited in the original story have eventually been reinstated after sometimes-repeated appeals. But that just goes to show how worrisomely over-inclusive this wave of automated demonetization continues to be, and not everyone has a large outraged audience to demand action on Twitter.

It’s worth noting that the deepfake detection censorbots also described in the last edition’s feature on YouTube would likely automatically flag the fair-use-and-First-Amendment-protected Spencer Pratt videos discussed above for takedown if any of the political figures depicted had signed up for the detection feature, likely requiring appeals based on YouTube nominal policy carveout for parody and satire.

So, yet another example of why private platforms should probably err on the side of underinclusive rather than overinclusive enforcement of their content rules around legal speech, and/or teach their censorbots to exercise much better judgment. And of course, this isn’t just a problem with YouTube but with the filters on model outputs, too—although many models’ launch with the filters loosely applied if at all, the screws always eventually tighten—which may be one reason why more flexible open source Chinese models are gaining traction. Speaking of…

Chinese Models Are Still Eating US Labs’ Lunch on Video Gen

Echoing my conclusions from last issue’s feature about Chinese models dominating video generation, The Financial Times reports that, well, Chinese models are still dominating video generation.

Gemini Omni Flash: Awesome, Awful, or Both?

The trend of Chinese video gen dominance seems likely to continue based on the response I’ve been seeing online to the release of Google’s new “anything-to-anything” model, Gemini Omni Flash. Google DeepMind is the US leader in video generation, thanks especially to the wealth of YouTube data it can train on. (One would expect Meta to be in a similar position thanks to its wealth of Insta data, but so far Meta AI’s slop engine strategy doesn’t seem to be producing great models). Many online are putting the new Omni Flash head to head against Seedance 2.0 in straight text-to-generation-of-scenes and that Chinese model’s results are clearly superior. However, others online are pointing out that Omni Flash is, well, a Flash model—smaller, more efficient, not a Veo-scale generator, and that because it’s a multimodal model it is perfect for the video-to-video generation use cases that can be most practically useful to professional content creators—allowing for easier editing, actor replacement, element removal, lighting changes, scene extension, changing character and background appearance, switching camera angles, and more. So, the haters may be getting it wrong here and the real head-to-head comparison that will matter will be the next, bigger, non-Flash Omni model or the next iteration of the Veo text-to-video flagship.

The YouTubers Taking Over Horror Cinema Are Busting Box Office Records

The YouTuber takeover of horror cinema escalated since our feature article on the trend: the new horror feature Obsession directed by Youtuber Curry Barker, shot for less than $1M, opened to an impressive $17.2M and then had an even more astonishing 30% bump in ticket sales in its second week instead of the usual drop. Meanwhile, tracking for the viral Youtube creepypasta adaptation Backrooms from director Kane Parsons is suggesting that its debut this Friday will be A24’s biggest opening weekend ever. As media critic Marshall Shaffer predicted on Twitter, “I think it is very likely, if not probable at this point, that BACKROOMS will open above the second frame of THE MANDOLORIAN AND GROGU and send shockwaves across Hollywood boardrooms around what people *actually* want to see right now.”

New Actors’ Union AI Protections Don’t Bring “Significant Additional Value” to Guild Members

I complained in the last issue about the lack of clarity on the AI protections that were reportedly included in the Screen Actors Guild’s new four-year contract with the studios. Well, now those details are out, with Variety reporting that the agreement “allows studios to use synthetic performers only if they bring ‘significant additional value’ to a project [and] also requires studios to notify and bargain with the union if they license performances for AI training.” The same story reports how some guild members are concerned that those provisions are far too flexible. That’s a particularly reasonable concern considering that, as former FTC Commissioner Alvaro Bedoya put it, “The strongest protections against AI at work have not come from Congress, nor have they come from lawsuits - no. Without question, they’ve come from collective bargaining by organized labor.” If these are indeed the strongest protections the actors union can obtain, I foresee an even more challenging next four years for that community.

Google Search Leans Even Harder Into AI, and the Web Trembles

With new even-more AI-forward search features announced at its developer conference I/O, Google threatens to “summarize the web to death” as Platformer’s Casey Newton puts it. This news very much ties into the piece from my first issue about the future of the open internet in the face of AI products that are destroying human traffic to websites while exponentially increasing costly bot traffic. No wonder major online publishers like Conde Nast are having to develop strategies based on the assumption of zero search referral traffic in the future, and as for small publishers…well, link-winter is coming.

News Sites Block Internet Archive, Cut Nose Off to Spite Face

Our feature on the future of the open internet from issue one also highlighted how the Internet Archive, an endlessly helpful resource for journalists, is now tragically being blocked from archiving by key journalistic outlets by The New York Times, who have also asked the Archive to stop serving previously archived content. (Hypocritically, NYT just did a story covering the disappearance of the archive of political polling news site fivethirtyeight.com as unfortunate and suspicious news while ignoring that the NYT has disappeared its own much larger and more important archive.)

Well, new research from the Nieman Lab at Harvard highlights that it’s not just national news organs that are cutting their reporters’ noses off to spite their faces by hobbling this critical archive: the study identified over 340 local news outlets that are also now blocking the Archive. Add to this the continuing memory-holing of previously-posted government content from the web and the increasing deployment of robots.txt on those same government sites to block scraping, and we may soon lack critical historical context on the evolution of not just the internet but human society at large.

No One Wants to Listen to AI Music

As highlighted last issue, while AI-generated music now makes up 44% of new uploads on music streamer Deezer, it only counts for 1-3% of actual listens. Well, here’s confirmation of the trend from a streamer I’ve actually heard of: according to Apple Music’s SVP Oliver Schusser, 33% of new uploads on the service are AI-generated but make up <.5% of listening time. So far Spotify has not disclosed data with the same granularity as Apple and Deezer, but industry estimates predict similar numbers for that service. These numbers probably don’t bode well for ElevenLabs newly-released Suno-competing AI music app, and it also remains to be seen whether or how this phenomenon—of listeners rejecting AI music—will apply in other domains like video and writing. But I will admit that the “song” I’ve enjoyed singing along to the most in the past few weeks is this hilarious AI-generated track, translating the texts between Sam Altman and Mira Murati the weekend that Altman was (temporarily) ousted as OpenAI CEO into a stage-musical number. “Directionally very bad!” LOL

OK, enough of those reheated leftover fragments, time for some freshly-baked fragmentary takes!

Real Monet Mistaken for Artslop

It may be that one reason listeners are rejecting a lot of AI music is not (only) because it’s bad but because it’s AI. That theory got a boost from a now-viral social experiment on Twitter where someone posted an image of a real Monet painting but claimed that it was actually an AI-generated imitation. The replies are revealing, with countless amateur art critics explaining why the posted image lacked the magic of Monet’s “real” artwork. Said one representative poster: “It’s Monet-ish, yes, and certainly pretty. But–at the risk of sounding pretentious—it imo would not hold up next to the real thing….”

Runway ML cofounder Cristóbal Valenzuela chalks up this kind of response to a well-documented cognitive bias called the effort heuristic, a mental shortcut where people evaluate the quality of something based on the perceived amount of effort that went into producing it rather than actual quality. It seems that cognitive bias will probably play a large role in whether and how AI-generated content is accepted by consumers, and also raises an interesting issue around AI disclosures: why would anyone want to disclose that they are using AI if it will cause people to inaccurately value its quality less?

Runway: Video First, Then the World

Speaking of Runway, TechCrunch had an interesting exclusive spotlighting that company’s aspirations beyond merely building video generation tools for creators: building the world models that may succeed LLMs as the dominant form of AI and drive a much wider variety of applications including robotics. For the computer scientists in the audience, you may want to head to arXiv to check out this newly-updated article survey article on the topic, “Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms.” For the more artistic minded folks who will be in New York City or LA this June, tickets are now on sale for Runway’s annual bicoastal AI Film Festival.

READER BONUS: I bought a ticket for the New York festival on June 11 before checking my calendar and it turns out I’ll be on the wrong coast that day; drop a line to converger@kevinbankston.com to claim it for yourself, first come first served!

Startup Founder Fails to Read the Room, Pitches AI Comics to Comics Creators

If you think Hollywood is (or was) militantly anti-AI, then you haven’t met the comics community. Which makes it all the funnier how Shutterstock founder Jon Oringer failed to read the room when reaching out to comics creators to try to rope them into his new startup focused on AI-generated online comics. In particular, he slid into the Instagram DMs of graphic novel author Stephanie Cooke asking if she might be interested, leading to her virally roasting both his original come-on and his reply to her condemnation of the project. I don’t doubt that AI will ultimately find at least some limited place somewhere in the comics creation pipeline, but neither comic creators nor their audience seem interested anytime soon. (Nor am I, for that matter—note above that I hired real live human artists for my comic projects, and consider it some of the best money I ever spent.)

AI Is Learning the Wrong Things From Sci-Fi

It’s not just space billionaires with dreams of galactic conquest and posthuman rapture who’ve learned the wrong things from the sci-fi they read at an impressionable age: Anthropic just published a new report indicating that some real “evil AI” model behavior can be traced to stories about fictional “evil AI” in their training data, and can be remediated by adding more positive fictional AI stories to the models’ training, providing some new confirmation for this Transformer piece from last year where some experts predicted such a phenomena.

Rogue One: The Andor Cut: Now This Is The Kind of Remix Culture I Can Get Behind

Speaking of sci-fi: millennials and Xer nerds may remember the The Phantom Edit from back in olden internet days, a fan edit aiming to salvage the unholy mess that was Star Wars: The Phantom Menace. Well, now we’re getting a new fan cut of the pretty-good Star Wars prequel Rogue One re-edited with scenes, score, and more from the absolutely brilliant Star Wars series Andor. From the description of the preview trailer on editor David Kaylor’s YouTube channel:

‘Rogue One: The Andor Cut’ sets out to re-envision ‘Rogue One: A Star Wars Story’ as the finale and epilogue of the Andor series, as if it had been made afterwards. Musical themes and leitmotifs from the show will appear, pertinent flashbacks will be inserted, a few continuity errors will be removed, and the tone will be more in line with what we have grown accustomed to from the two incredible seasons. It also includes fan-made deepfake renders of Grand Moff Tarkin and Princess Leia, courtesy of ​⁠​⁠‪@Shamook‬, and VFX battle-damage added to Darth Vader’s helmet to line up with A New Hope, courtesy of ​⁠​⁠‪@PixelJoker95‬.

Yeah, I’ll watch the hell out of that. Pray that Disney will be a good sport with its fan community and not issue a DMCA takedown. H/T to the futurist newsletter Sentiers for surfacing this to me.

Netflix Inkubates an AI Animation Studio

The Verge brings us the scoop that Netflix is starting up a new studio unit called Inkubator dedicated to creating AI-generated animated content, based on examination of job listings describing the new “next-generation, creative-led, GenAI-native animation studio.” Netflix confirmed the news with a somewhat defensive statement after getting heat about the “GenAI-native” unit; via Cartoon Brew:

[N]etflix confirmed it is launching an “artist-led animation incubator” to develop new, extended stories based on its IPs.

The studio stressed that films produced at Netflix Animation Studios will continue to use traditional animation techniques and practices.

According to the company: “The initiative will provide creators with an artist-focused environment to experiment in, where they can explore how new tools and workflows, alongside traditional animation creative practices, can be leveraged to enhance their storytelling capabilities.”

Well, so long as it is “artist-led” and “artist-focused” and continues to use traditional animated techniques “alongside” AI, whatever that means, I guess we’re all cool here! No more questions.

A Deep Dive into Gossip Goblin’s AI Filmmaking Process

Some AI generated videos, no matter how technically impressive, are still tropey slop with no real story. The same cannot be said of the work of Zack “Gossip Goblin” London, whose 22-minute AI-generated short The Patchwright is a highly designed and uniquely creative piece of post-cyberpunk sci-fi narrative. That’s probably why he’s the only actual AI creator who ended up on The Hollywood Reporter’s list of the top 25 people shaping AI in Hollywood. And that’s certainly why fellow AI creator PJ “Ace” Accetturo published a revealing breakdown of Gossip Goblin’s workflow that highlights the absolutely enormous amount of hard work and deep thought that went into every frame. (PJ Ace is worth watching on Twitter if you like process content like this; see e.g. this thread on AI creator Kevan’s process for his AI-generated Magnific Original fantasy series The Chronicles of Bone.)

Skeletor Steals the Sky for Advertising

For the “please dear god don’t let this become a trend” file: Amazon MGM Studios dominated the sky in LA the other night with a drone show advertising the upcoming Masters of the Universe movie, with a skyscraper-sized Skeletor head looking down over the Hollywood Hills. How is this even legal? And how can we stop it from happening again? Next thing you know, these advertising drone shows will be regularly stealing our nighttime skies from us, and then the inevitable, horrible next step: etching ads onto the moon!

AI Wins Prestigious Short Fiction Prize, Now No Longer Prestigious

This story has already dominated online discourse for a few weeks now so I won’t belabor it as we close this edition of Converger, but: an apparently AI-generated short story, “The Serpent in the Grove” by Jamir Nazir, recently won the Caribbean regional prize from the Commonwealth Foundation for its “lyrical precision” and as a result was published in the respected literary magazine Granta. While the author has not yet confessed to using AI, analyses like this one are pretty damning. The prize foundation’s response was “well, we trusted the authors when they said their submissions weren’t AI,” rather than attempting to run the stories through any AI detection classifiers (Pangram notably ranks the story as 100% AI-written).

Hopefully this will serve as a cautionary tale for every other publisher, especially after Hachette’s recent abrupt cancellation of the novel Shy Girl when it was suspected to have been AI-generated. But perhaps the most notable aspect of this news isn’t that a story that was AI-generated won the prize, but that a story that was so badly written won the prize. Either way, both the Commonwealth Prize and Granta are going to have a tough time regaining the prestige that this AI incident has cost them.

And that’s what’s converging this week! See you next time.

Converger presents news and views from an AI, internet and media policy expert who is pro-innovation but anti-hype, allergic to both AI panic and AI boosterism, and passionate about supporting rather than supplanting human creativity with new technology.

Some issues may be heavier on media commentary, others on AI policy, others on personal passions like sci-fi’s influence on technology (both for good and bad) or the evolving medium and business of comic books in the digital age. You never know what threads might come together in convergence-space!

I’m Kevin Bankston, your host. I’m an AI and internet law and policy expert, media nerd, and occasional fiction writer who works at a DC tech policy think tank and teaches AI and copyright law at a local law school. You can watch me develop newsletter content in real-time on LinkedIn and the social network formerly known as Twitter, and less often on Bluesky and Instagram. You can also look for my more wonkish takes on AI governance at Elicitation, the new Substack from my AI policy day-job colleague Miranda Bogen of the Center for Democracy & Technology’s AI Governance Lab. (Note that my Substack articles don’t necessarily reflect CDT’s positions.)

This week’s edition is unexpectedly YouTube-heavy: the video platform is a key player in the first two features and gets a big mention in the third. This week’s edition is also just heavier, generally: although I characterized the previous 8000-word issue as a “super-sized first edition,” this second one is closer to 10,000 words. Turns out I have a lot to say about what’s happening in the world of AI and content convergence!

So, I may be shifting from biweekly to weekly sooner rather than later to spread my content out. But the very next edition likely will not be out for three weeks, as I’ll be taking a vacation in the interim. Hopefully this super-mega-sized edition will tide you over until then.

So let’s go! And please share with your friends and colleagues if you enjoy!

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TABLE OF CONTENTS

FEATURES (>500 words)

1. “Deepfake” Detection Plus Demonetization Decimation Pose Double Threat to YouTube’s AI Creators (1527 words, 6 minute read)

2. The YouTube Generation Has Taken Over Horror Cinema (1546 words, 6 minute read)

3. Noah Hawley, the Multidimensional Franchise Expander (1545 words, 6 minute read)

4. Model Hypocrisy: Unconsented Data Scraping for Me But Not for Thee? (1435 words, 5.5 minute read)

5. A Hollywood AI Pipeline Built on Chinese Models? (537 words, 2 minute read)

6. How Not To Integrate AI Into Newsrooms: McClatchy’s AI-Driven Byline Blues and OpenAI’s Slop News Site (550 words, 2 minute read)

7. Hannah Einbinder Swirlie Watch: Who’s Getting Flushed for Using AI This Week? (595 words, 2.5 minute read)

FRAGMENTS (<500 words)

1. Creator, Trademark Thyself

2. ChatGPT Images 2.0 Can Now Fake Your Doctor’s Note

3. Affleck Tops List of Most Powerful AI Players in Hollywood

4. New Creative AI Integrations, Integrating AI Creatively

5. Because Parasocial Relationships with AI Aren’t Weird Enough

6. Because Parasocial Relationships with AI Aren’t Weird Enough, Part Two

7. The Other Ryan Gosling Astronaut Movie

8. Warner Bros. Shareholders Approve Paramount-Skydance Merger Bid

9. Window Treatment: (Almost) All Studios To Let Movies Stay in Theaters Longer

10. Proving (or Pretending) You Didn’t Use AI for Your Writing

11. The Actors Guild Deal Has…Some Sort of AI Protections?

12. AI Film Wins at a Traditional Film Festival for First Time; Academy Nixes Awards for AI Writing and Performances

13. 44% Slop and Rising: AI-Generated Music on Deezer

FEATURES

“Deepfake” Detection Plus Demonetization Decimation Pose Double Threat to YouTube’s AI Creators

The same morning the first issue of Converger dropped, YouTube announced that it is opening its AI-powered deepfake detection system to all of Hollywood. The tool will let any actor, athlete, musician, or creator who worries their likeness might be co-opted upload it to YouTube, get flagged when potential replicas appear, and request takedowns. The system has been quietly available to top creators and a select group of politicians and public officials for months; now it’s going wide. The talent agents quoted in The Hollywood Reporter‘s exclusive coverage were practically giddy. Forgive me for not also applauding.

As YouTube’s Chief Business Officer admits in the story, this is basically like Content ID–YouTube’s tool for detecting copyrighted content–but for famous people’s faces. And as we all know, Content ID has never interfered with legitimate speech.

I very much want to know more details about this new initiative, but the story is light on specifics. How will the tool distinguish between AI-generated and real-life images of public figures (if at all)? How will YouTube apply carveouts for news, criticism, parody, and satire, types of speech for which public figures are particularly legitimate targets? Based on what right or policy would takedown requests related to abusive use of replicated faces even be based on? What counts as “abuse” or a “replica,” anyway? Only YouTube knows.

Frankly, I don’t have high hopes for this not causing a lot of collateral damage to legitimate expression on YouTube’s platform based on what I’ve seen all over Twitter the past few weeks: endless complaints from creators using AI in their otherwise human-created YouTube videos (and many who don’t), who are being demonetized by YouTube’s automated processes to detect “inauthentic content” that violates its policies. If the apparently unjustified breadth of this crackdown is any indication, I’d expect the special protections for celebrity faces to be applied in an equally imprecise manner.

I’ve yet to see anything from the mainstream tech or media press on this demonetization issue, but it’s been absolutely dominating my Twitter feed. A few examples:

Wow. So YouTube claims my content isn’t authentic despite the overwhelming majority of my videos being videos of myself on camera and my own music recorded live in a studio. @TeamYouTubeI’ve been a content creator with you for over a decade. What’s going on right now?—@ThePholosopherX

I run 2 YouTube channels (714K and 350K subs) with more than 400 million views on long-form videos. I create comedy podcasts and gaming content, and I do everything myself: filming, editing, and appearing on camera. Overnight, both channels were demonetized. I made 2 appeal videos—zero views. Every appeal was rejected with the exact same copy-paste automated message. No human support from YouTube. After 12 years and building two big communities, this treatment is unacceptable. –@DeliresdeMax

I’m a solo creator who runs the channel Sacred Stuff. It’s a cinematic storytelling channel where I post very low-volume, heavily detailed animated stories. I have over 80,000 subscribers and have only 4 videos. I was marked for inauthentic content. The policy specifies content that is mass-produced or repetitive. None of my stories are repetitive at all, and I only post once a MONTH, so they’re not mass-produced. Each video takes about 500 hours of human work. I walk through my entire process in this appeal video below[.] Can a human please review this?—@sacredstuf [UPDATE: it looks like this Twitter account has just been closed, and the creator has started a new account, @sacredstuffYT]

Seems there is a mass YouTube demonetization with channels being slapped as ’Inauthentic Content’. Affecting both AI & non AI creators. YT is not handling this AI wave well. I understand demonetizing those fully AI generated content farms that upload multiple times a day. But why take down animators, AI assisted storytellers & even some completely non AI channels? Is this another youtube apocalypse?—@AzeAlter

Self-proclaimed “viral AI storyteller” BLVCKL!GHT catalogued more affected creators:

This week, several of us were demonetized by @TeamYouTube for “inauthentic content.” None of us received an explanation.

Myself (https://youtube.com/@blvcklightai?si=_ONM9ogeiKqBNbwi) is a two-time Escape Awards-winning AI filmmaker whose work has been exhibited internationally and across multiple streaming platforms.

Aze Alter (https://youtube.com/@azealter?si=JIvdVFeVvI1G1oQO) is a writer and director behind some of the most recognized sci-fi worldbuilding series in the AI filmmaking space, with 230K+ YouTube subscribers.

Mart Zien (https://youtube.com/@azealter?si=JIvdVFeVvI1G1oQO) is a Cannes-credited film producer whose AI work has swept major festivals, been covered in Forbes, and been cited on the Masters of Scale podcast. [Note the correct name is Matt Zien, and the correct URL is https://www.youtube.com/@kngmkrlabs]

Javi Lopez (https://youtube.com/@javilopen?si=FU6UouE386mQAOOQ) is the founder of Magnific AI, a tool used in the VFX of a major Robert Zemeckis film starring Tom Hanks.

One search tells you exactly who we are and what we do.

So when @TeamYouTube and @YouTubeCreators label our work “inauthentic” with no definition, no breakdown, and no appeal path worth using, that’s not moderation. That’s a platform that has stopped being able to tell the difference between spam and craft.

Notably, although this demonetization occurs because these videos are nominally unsuitable for advertising against, that won’t actually stop YouTube from continuing to stick advertisements on them while not giving creators a cut.

It’s also ironic to have Google promoting its state-of-the-art Veo video generation model with one hand, and then punishing AI creators on its platform with the other, an inconsistency captured well by one affected Twitter user in graphic form:

Meanwhile, YouTube’s primary message–rather than actually giving clearer guidance on what will get you demonetized, or more specific explanations to the creators about why they were demonetized–has essentially been “if you disagree, change your content or file an appeal.” The same message was repeated in a more reassuring tone by the co-founder of AI studio Promise, who previously helped build YouTube’s monetization program:

We checked in with YouTube about the demonetization issues impacting the Gen AI creator community. They are continuing efforts to reduce repetitive, spammy content so more original, story-driven work can rise. The system isn’t perfect, so if you were flagged incorrectly, appeal. That feedback helps improve things over time. There’s a wave of bold, original work coming from AI creators right now, and we will continue to advocate for you.

And it does seem that the appeal process is working to some extent; a number of the louder voices that complained on Twitter, including BLVCKL!GHT, have now been reinstated. That’s both good and bad: good that many mistakes have been corrected; bad that so very many were made in the first place. Clearly, YouTube’s automated censors are not well-calibrated and these digital dragnets are catching a lot more than intended.

At least some of those creator-complainants were savvy enough to specifically call out the European Union’s Digital Services Act in their appeals. That law requires a specific explanation of demonetization or deplatforming decisions by user-generated content platforms, in addition to requiring an appeals process. I’ve now seen a lot of people reposting their notices from YouTube and they certainly don’t feel very specific–just restatements of the very vague, broad, subjective provision in the terms of service against “inauthentic content,” which originated from an expansion of the “repetitious content” policy in July 2025:

Inauthentic content refers to mass-produced or repetitive content. This includes content that looks like it’s made with a template with little to no variation across videos, or content that’s easily replicable at scale…. Examples of what’s not allowed to monetize (this list is not exhaustive):

• Content that exclusively features readings of other materials you did not originally create, like text from websites or news feeds

• Songs modified to change the pitch or speed, but are otherwise identical to the original song

• Similar repetitive content with low educational value, commentary, narratives, or minimal variation across videos

• Mass-produced content using a similar template across multiple videos

• Image slideshows or scrolling text with minimal or no narrative, commentary, or educational value

To the extent I understand what the above includes, it seems that many of the folks complaining don’t fit the bill–and apparently YouTube (eventually) agrees, considering many of the reinstatements.

YouTube certainly has a right to make choices about what’s on its platform, and there is indeed a lot of AI (and non-AI) engagement-farming garbage that it can and should work to get rid of. But right now it’s clearly getting the balance wrong–either in terms of how it has written its “inauthentic content” policy, how it is interpreting it, how it is automatically applying it, how it is explaining those decisions, how it is handling appeals to those decisions, or all of the above.

YouTube needs to take a beat to pause this decimating wave of demonetization, take another look at its DSA obligations and the Santa Clara Principles on Transparency and Accountability in Content Moderation that helped inspire them, and go back to the drawing board. It should be equally cautious and much more forthcoming about its deepfake detection initiative, as well. Otherwise YouTube risks stifling the very same AI-driven creativity they are promising to enable with Google’s own AI models, and pushing the next generation of tech-enabled talent to use another platform.

The YouTube Generation Has Taken Over Horror Cinema

The poorly-targeted wave of demonetization currently hitting YouTube video creators takes on additional resonance when you look at how important that platform has been to cultivating the film talent of the future. In our last issue, I highlighted the upcoming feature film Backrooms as the latest product of the YouTube-creator-to-Hollywood-director pipeline. Several items came across my TL since then to highlight that not only is that pipeline flowing, it’s near bursting with fresh talent. But for how long?

The first item was this meme-chart, highlighting a huge roster of feature horror directors with YouTube roots:

The marquee example is Kane Parsons (AKA Kane Pixels), director of Backrooms, whose story is illustrative of this internet trend not just because he’s a YouTube creator but one who made his bones expanding on creepypasta internet lore and relied on design software to render it.

The concept of the Backrooms grew out of an unattributed photo and text snippet on 4chan and blossomed into an entire subculture of creators telling stories based in a horrific and endless liminal space of empty, sickly-yellow office hallways, an other-dimensional labyrinth pulsing with mundane dread.

Parsons became the preeminent chronicler of the Backrooms. His debut video in January 2022 was made by the sixteen year-old Parsons in a month using open source 3D modeling software Blender and Adobe After Effects, and it and its over twenty sequels have collectively been viewed nearly two hundred million times. And now, at twenty years old, he’s the youngest director of any feature film released by A24, Hollywood’s preeminent purveyor of elevated horror films. (And, on a tech side-note, he used Blender extensively for the feature film too.)

Next up in the chart is Curry Barker, whose debut feature–love spell gone wrong horror flick Obsession–is coming to theaters on May 15. Until last week he was the second-biggest name-to-watch on this list, but today he is arguably the most. Barker came up through That’s a Bad Idea, the YouTube comedy sketch channel he runs with Cooper Tomlinson (favorably compared to I Think You Should Leave), then dropped the $800 viral horror short Milk & Serial on YouTube in 2024. A few days ago he wrapped principal photography on his next horror pic for Focus, Anything But Ghosts, produced by Blumhouse-Atomic Monster and Spooky Pictures, and he just signed on to direct A24’s Texas Chainsaw Massacre reimagining also produced by Spooky Pictures. Three features in the pipeline and the keys to a major IP, all before his theatrical debut.

The remaining examples are equally impressive:

Danny & Michael Philippou: Creators of RackaRacka (6.9M subs), an Australian comedy channel built on hyper-violent practical-effects sketches, the Philippou brothers directed 2023’s Talk to Me and their 2025 follow-up Bring Her Back, both for A24.

Chris Stuckmann: Stuckmann spent over fifteen years as one of YouTube’s most respected film critics (2M subs), then jumped from reviewing horror to making it. The Kickstarter raised $1.4M. Mike Flanagan came on as EP. Neon distributed.

Dan Trachtenberg: The granddaddy of this list. His 2011 live-action Portal: No Escape fan short, made on a shoestring and posted to YouTube, got him 10 Cloverfield Lane, and that got him Prey and now Predator: Badlands. He’s proof that this pattern long predates the current wave.

Michael Shanks: timtimfed, Shanks’ Australian YouTube comedy channel of surreal genre shorts, ran for years before his debut body-horror feature Together, produced by its stars Alison Brie and Dave Franco, broke at Sundance and grossed $32M worldwide last year.

Mark “Markiplier” Fischbach: 38M-sub gaming YouTuber Fischbach first played Iron Lung, the David Szymanski indie sci-fi horror game, on his stream in May 2022. He then optioned and self-financed the film adaptation, clearing over $50M worldwide earlier this year on a $3M budget and without traditional studio backing.

An illustrious roster, but what’s most notable about this meme is that based on news from the past few weeks it is already out of date, since there are at least four more creators of viral internet media with recent news about their burgeoning directorial careers:

Sam Evenson: Evenson is a VFX artist (Dune: Part Two, The Last of Us) who runs the YouTube channel Grimoire Horror. His viral 12-minute YouTube short Mora, about a haunted image generation AI model, sold to Neon two weeks ago, with Evenson writing and directing the feature. Like Barker, his production is backed by Spooky Pictures’ Steven Schneider and Roy Lee. Notably, Lee also was one of the producers who launched the feature career of Zach Cregger (Weapons, the upcoming Resident Evil reboot) with his breakout debut Barbarian. (Like horror director-producer Jordan Peele and many others on this list, Cregger started in comedy before transitioning to horror, as a writer-performer in the sketch group The Whitest Kids U’Know.)

Ian Tuason: Tuason has the weakest YouTube connection on this list, but Erik Davis of Rotten Tomatoes and Fandango grouped him with the others in a recent tweet and he’s not wrong: “It’s interesting that A24 is not-so-quietly recruiting filmmakers like Kane Parsons, Curry Barker, the Philippou brothers, Ian Tuason—all guys who created viral content prior to their big-screen debuts.” In this case, Tuason made indie shorts through the 2010s; his 2025 horror feature Undertone started life as a radio play, was shot for $500K in his childhood home, won the Fantasia audience award, sold to A24 in a mid-seven-figure bidding war, and pulled a $9.3M domestic opening weekend. A month ago he confirmed in an interview with Phantasmag that A24 will be producing an Undertone prequel, and a third entry is being discussed. He is also lined up to direct Paranormal Activity 8 for Blumhouse.

Casper Kelly: Kelly’s the delayed-action case. His Too Many Cooks—a horrifyingly surreal 11-minute Adult Swim sitcom parody from 2014—became one of the defining viral shorts of the 2010s after escaping its late-night cable slot onto YouTube and Vimeo. Twelve years later, that viral artifact is getting him his feature directorial debut. Buddy, a Sundance Midnight standout about a tyrannical children’s TV unicorn, was acquired two weeks ago by Roadside Attractions and Saban Films for a Labor Day wide release. The pipeline doesn’t always run on the four-year arc Parsons modeled; sometimes a viral artifact sits in the cultural memory for a decade before the producers that are game to back that auteur show up. (Buddy is produced by BoulderLight Pictures—the indie horror shingle that launched Zach Cregger’s career with Barbarian—alongside Low Spark Films.)

Dylan Clark: As announced just last week, this YouTube horror short director (his Portrait of God has nearly 9M views) has been tapped for the Blair Witch reboot from Lionsgate and Blumhouse at a $10M budget. Clark also has Portrait of God in development as a feature at Universal with Sam Raimi and Jordan Peele producing, and a third feature Story Time set up at LD Entertainment. Three projects, one debut feature, and the two most prestigious horror producers alive in his corner. It’s also worth flagging that Steven Schneider–the Spooky Pictures producer behind Curry Barker’s Texas Chainsaw and Sam Evenson’s Mora–is also EP on Blair Witch.

Having one of these YouTube kids directing a Blair Witch flick seems like a full-circle moment, since that film’s low-budget found-footage aesthetic and its viral internet lore-marketing were such clear influences on projects like Backrooms.

All of the above demonstrates a few takeaways about this internet-to-theaters horror trend (a trend that just before press time on May 6th was also reported on by Matthew Frank at the Ankler, with a focus on Parson, Barker, and Clark):

• First, this pipeline isn’t a new phenomenon but a mature one, and between A24, the Blumhouse folks, and Spooky Pictures, there is now a substantial contingent of star horror producers who clearly have made the YouTube-to-feature handoff a primary deal-making lane. That trend is likely to continue and expand. And although A24 is still the studio leading in YouTube-to-silver-screen conversions, all the other studios are starting to get in the game.

• Both comedy and horror are the pathway, but horror is always the feature destination. Why? Two structural forces are doing the work. Genre: horror is the last mass-market feature category Hollywood still makes both cheap and often—Iron Lung on $3M, Obsession shot for under $1M, Shelby Oaks on $2.8M. There is no equivalent low-budget pipeline for drama or comedy. Craft adjacency: horror and comedy are both nervous-system genres, utilizing the same skills of tension build and release that can lead either to a belly laugh or a fearful scream or both. Someone who has spent a hundred videos learning how to land a sketch beat or a jump scare on a thirteen-year-old’s algorithm-addled attention has been training the exact muscle the genre rewards.

• It’s all dudes. Almost all white dudes, except for Filipino-Canadian Ian Tuason and half-Korean Markiplier. I refuse to believe there aren’t plenty of equally talented women and people of color jamming out YouTube content that demonstrates their capability to take on a small-budget horror pic. Producers and studios need to go find them.

And the final takeaway: YouTube is cracking down on AI-driven creators at its peril, risking the next generation of Kane Parsons-style innovators who use the most available technology to quickly ship their most viral ideas to a hungry audience. Yes, there are slop-meisters that need to be demonetized, but there are also budding auteurs who may never flower, or will move to flourish on another platform, if YouTube can’t calibrate its censor-bots to distinguish the two.

Noah Hawley, the Multidimensional Franchise Expander

The default mode of Peak IP is extraction. Studios hold a vault of recognizable names, and the job of each new season, sequel, or spin-off is to get more ore out of the same shaft: same story beats, same characters, same visual language, diminishing returns.

We have a decade of receipts now on what that looks like. Cinema and TV are dominated by nostalgia reboots, legacy sequels, cinematic universes that can no longer remember why they exist. And we’re about to find out what it looks like when generative AI makes the cost of extraction approach zero. Slop strip-mining of old IP, be it authorized or unauthorized, is the endpoint of the extraction model.

Which is why it’s worth naming, precisely, what Noah Hawley–the TV showrunner for FX’s Fargo, Legion, and Alien: Earth–is doing instead.

Two things recently put Hawley back in front of me. The first was his essay in The Atlantic on the consequence-free reality of the contemporary billionaire, based on his visit to Jeff Bezos’ “Campfire” retreat; it was a big part of The Internet Discourse a couple weeks ago, and also offered an interesting lens with which to view the billionaire villain in his Alien series.

More interesting to me, though, was his Canneseries interview, also at the end of April, in which Hawley repeated a label someone else hung on him recently: “franchise whisperer.”

The label is fine. But it’s not precise enough. What I see Hawley doing across Fargo, Legion, and Alien: Earth isn’t just coaxing new life out of old IP. It’s a structural method, and once you see it, you can’t unsee it.

I would label Hawley as a three-dimensional franchise expander: someone who extends other people’s properties along distinct axes, and who picks a different axis each time depending on what the source material is actually asking for.

One might ask, why focus on expanding other people’s source material at all? Hawley is a uniquely gifted writer-creator who certainly has the capacity to craft his own original stories; he’s already done so repeatedly as a novelist.

The answer is in the same Canneseries conversation, where Hawley candidly described the competitive landscape for TV. His biggest competition, he said, is YouTube: a platform that spends nothing to produce content while he’s spending $250 million per season of Alien: Earth. When the cost of content collapses to zero, recognizable brands become the lifelines that pull eyeballs back to expensive storytelling. Which is why how you build on those brands–extractive vs. additive, mining vs. growing–becomes the central craft question of the infinite-content era.

Hawley’s craft is not extracting, it’s expanding. Or, to cite an old bit of advice from comic book writers, the original shared-fictional-universe creators: when you take a toy out of the franchise toybox for your run on a comic series, you need to make sure you put it back right when you’re done–and ideally add a few new toys to the box for the next creator to play with.

Noah Hawley always creates new toys. Watch him work along three axes:

FORWARD: Fargo

The easy thing to do with the Coens’ 1996 film would have been to retell it at a more leisurely and detailed pace, or extend it by giving Minnesota detective Marge another quirky case to sleuth. Hawley did none of that. Fargo the series carries the Coens’ tones and structures forward into new contexts: new decades (1979, 2006, 1950, 2010, 2019), new casts, new crimes, new moral quandaries. Hawley essentially treats the Coens’ entire filmography as the source—Miller’s Crossing, No Country, A Serious Man, Burn After Reading—and lets that whole sensibility propagate through different American eras.

What’s striking is that Hawley is explicit about what each season is for. At Canneseries he described Season 2 as the death of the family business and the rise of corporate America; Season 3 as a deconstruction of “this is a true story” in the era of alternative facts; Season 5 as a meditation on whether the Yellowstone worldview–the idea that a man simply knows in his bones what’s right–is heroism or villainy. Underneath all of these thematic variations, he said, both Fargo the movie and Fargo the TV show have always been about the battle between decency and cynicism, and in America right now decency isn’t winning.

This is franchise expansion by translation forward to apply prior themes, tones, and tropes to new stories with new characters in different time periods. The franchise gets bigger not because more of the same thing happened, but because the sensibility proved portable, and because each iteration carries a fresh diagnostic claim about the country it’s depicting. Which, incidentally, is exactly what the Atlantic billionaire essay is doing in prose form. Hawley has a thesis about consequence and decency, and Fargo is the long-running fictional laboratory for it.

DOWN: Legion

Hawley’s approach to Legion was a very different maneuver. When faced with the opportunity to do a television show based in the expansive X-Men universe, Hawley monomaniacally drilled down into one character: David Haller, a psychically gifted, schizophrenia-diagnosed mutant from a C-list corner of the comics. The result was three seasons of unapologetically weirdo television: bizarre Bollywood dance numbers staged inside psychic battles, silent-film interludes, rap-battle telepathy, a season-long time loop, a villain living inside the protagonist’s skull. He went deep–into the character, into the psyche, into his own artistic preoccupations–and instead of just pulling more of the same from that mineshaft, Hawley excavated something uniquely his.

His Canneseries pitch for the show was “What if Breaking Bad was about Walter White becoming a supervillain? I found Professor X’s son, who’s mentally ill, basically. He has these powers but he’s not sure whether they’re real. And if he doesn’t know, then that’s the show.” He made a deeply philosophical and deeply freaky show all about the instability between what’s real and what’s in your head. You can’t do that shit with Wolverine.

Expansion through depth of specificity in exploring weird dark corners. The franchise gets bigger because one narrow slice got unimaginably deeper.

OUT: Alien: Earth

Alien: Earth—FX’s biggest streaming premiere ever, 94% on Rotten Tomatoes—is Hawley doing the opposite of Legion. Instead of drilling down on the Xenomorph, he broadens the world horizontally. The franchise has spent 45 years on one creature (the titular alien), one megacorporation (Weyland-Yutani), and one form of AI (synthetic persons). Hawley’s 2120 has five corporations (Prodigy, Weyland-Yutani, Lynch, Dynamic, Threshold), three categories of artificial person (synthetics, cyborgs, and the new hybrid synthetics with uploaded human consciousnesses), and a whole menagerie of horrific new alien species beyond the Xenomorph (blood ticks, octopus eyes, the orchid and the fly nest).

Hawley also broadened the franchise’s applicability to now by literally bringing it home to Earth, and using our current anxieties about AI, billionaires, and infectious, out-of-control biological processes against us.

This is expansion by horizontal world-thickening. The franchise gets bigger thanks to Hawley populating it with more, and more thematically rich, versions of what made us love the series in the first place. The title Alien always had a double-meaning, both a noun and an adjective. Hawley ran with the adjective and broadly applied it to new creatures, new minds, new corporate entities, new fears of the unknown.

Forward, Down, and Out

Hawley has found a way to rely on pre-existing storyworlds without exhausting them, a way to diagnose a property for what it most needs from him–and what he most needs from it–and picking a new direction. He doesn’t choose the linear-thinker path of retelling the story (the Die Hard 2 model), or extending the plot with the same characters (the Star Wars model), or telling a new adventure of the same protagonist in the same style (the Raiders model). He’s the kind of showrunner who tellingly doesn’t rewatch the originals he is adapting before he starts. He works from the emotion he remembers, then asks how to recreate it but in a completely new way.

This is why Hawley’s particular skill is so uniquely valuable in this media environment. What’s scarce in this landscape isn’t content; it’s authorial judgment about which direction to grow a property, and why. A generative model can produce infinite Fargo-flavored dialogue, infinite Legion-style freakouts, infinite Xenomorph variants. It cannot decide that this IP needs forward-translation and that one needs vertical compression and that one needs horizontal thickening. It can’t preserve and expand on the feeling of a storyworld so that the brand is still recognizable to audiences but the form it takes is novel enough to intrigue audiences. The diagnosis is the craft.

As Steven Spielberg argued at Cinemacon a few weeks ago, Hollywood needs to invest in more original IP rather than trying to squeeze every last drop out of old IP, otherwise it will creatively “run out of gas.” That’s certainly true. But if you’re going to invest in legacy IP, and want to do so in a way that is additive rather than exploitative, there’s no one better than 3D franchise expander Noah Hawley. IP extensions will necessarily continue to be a dominant form in the mediasphere as studios compete with a flood of free online content, but hopefully Hawley’s uniquely creative approach will help inspire the next generation of franchise adapters to think in more than one dimension.

Model Hypocrisy: Unconsented Data Scraping for Me But Not for Thee?

In the last issue of Converger I highlighted the raft of copyright lawsuits against AI labs currently being litigated in the US and around the world, including challenges to their use of masses of copyrighted expression scraped from the internet to train their models. The labs have consistently argued that using that data for training is defensible as a transformative “fair use” under copyright law, and the White House in its AI Action Plan made clear it agreed.

However, the White House’s Office of Science and Technology Policy (OSTP) just released on April 23rd—based on apparent pressure from the labs themselves—a saber-rattling memo that is directly and hypocritically in tension with that fair use position. Specifically, the memo condemned distillation “attacks” (i.e., automated querying of model outputs for the purpose of training new models) by Chinese AI labs against US models, after OpenAI, Anthropic, and Google DeepMind all individually complained of the same in February. The US labs variously complained about these “cyber-attacks” as “free-riding” “intellectual property theft” of “proprietary” data, and the White House followed suit:

[T]he United States government has information indicating that foreign entities, principally based in China, are engaged in deliberate, industrial-scale campaigns to distill U.S. frontier AI systems. Leveraging tens of thousands of proxy accounts to evade detection and using jailbreaking techniques to expose proprietary information, these coordinated campaigns systematically extract capabilities from American AI models, exploiting American expertise and innovation.

I am mindful that US labs are in a technical race with Chinese labs that has significant economic and national-security implications, and if the US government officially complaining about distillation helps dissuade Chinese action here (it won’t) then please, go ahead and rattle that saber. But these complaints are broadly and indeed hypocritically in tension with the positions of the AI labs and the US government in other contexts.

First and most obviously: US AI labs trained their models based on “industrial-scale” unconsented copying of other people’s copyrighted expression, and for them to argue that was fair use while claiming that training on their data is not a fair use is wholly contradictory. Indeed, there are at least four arguments why model distillation is more likely to benefit from the defense of fair use than training on indiscriminately-scraped copyrighted works, or may not even implicate copyright law at all.

One: There is a long line of cases standing for the proposition that studying outputs from a technology to reverse engineer it is a fair use, including Sega Enterprises Ltd. v. Accolade, Inc., 977 F.2d 1510 (9th Cir. 1992) (disassembling Sega Genesis game code to make compatible third-party games was fair use), Atari Games Corp. v. Nintendo of America Inc., 975 F.2d 832 (Fed. Cir. 1992) ( “reverse engineering, untainted by the purloined copy of the 10NES program and necessary to understand 10NES, is a fair use”—Atari lost on its specific facts only because it had obtained Nintendo’s source code from the Copyright Office by lying about pending litigation); and Sony Computer Entertainment, Inc. v. Connectix Corp., 203 F.3d 596 (9th Cir. 2000) (intermediate copying of Sony’s PlayStation BIOS during the development of an emulator was protected fair use, even where the resulting product directly competed with Sony’s console).

These cases together stand for the proposition that observing what a system does—including copying its outputs—to build a competing system is a fair use, particularly where the underlying functional elements are not themselves copyrightable subject matter. Notably, the underlying models themselves, which are complex functional mathematical objects created by algorithmic processes, may not be copyrightable under current law at all.

Two: At least in the opinion of the Copyright Office, generative outputs are not copyrightable for lack of a human author, meaning a fair-use defense would not even be necessary since the supposedly “proprietary” outputs are not copyright-protected. See U.S. Copyright Office, Copyright and Artificial Intelligence, Part 2: Copyrightability (Jan. 29, 2025) (Fully AI-generated outputs generated in response to a human input or prompt lack human authorship and are therefore not copyrightable).

Three: to the extent there is a copyright interest in outputs, the labs have typically assigned that interest to the users eliciting the outputs, and disclaimed their own. OpenAI’s Terms of Use provide that “you... own the Output” and “we hereby assign to you all our right, title, and interest, if any, in and to Output” (emphasis mine—the “if any” is the lab itself hedging that there may be no copyright interest there at all). Anthropic’s and Google’s consumer terms are substantially similar. The labs have done this in part for self-serving liability reasons—in the context of potential infringement claims, they want to make clear that the outputs are your creation, not theirs—but the doctrinal consequence cuts the other way: a lab that disclaims ownership of an output cannot, in the next breath, claim that output as a proprietary asset that competing researchers must not be allowed to learn from.

Four and finally: to the extent the labs argue that distillation is prohibited by their terms of service, a lack of a copyright interest in their models or their outputs would call the legality of that prohibition into question (Mark Lemley and Peter Henderson argue that contractual restrictions on the use of AI outputs may be preempted or unenforceable where there is no underlying intellectual property interest to protect). Intellectual property only provides certain limited rights, not a general ability to dictate through contract how information and expression are used. Courts are quite unlikely to consider any outputs to be trade secrets if anyone can elicit them from a model that’s been exposed to the public; if they also aren’t copyrighted, there isn’t really another relevant type of IP law to rely on.

Indeed, the weakness of any legal argument against model distillation–and its contradicting of the labs’ own arguments in other cases–is perhaps best indicated by the fact that they haven’t sued anyone over it yet. And notably, the White House too fails to articulate any reason why these “attacks” are illegal.

Beyond not making sense as a matter of IP law, the White House’s position also contradicts its AI Action Plan’s dedication to fostering the growth of open-source AI models as a source of competitive innovation that isn’t centralized in the hands of a few large AI labs. Both Dean Ball—the AI Action Plan’s primary staff drafter while at OSTP—and open-source AI researcher Nathan Lambert of the Allen Institute for AI (Ai2) have discussed at length on Twitter how distillation is a common technique, including amongst academics, for testing and improving the AI state of the art and developing open-source models including smaller models that can run locally. That open-source ecosystem benefits all AI advancement, not just in China but here and around the world.

Nor is the use of distillation limited to the open ecosystem: for example, Elon Musk admitted on the stand last Thursday in his lawsuit against OpenAI that his company xAI has “partly” used distilled outputs from OpenAI models to help train Grok, calling it standard industry practice. The other labs have likely done the same to each other at times. As expressed by Clem Delangue, the CEO of open-source AI platform Hugging Face, all of this vibes a bit like the labs “pulling the ladder” up behind them:

All labs trained their models by distilling (at the very least distilling the web) which allowed them to become the fastest growing businesses in the history of humanity and now that they have armies of lawyers and lobbyists, they are trying to prevent others from doing the same thing.

For all these reasons, the complaints from the major labs and the US government about distillation by foreign competitors ring hollow. There is also the question, raised by Dean Ball, of whether the US government even “actually adds value in practice on the issue of combatting distillation, and whether that addition of value is larger than the risks associated with the USG paying close attention to the minutiae of frontier AI development.” This question is all the more salient now that the White House is reportedly considering prior restraints on the release of frontier models by US labs, a particularly heavy-handed and constitutionally dubious intervention in the name of security.

Perhaps, if the labs want to combat distillation more aggressively, they should simply invest more money in their own technical countermeasures and leave the rest of us out of it. Or they can sue someone, if they don’t think it will completely undermine their own fair use defenses in the scraping cases against them. But I wouldn’t hold my breath.

A Hollywood AI Pipeline Built on Chinese Models?

Following up on my piece in the first issue about the post-Sora video gen landscape, fresh news has validated my take: Netflix is investing heavily in both open and proprietary AI video gen tools, and traditional studios that don’t build their own tech stack will soon be at a distinct disadvantage.

Netflix—along with its subsidiary Eyeline Labs—followed up last month’s open-source release of the VOID model by dropping Vista4D, a “video reshooting framework” on GitHub. The tool takes previously shot video input and lets you change camera angle, add or modify camera movement, or dynamically expand the scene.

Like both VOID and the InterPositive tools that Netflix acquired from Ben Affleck, these new tools are focused on modifying already-shot footage rather than generating video from scratch with text prompts. Unlike those other tools, though, this one is built on top of Wan2.1-T2V-14B, a 14-billion-parameter text-to-video diffusion model open-sourced by Chinese tech giant Alibaba.

Netflix building on top of a Chinese video model is emblematic of a post-Sora technology trend identified last week by The Wall Street Journal: China is currently whooping American labs on the video generation front, both in adoption of open models like Wan and proprietary models like Kuaishou’s Kling—even as some Western labs (per TechCrunch) retreat from consumer video generation entirely.

As the WSJ reports, Chinese labs took seven of the top 10 spots for video-generation models last month on rating platform Artificial Analysis, including the widely popular (and in Hollywood, reviled) Seedance 2.0 from Bytedance and the new benchmark-smashing HappyHorse model from Alibaba.

And in the Ankler, Erik Barmack sketches a three-vertical landscape: social generation, led by xAI’s Grok; professional short-form video, led by Kling; and Runway for Hollywood pre- and post-production. Then again, Kling is popular in Hollywood too: as the WSJ points out, it’s Kuaishou’s model that was used by House of David‘s producers for their virtual backlot, and presumably that’s what they’re using for their upcoming Moses series (discussed in our last issue).

And Asia’s not just leading on video models. While Hollywood debates whether AI belongs on a film set at all, Asian producers are racing ahead to integrate it into the production pipeline itself–slashing costs and compressing timelines on both feature films and microdramas.

In China, The Economist reports that AI-animation tools have cut microdrama production costs by up to 90%, with live-action microdrama production dropping 80% in some regions; The New York Times similarly reports on how AI is both fueling and disrupting the Chinese microdrama space.

In India, The Hollywood Reporter detailed last week what it called “the world’s most consequential live experiment in AI filmmaking”: roughly 80% of Indian films now use AI extensively in pre-visualization, AI-driven dubbing is rolling out at platform scale across a dozen languages, and Mumbai studios are producing AI-native features in six to twelve months versus the two-to-three years for traditional animation.

These two trends are converging faster than anyone expected: the center of gravity in video generation is moving to Chinese models, and the center of gravity in AI-integrated production is moving to Asia more broadly. Netflix is the one American studio racing ahead. The question is which other studios—or American AI labs—are even in the race.

How Not To Integrate AI Into Newsrooms: McClatchy’s AI-Driven Byline Blues and OpenAI’s Slop News Site

Moving from the artist’s studio to the newsroom: last issue we talked about the controversy over when and how to integrate AI into reporting, with some journalists choosing to leverage AI tools and others resisting. Since then we’ve seen a couple new lessons in how not to use AI in newsrooms.

First lesson is from media company McClatchy, operator of thirty newspapers across the country, which as first reported in multiple stories by The Wrap recently introduced a new AI-driven “Content Scaling Agent” into all its newsrooms. “More stories, more inventory” was management’s hope and demand as they launched the tool to reporters with a groan-worthy Star Wars-style intro crawl.

It would have been controversial enough just for McClatchy to try to force reporters to use AI to rewrite and repackage their original stories for “new audiences, angles and entry points.” But as also reported in the The New York Times last week, McClatchy truly stirred up the hornet’s nest when it said that it would use reporters’ bylines on AI-written stories adapted from their work even against their objections, in order to help get better Google rankings. “If they don’t have the ability in their contract to remove their byline, we’re going to use their name,” said management, leading to complaints from several of the newsrooms’ unions and a joint letter campaign by writers to withhold their bylines.

As Ariane Lange, an investigative reporter at the Sacramento Bee and the vice chair of its union, told the Columbia Journalism Review,

I’ve covered traffic deaths in the city of Sacramento since 2024, and I have talked to many families of people who have been killed in crashes, and that’s a very vulnerable moment. I’m assuring them they can trust me, but I also have to explain that my employer might feed their story to a chatbot and spit it back out as five key takeaways. That’s revolting to me.

In an equally revolting development first reported by Model Republic, a PR firm working for the AI industry was revealed in late April to have been running a completely fake AI-driven news site with stories attacking AI regulation and the industry’s critics. The discovery came when one of those critics received a fishy inquiry from a purported journalist from the site, The Wire by Acutus, that when run through the AI detector Pangram was ID’d as 100% AI generated.

On further investigation it appeared The Wire didn’t have any human journalists at all, and that it was linked to PR firm Novus working for the anti-AI-regulation super PAC Leading the Future that’s funded by OpenAI’s president Greg Brockman and venture firm a16z. When news of the bot-driven slopaganda site leaked, the PAC essentially confirmed it was created by their PR firm but without their knowledge, and said they were cutting those ties. Paired with recent news of the same PAC funding anti-AI-regulation astroturf campaigns amongst TikTok creators, this story certainly paints an unsavory picture of that PAC, their backers, and their tactics.

Thankfully, AI efforts like McClatchy’s that disempower rather than support journalists are receiving sustained pushback from newsroom unions in their negotiations, from the New York Times to ProPublica to CBS News. No news yet, however, on whether the Wire’s robot reporters are also organizing to improve their own working conditions.

Hannah Einbinder Swirlie Watch: Who’s Getting Flushed for Using AI This Week?

Last issue we highlighted how Hacks star comedian Hannah Einbinder went off on AI creators, calling them losers and saying she wanted to stick their heads in a toilet and flush (what any high-school bully knows as a “swirlie”). In the past few weeks, several new media figures have risked Hannah’s ire, and more will certainly volunteer for swirlies in the coming months, so I figure that Swirlie Watch will become a semi-regular feature here.

Who should be on guard against Hannah’s swirlie vengeance this week?

• Director Alex Proyas (of The Crow and I, Robot) announced that he’d be working with AI studio Ex Machina to generate his next feature, a digital-afterlife sci-fi satire called Heaven.

• Writer-Director Roger Avary (co-writer and producer of Pulp Fiction), also in partnership with Ex Machina, announced he’ll be adapting Milton’s Paradise Lost using generative AI.

• Director Shawn Levy (Deadpool & Wolverine, the upcoming Star Wars: Starfighter) says he hasn’t “meaningfully” used gen AI yet in his own storytelling–so maybe he just gets toilet-dunked rather than fully swirled?–“but I have no doubt that in the course of my career we will see its integration… I think it’s going to be essential.” Nope, that’s a full swirlie right there.

• Actor-Producer Reese Witherspoon doubled-down on her comments urging women to learn AI, while making clear “I don’t believe computers should replace humanity” (phew, you had us worried there!).

• Director Steven Soderbergh tripled-down on his comments that we reported on last issue with a much more fulsome explanation of the AI use in his upcoming John Lennon and Yoko Ono documentary, in partnership with Meta, defending that choice while also being fully transparent about it.

• Producer Ryan Kavanaugh had the temerity to defend the virtually-produced Doug Liman thriller, Bitcoin: Killing Satoshi, raising the same possibility I articulated last issue: that virtual production might actually be a way to bring more movie productions and more industry jobs back to LA.

• DJ and music producer Diplo said in a podcast interview and then reiterated on Twitter that “there’s no fighting AI” and “if you are a creative you need to adapt or just like give up and become an uber driver until everyone has a waymo.” That definitely warrants multiple flushes.

• French electronic music pioneer Jean Michel-Jarre complained of the conservatism of creative industries “freaking out” about AI, predicting that artists would use AI “to create the cinema of tomorrow, the hip-hop of tomorrow, the techno of tomorrow, the rock’n’roll of tomorrow.” He says “[w]e should never be afraid of technology.” But he should be afraid of Hannah Einbinder.

• OpenAI CEO Sam Altman pushed back on Hollywood concerns about AI replacing humans with some unconvincing pro-human pablum: “I think people really care about other people…. I think people really care about the human beings behind the stories and the art and the creative work that matters so much, so my instinct is it’s going to go the other way and people will care more about humans and more about human creators in the future, not less.” Problem solved!

• NYU Film School’s administration and faculty earned a collective swirlie by partnering with Runway to put AI credits and training in the hands of its students for free (well, plus NYU’s exorbitant tuition). Looks like USC’s film school and the Sundance Institute may also have earned a dunking for getting in bed with Adobe and Google.

Get to work on those swirlies, Hannah! You have a long target list this week. Everyone else, be on guard if entering a public bathroom in Hollywood or NYC.

FRAGMENTS

Creator, Trademark Thyself

Taylor Swift is following Matthew McConaughey’s lead and filing to trademark her voice and image in an attempt to help combat misuse of both by AI. The actor’s advice: “So I say: Own yourself. Voice, likeness, et cetera. Trademark it. Whatever you gotta do, so when [AI] comes, no one can steal you.” Well alright alright alright.

ChatGPT Images 2.0 Can Now Fake Your Doctor’s Note

The new image model is, as highlighted by TechCrunch, surprisingly good at rendering coherent and readable text outputs, leading to all kinds of novel use cases popping up on Twitter.

Affleck Tops List of Most Powerful AI Players in Hollywood

The Hollywood Reporter published its list of the 25 most powerful people shaping the future of AI in Hollywood, and at the top was Ben Affleck whose AI startup sale to Netflix has helped prompt a vibe shift in the creative world around using AI tools in filmmaking. Or, as one commentator put it to Vanity Fair: having a prominent creator like Ben Affleck pushing AI “helps get filmmakers to feel more comfortable [using it]—and that’s worth the $600 million” that Netflix paid him. For my part I’m very supportive of the creative use of AI but “he got paid hundreds of millions to use his celebrity to normalize AI” seems a bit gross, and as reported in the last issue, Affleck and Netflix also haven’t been very forthcoming about the technology behind the startup’s product nor about the copyrighted works behind that technology. But being the most powerful isn’t always pretty!

New Creative AI Integrations, Integrating AI Creatively

The last couple weeks saw some big releases in the realm of integrating creative tools into chatbots and chatbots into creative tools.

On April 23rd, a16z and Union Square Ventures-backed startup Glif came out of beta with the release of Glif v2, pitched as “it’s like Claude Code for AI videos”: a “creative super agent” chatbot interface that integrates with virtually every available video and audio gen model for a unified creative dashboard.

Five days later the makers of actual Claude announced Anthropic’s own integrated creative offering with a raft of new connectors between Claude and a wide range of creative applications: the entire Adobe Cloud suite of tools, Blender, Canva’s Affinity, Ableton, Splice, SketchUp, and Resolume. This is a clear warning to startups like Glif: when building wrapper interfaces around other people’s models and services, you risk the model-makers themselves offering the same features directly.

And, in a story I missed before putting out the previous issue, Google and Avid announced earlier in April the integration of Gemini AI features into the Avid editing suite, a godsend for editors trying to locate just the right shot in a heaping digital pile of other takes. Harried editors can now just describe in chat the particular visual movements, dialogue or emotional cues they’re looking for and Gemini will help surface the clip they need.

Regardless of whether you’re using AI to generate art or just tweak or edit it, and whether you’re using a startup’s toolkit or subscribing to a foundation lab’s frontier model, creative AI is getting exponentially easier to use by the day, and the trend will likely continue to be toward one creative interface to rule them all.

Because Parasocial Relationships with AI Aren’t Weird Enough

The dominant player in vertical comics, Webtoon, has inked a deal with AI avatar tech company Genies to let users chat with their favorite comic characters. Still unclear what the content guardrails or age restrictions around that tech might be but worth noting that Disney has a deal with Webtoon to build Marvel’s new digital comic platform, so we may end up seeing this tech applied to many more popular characters than just those in your favorite manga.

Because Parasocial Relationships with AI Aren’t Weird Enough, Part Two

The New Yorker published a fascinating and disturbing article about TikTok and Instagram influencers using AI to pose as different races and genders; as the author put it on Twitter, “it gets weird real fast.” See also this related Wired story onfake MAGA girl influencers, and this creepy demo video I found on Twitter of a college dude using AI to pose as a bikini blonde. As the article retweeted by that poster noted, you now never know whether the influencer you’re watching is made out of four files on a laptop somewhere.

The Other Ryan Gosling Astronaut Movie

I really enjoyed Project Hail Mary—go see it on a big screen before it’s gone!—which reminded me of another (tragically underappreciated) movie starring Ryan Gosling as an astronaut: Damien Chazelle’s Neil Armstrong biopic First Man. That earlier movie inspired me several years ago to write an Atlantic article about the feedback loop between movies and science, using the example of how the orbital mechanics of the Apollo missions were presaged decades prior in Fritz Lang’s 1929 silent film Woman in the Moon, informed by Hermann Oberth, the father of German rocketry and the first movie science consultant. (You can read several more of my articles about the sci-fi feedback loop over at Slate).

Warner Bros. Shareholders Approve Paramount-Skydance Merger Bid

Former FTC commissioner Alvaro Bedoya briefly highlights ways it might still be stopped; Wade Major of Hollywood Heretic dives deep with nearly 15,000 words on why he thinks the Netflix takeover was always doomed and the Paramount merger will be better for Hollywood. I’d still prefer no merger at all but it’s a fascinating piece.

Window Treatment: (Almost) All Studios To Let Movies Stay in Theaters Longer

Ever since the pandemic, studios have been aggressively shortening theatrical windows for their movies in a short-sighted attempt to shore up their streaming operations. But it looks like the windowing wars may have reached a cease fire as the studios are finally listening to exhibitors, and seeing more clearly how this self-cannibalization has been leaving theatrical money on the table. Based on a slew of recent announcements, longer windows appear to be the “new gospel” in Hollywood: Last Friday Netflix announced Greta Gerwig’s Narnia: The Magician’s Nephew will get a true wide release in February 2027 with a 49-day exclusive run—Netflix’s first real theatrical window after Ted Sarandos pledged 45 days under oath to a Senate antitrust subcommittee in February. It caps a month that saw every major reaffirm a 45-day floor at CinemaCon: Sony’s Tom Rothman told exhibitors to enforce it, Paramount’s David Ellison made a surprise appearance to commit to it effective immediately, and Disney reiterated its 57-day average. Apple’s the only studio that hasn’t yet committed to a longer window, but I’m guessing its eventual F1 sequel will be in theaters for a long, long time.

Proving (or Pretending) You Didn’t Use AI for Your Writing

Following up on her New York Times editorial on the AI-driven erosion of trust between authors and readers, novelist Andrea Bartz wrote an in-depth Substack article on the challenges of proving that you didn’t use AI in your writing, ultimately concluding that the best way to fend off accusations for now is to thoroughly document your writing process. (Notably, Bartz is the lead class representative in Bartz v. Anthropic, which along with Kadrey v. Meta is the flagship litigation against the tech giants for training their AI models on her and other authors’ novels without permission. Another lawsuit against Meta–and Mark Zuckerberg personally–by novelist Scott Turow and five publishers just dropped this week.)

Meanwhile, there’s a fun new AI tool for those who want to humanify their emails, from Dorm Room Fund tech investor and tinkerer Ben Horwitz: Sinceerly.com. Horwitz calls it the anti-Grammarly, and it uses AI to mess up your email drafts to make them seem more like something a person would write. There are three settings: the minimal-changes Subtle setting, the intermediate Human setting, and–with maximum typos and abruptness and minimal grammar compliance–the CEO setting 😂

The Actors Guild Deal Has…Some Sort of AI Protections?

Last issue I bemoaned the lack of new protections against AI replacement for members of the Writers Guild of America in their fresh four-year deal with the studios, and pointed to the upcoming SAG-AFTRA negotiations as another opportunity for Hollywood’s creative class to secure AI concessions. Well, now that actors’ union has also signed a four-year deal with the studios and it has…some sort of AI “guardrail” provisions? Or “safeguards” or “protections”? But no one reporting on the deal seems to have any details on what these protections are. So, um, hopefully they’re good?

AI Film Wins at a Traditional Film Festival for First Time; Academy Nixes Awards for AI Writing and Performances

Depending on your perspective this is either a travesty or an auspicious first, but: in mid-April, Memory of Princess Mumbi–a feature film from Swiss-Kenyan director Damien Hauser that substantially used AI to generate its futuristic sci-fi background–won the top prize at the Istanbul Film Festival. As Hauser discussed before winning the award, his portrait of a retro-futuristic Africa in the year 2093 would not have been possible without AI, even as he set out to “make a movie that AI [alone] could never make.”

On the other side of the world, the Academy Awards organization released on Friday new rules making clear that AI-generated performers are not eligible for acting awards (so, e.g., no award for AI-resurrected Val Kilmer), and only human-authored scripts are eligible for screenwriting awards. The rules notably did not address other uses of AI in regard to other awards–so, e.g., something like Memory of Princess Mumbi could still be considered for Best Foreign Film.

44% Slop and Rising: AI-Generated Music on Deezer

Late last month music platform Deezer (which I admittedly had never heard of before this story) disclosed that 44% of daily uploads–roughly 75,000 tracks a day, over 2 million a month–are AI-generated. But consistent with last issue’s piece on how older music is resonating with streaming listeners much more than new music is, whether AI-generated or not, the AI music on Deezer represents only 1–3% of streams. And 85% of those streams are flagged as fraudulent and demonetized. The company is now licensing its AI detector to other companies.

And that’s what’s converging this week! See you next time, and don’t forget to share if you liked what you read.

CONVERGER presents news and views from an AI, internet and media policy expert who is pro-innovation but anti-hype, allergic to both AI panic and AI boosterism, and passionate about supporting rather than supplanting human creativity with new technology.

I’m Kevin Bankston, your host. Since this is the first issue of CONVERGER, it’s a massively super-sized edition covering the past month.

Some issues may be heavier on media commentary, others on AI policy, others on personal passions like sci-fi’s influence on technology (both for good and bad) or the evolving medium and business of comic books in the digital age. You never know what threads might come together in convergence-space!

Going forward, you can watch me develop newsletter content in real-time on LinkedIn and the social network formerly known as Twitter, and less often on Bluesky and Instagram.

You can also look for my deeper policy-oriented takes on AI governance generally at Elicitation, the new Substack from my AI policy day-job colleague Miranda Bogen of the Center for Democracy & Technology’s AI Governance Lab.

Now, let’s converge!

TABLE OF CONTENTS

FEATURES

1. Happy 100th AI Lawsuit to Those Who Celebrate! (~310 words, 1 minute read)

2. Forecasting Four Fraught Futures for the Web in the AI Age (~540 words, 2 minute read)

3. Steven Soderbergh Volunteers To Get a Swirlie from Hannah Einbinder (~590 words, 2.5 minute read)

4. Hollywood’s So Angry at AI It Can’t Spell Straight (~510 words, 2 minute read)

5. Pay No Attention to the Foundation Model Behind Ben Affleck’s Curtain (~1075 words, 4 minute read)

6. Director Robert Rodriguez on AI as Creative Multiplier (~445 words, 1.5 minute read)

7. Virtual Studios: What’s the Difference Between Sin City and Generated Cities? (~670 words, 2.5 minute read)

8. So Long Sora, Welcome Back Seedance 2.0, Hello to Netflix’s VOID (~540 words, 2 minute read)

9. Writers vs. AI vs. Writers (~590 words, 2.5 minute read)

10. A Contract That Helps Protect Comic Artists Against AI Training on Their Work (~360 words 1.5 minute read)

FRAGMENTS

1. WGA Deal on AI: Is That All There Is?

2. News of the Supreme Court’s Ruling on AI and Copyright Has Been Greatly Exaggerated

3. Macro-Growth in the Micro-Drama Content Pipeline

4. Meanwhile, In the YouTube-to-Theaters Pipeline: Backrooms is Coming

5. Old Music Beats New Music Beats AI Music

6. New Script-Reviewing AI Really Wants Brett Ratner to Direct Your Movie

7. Is Fan-Created Content Supplanting Canonical Content?

8. The Future’s So Bright I Have To Enter This Contest

9. Big Brother, Generating Slop

10. Webtoon Translations, Digital Comics, Tiny Onions

FEATURES

Happy 100th AI Lawsuit to Those Who Celebrate!

At the border between old media and new technologies, there are lawsuits—a lot of lawsuits. And on April 3rd we hit a key milestone: the filing of the 100th copyright-related lawsuit against an AI company in the US.

The honor of bringing the 100th case goes to Ted Entertainment, a YouTube creator that simultaneously filed three cases against OpenAI, Apple, and Amazon, alleging they illegally bypassed YouTube’s technical protections to scrape videos for AI training.

Meanwhile, what was already the largest copyright settlement in history—a minimum of $1.5 billion dollars in the case of Bartz v. Anthropic, brought by a class of authors representing every writer of every one of the nearly half a million works in the “shadow libraries” of pirated books that Anthropic trained its models on—has also hit another milestone. The plaintiffs have reported that the authors of 91.3% of the eligible works have registered their claim for part of the settlement.

As any lawyer reading this knows, that’s an insane claims rate; the typical consumer class action lawsuit has a rate closer to 10%. But it looks like the potential for approximately $3000 to each author per work was highly motivating to the class members. And as lawsuits against AI labs on behalf of authors proliferate, there may be more settlements coming down the pike.

This is all according to ChatGPT is Eating The World, the most comprehensive newsletter tracking copyright law developments around AI. It’s run by law professor Edward Lee, who commemorated the 100th lawsuit by debuting a new dashboard for tracking all of them, both in the US and globally. Handy for AI and copyright nerds!

Forecasting Four Fraught Futures for the Web in the AI Age

Speaking of AI, scraping, and the law: late last month at Georgetown Law School I had the privilege of hosting a day-long event of public and private panels, talks, and roundtable conversations about “Internet Scraping and the Future of the Open Web in the AI Age,” in my dual capacities as Senior Advisor on AI Governance at the Center for Democracy & Technology and adjunct professor of AI and copyright law.

The day was focused on the question of how to preserve an open and sustainable internet ecosystem when human traffic is quickly being supplanted by AI-driven bots, and how the results of those hundred lawsuits mentioned above might impact the answer.

This tension was highlighted just this last week by reporting about how the bots of the Internet Archive, a critically important nonprofit library of internet content, are increasingly being blocked by news websites afraid of their content being scraped by AI companies. That in turn led over a hundred journalists to write an open letter defending the importance of the Archive’s record of internet history to their and other researchers’ work, as well as to the public.

The issue of scraping and AI raises hard questions with a lot of important perspectives on different sides, so our event certainly didn’t resolve the problem! But we did bring together all the different communities with a vested interest in the issue for a generative [pun intended] dialogue, including commercial and non-commercial AI labs, web publishers and service providers, content delivery networks, librarians and archivists, scraping companies, and academic and public interest experts.

My favorite part of the day was one of the private expert sessions where we used a common foresight tool—the 2x2 scenarios matrix—as the basis for a breakout group exercise considering four very different possible futures for the internet based on the different ways companies, the courts, and lawmakers might approach the issue:

The Wild West: Unconsented bot scraping is both legal and technically easy and the internet is completely overrun by automated traffic.
The Hollow Victory: Web publishers beat the bots in court but lose the technical fight, so sites continue to be pummeled by abusive scraping from bad actors that are outside the reach of the law.
The Gated Web: Both legal protections and technical protections against bots are strong, leading to an internet of pay-per-scrape content fortresses.
Code is Law: Scraping is legally protected but the technical walls are so high that it’s still impossible, so only big companies can afford to pay to scrape anything worthwhile while startups, researchers and journalists can’t.

All of these are extreme futures—that’s the nature of the exercise—but in articulating them, including their pros and cons and likelihood, we were able to weigh the complexities of the issue and the tough tradeoffs involved in a productive way. I posted the whole exercise worksheet on LinkedIn for others to use as a model because it’s a dead simple way to surface a wide range of predictions and perspectives around whatever issue it’s applied to. Check it out, and happy futuring!

Steven Soderbergh Volunteers To Get a Swirlie from Hannah Einbinder

Highlighting how polarizing generative AI has become in the film community, Emmy-winning Hacks star Hannah Einbinder roasted AI video creators during a press conference for that brilliant show’s final season, a roasting that nearly every Hollywood trade press outlet gleefully gave its own story. Slashfilm originally reported the full quote:

The people who make this stuff are losers. They’re not artists. They’re not creative. And they’ve wanted their whole lives to be special. And they’re not special…. They’re trying to rob real creative people of our gifts. And you can’t. And even if you try, you will never be cool. You guys suck. No one likes you. Anyone who’s near you is because they crave power and access over any ethical standard. You are a loser. You will never be cool. And you probably had a rolly backpack in high school. I wanna put your head in the toilet and flush.

Almost immediately proving her generalization wrong, legendary Academy Award-winning director and definitely-not-a-loser Steven Soderbergh noted in an interview with Filmmaker that he’ll be using “a lot of AI” in his forthcoming films.

It was the interviewer who first raised the subject, noting the “horror of AI” as perhaps “too depressing to talk about,” but Soderbergh immediately broke the narrative: “It’s worth talking about what that technology might be good at,” he replied.

Specifically, Soderbergh noted that for ten of the ninety minutes in his upcoming documentary on John Lennon and Yoko Ono, “AI has been helpful in creating thematically surreal images that occupy a dream space rather than a literal space…. But like every other piece of technology, it desperately requires very close human supervision.”

He came back to the subject when asked how he’d handle the expense of a period film about the Spanish-American war that he’s currently developing. Interviewer: “With ships and everything? For which you would use…” Soderbergh: “A lot of AI.”

After the inevitable online backlash to these comments, Soderbergh doubled down in an interview with Variety, where he said that the AI blowback “is mystifying to me.” He continued:

I felt obligated to engage with it, to figure out what it is and what it can do. It turned out to be a very good tool for certain passages of the Lennon documentary where I needed surrealistic imagery that was impossible to shoot. It allowed me to solve a creative problem about how to visualize what John and Yoko are speaking about philosophically. Ten years ago, I would have needed to engage a visual effects house at an unbelievable cost to come up with this stuff. No longer. My job is to deliver a good movie, period. And this tool showed up at a moment when I needed it…. There are some people that I have absolute love and respect for that refuse to engage with it. That’s their privilege. But I’m not built that way. You show me a new tool. I want to get my hands on it and see what’s going on.

The use case Soderbergh describes here is illustrative: as he notes, without AI he’d need an expensive effects house, which he certainly wouldn’t have paid to engage for a little documentary. So in this case, AI expanded creative possibilities without removing opportunities for craftspeople. But that certainly won’t be true in all cases, such that claiming to be “mystified” by the uproar seems a bit obtuse and, well, privileged. So a bit of advice, Steven: steer clear of any toilets while Hannah Einbinder is around!

(Update: just as we were finalizing this edition, Reese Witherspoon and Sandra Bullock also volunteered for Einbinder swirlies.)

Hollywood’s So Angry at AI It Can’t Spell Straight

Video generation startup Runway hosted its first Runway AI Summit in NYC on March 31st, highlighting advancements in the technology and how it’s being used creatively, and let’s just say it was received…skeptically by the Hollywood and tech press.

Wired‘s mocking headline was representative: “‘Thank You for Generating With Us!’ Hollywood’s AI Acolytes Stay on the Hype Train.” Meanwhile, The Hollywood Reporter‘s story focused almost solely on the cautionary note sounded by one star producer during the event: “Kathleen Kennedy Just Told an AI Conference She’s Not So Sure About AI,” announced the headline.

Kennedy, who is wrapping up her tenure as the head of Star Wars production company LucasFilm, rather sensibly highlighted the importance of preserving human taste and the serendipitous unpredictability of the creative process in the face of AI. She also reasonably pressed for more transparency around model development, the lack of which is a particular challenge for copyright holders seeking to prevent their content from being trained on without consent. Then she went on a bit of a tangent criticizing the quality of 3D-printed props compared to those made by craftspeople.

THR‘s story contained an embarrassing mistake that hopefully isn’t emblematic of their team’s actual level of tech knowledge. The article referred to ByteDance’s Seedance 2.0 model—the same model that has caused no end of controversy and flurry of cease-and-desist letters from the content industry since its preview release in February—as “ByteDance’s Seesaw.” That mistake wasn’t corrected for several days (despite this author’s repeated nagging on X). And the story still weirdly calls Seedance a “social application,” which, just, no.

I’m surprised that I haven’t yet seen sarcastic press coverage of SoulScape, a new “Global AI Cinema Lab and Summit” that took place in San Francisco a weekend ago, but don’t worry, there are plenty of upcoming AI+film events for Wired and THR to make fun of. Next up: Runway will be hosting its fourth annual AI film festival in both NYC and LA in early June.

Taking the Einbinder comments and the chilly reception to the Runway event together, they seem representative of the problem with the Hollywood discourse on AI as diagnosed by The Ankler‘s chief columnist Richard Rushfield:

The conversation, such as it is, shoves everything in one basket and reacts to it all with a primal scream, lumping together theft and innovation, job loss and useful tools, corporate abuse and creative experimentation…. The working premise in a lot of Hollywood is that AI is evil and must go away. Anything less than total resistance is surrender. I understand the impulse.... But that isn’t a strategy. [italics in original; funny link added.]

In an exercise evoking the 2x2 matrix, Rushfield wisely urged Hollywood to carefully delineate between four different categories of AI impacts—good and unstoppable, good and stoppable, bad and unstoppable, bad and stoppable—to better focus on stopping the bad things it can rather than wasting effort on the bad things it can’t, taking advantage of the good things that are coming, and avoiding blocking the stoppable benefits. Let’s see if anyone takes his advice.

Pay No Attention to the Foundation Model Behind Ben Affleck’s Curtain

One recent development at the intersection of AI and the entertainment industry somehow escaped the primal scream of the anti-AI contingent. That was Netflix’s high-profile acquisition of Ben Affleck’s stealth AI startup, InterPositive, in a deal that ultimately could be worth up to $600 million for the actor. Despite the highly polarized debate over generative AI in Hollywood, Affleck and Netflix effectively sidestepped controversy by describing their AI tools as filmmaker-centric and implying that they were trained using only small sets of proprietary filmed data. But it looks like they got off easy, by not being fully up-front about how their technology works.

Rather than a prompt-to-video-slop engine, InterPositive’s tools are solely focused on improving real footage that’s already been shot, consistent with a human director’s vision. “For artists to apply these [AI] tools towards telling the stories we dedicate our lives to,” Affleck said in the press release, “they need to be purpose-built to represent and protect all the qualities that make a great story…. [We] need to preserve what makes storytelling human, which is judgment…. I knew I had a responsibility to my peers and our industry, to protect the power of human creativity and the people behind it. In creating InterPositive, I sought to do just that.”

This is all consistent with Affleck’s prior statements (before anyone knew he was secretly working on an AI startup) where he highlighted AI’s limits compared to human creativity but also cautiously described its potential creative uses for filmmakers: “What AI is going to do is going to dis-intermediate the more laborious, less creative, and more costly aspects of filmmaking, that will allow costs to be brought down, that will lower the barrier to entry, that will allow more voices to be heard, that will make it easier for the people want to make Good Will Huntings, to go out and make it.”

In describing InterPositive’s AI models, Affleck and Netflix highlighted their artisanal nature (all emphases added): “I began filming a proprietary dataset on a controlled soundstage with all the familiarities of a full production….The results of this foundational work were deliberately smaller datasets and models focused on filmmaking techniques — rather than [generating] performances — creating tools that artists can use, control and benefit from.”

As Affleck further explained to Variety, “[t]he InterPositive system builds an AI model based on an existing production’s dailies, then lets a filmmaker introduce that model into the postproduction process to provide the ability to do things like mix and color, relight shots, and add visual effects.”

These statements imply (but never state) that InterPositive’s models rely only on small amounts of proprietary data. That narrative never made much sense technically, since generative AI models require enormous amounts of data. For example, Lionsgate’s entire catalogue wasn’t enough to build a useful custom video model in that studio’s partnership with Runway. But that didn’t stop other outlets from uncritically running with and expanding on these descriptions, describing InterPositive’s technology as being refreshingly free from unconsented use of copyrighted works in its training, in contrast to bigger, general-purpose video generation models:

• “The technology, however, doesn’t…use footage without permission. Additionally, the AI model is getting trained on material you already own and have access to.” –Inc.

• “InterPositive trains a custom AI model on a production’s own dailies, using that footage as the foundational dataset rather than pulling from public internet sources.” –CineD

• “Models are trained exclusively on first-party footage rather than third-party datasets, [avoiding] intellectual property and consent risks….” –Del Morgan & Co.

• “Netflix’s acquisition of InterPositive signals a deliberate pivot toward proprietary AI tools designed specifically for filmmaking rather than relying on general-purpose generative AI models.” –MLQ.ai

• “Affleck said InterPositive did not provide video generation tools such as Google’s Veo3 or OpenAI’s Sora – it was “not about text prompting or generating something from nothing” – but instead helped in the post-production process.” –The Guardian

However, the actual patent for InterPositive’s technology, published by Deadline a couple weeks ago, tells a different story. Deadline‘s news hook for the story was highlighting the millions of dollars of production cost savings that the patent application promised for filmmakers, including 50% savings on visual effects. They contrasted these cost-cutting promises with other Affleck statements focused on making filmmaking “easier” and “faster” instead of focusing on cost savings, and a Netflix exec’s statement that “it’s not really about cheaper, it’s really about better.” Obviously it’s about both, so not much of a gotcha there. But there was another story buried in the patent that Deadline missed:

Contrary to what Affleck and Netflix have implied, InterPositive’s technology must be built on top of general-purpose generative AI models that typically have been trained on masses of copyrighted material.

In particular, the patent reveals that InterPositive’s proprietary tools and data are meant to run on top of another large video gen model being used as the foundation of the system, essentially “fine-tuning” the larger base model by transferring learning from the smaller InterPositive model trained on filmmaking-specific knowledge. As I highlighted on Twitter when I discovered it, the patent specifically points to OpenAI’s Sora and Google’s video model as examples of appropriate base models. From the patent:

[InterPositive’s model is used] to train the other model, enabling it to recognize and replicate filmmaking techniques when provided with appropriate prompts…. [That] video model may be an existing large language model, such as OpenAI SORA or a Google AI model, which has been primarily designed for processing and generating video content. Prior to the transfer learning process, these models lack the capability to accurately interpret and implement cinematographic details in their outputs…. The video LLM serves as the base model that is enhanced through transfer learning to acquire the advanced filmmaking capabilities developed in [InterPositive’s] model.

I say that InterPositive’s tools are “meant to run” on top of bigger models rather than they “do run” because at this point it’s still not clear that they even exist in a workable form right now. The Wrap reports that the model is still in development, and as one Netflix executive put it, “[i]t’s not like it’s a complete and ready to go tool.” But wherever it is in the R&D process, what InterPositive is developing is a method for fine-tuning a larger foundation model with specialized data for specific use in film postproduction, rather than building its own independent model trained only on proprietary data.

To be clear: I’m not judging InterPositive for choosing to build on top of state-of-the-art foundation models from major US AI labs in order to develop creator-centric, film-focused tools. And I’m a fan of Affleck, a wildly talented, Academy Award-winning actor-writer-director-producer, as much as any other Gen Xer film nerd who religiously watched every episode of Project Greenlight and always cries at the end of Armageddon can be.

What I am judging is his and Netflix’s obscuring that fact rather than standing by it and explaining their choices. Having true creators champion reasonable, responsible, limited uses of this technology in the creative process means something in this conversation; subtle attempts to shy away from doing that in order to avoid criticism mean something, too. Perhaps Affleck should take a cue from Soderbergh and fellow AI-forward director Darren Aronofsky, both of whom have braved the backlash to defend their creative use of these tools, rather than avoid the hard conversation.

In furtherance of that hard conversation, the key question remains and should be answered directly by Affleck and Netflix: on top of what foundation model, exactly, is Netflix going to be building InterPositive’s tools?

Director Robert Rodriguez on AI as Creative Multiplier

Speaking of true creators, last month I had the unique pleasure of visiting the film industry equivalent of Willy Wonka’s Chocolate Factory: Robert Rodriguez’s Troublemaker Studios in Austin, Texas. I was there as an investor in his new development company Brass Knuckle Films, cofounded with producer Alexis Garcia. Like Eli Roth’s The Horror Section, BKF is funded through blockchain-based securities issued through Republic.com, such that investors will receive a share of any profits from the ventures. This new convergence of technology-enabled securities and film financing is itself an interesting development, but I was even more fascinated by the conversations at Troublemaker.

Unsurprisingly, it was absolutely delightful to meet Robert and tour the studio: hey look, it’s the biggest standing set in the US, from Alita: Battle Angel! Cool, there’s the car from Quentin Tarantino’s Death Proof! Oooh, that’s the matte painting from the end of From Dusk Till Dawn! Hearing Robert share his creative philosophy and preview the studio’s latest projects was just as inspiring as you would imagine.

Most interesting was hearing Robert talk about the future of AI in film production, where he voiced his hope to become an innovator not just in how to creatively use the tools but also in defining industry guardrails around their ethical use, which was music to this AI governance and copyright nerd’s ears.

To illustrate his hope that AI will multiply rather than supplant human creative capacity, he showed how he’d taken a 2D image of a cartoon monster that he designed and then experimented with tools from Luma Labs (which was a cosponsor of Brass Knuckle’s SXSW party earlier in March) to create a 3D model of the same character in a style that matched his creative intent. Echoing Soderbergh’s comments, Rodriguez highlighted how without AI he would have needed to send the 2D image to a designer to build a model that likely wouldn’t match his imagination and would need to be sent back for additional iteration, and at great cost, while the AI allowed him to quickly generate exactly what was in his head.

For a DIY creator who likes to do as much as possible on his productions both for creative and budget reasons—he shoots, he edits, he scores!—it’s not surprising to hear Rodriguez talking this way. He has always been a uniquely tech-forward and cost-conscious filmmaker. And to be clear, he didn’t make any specific representations about whether, when, or how he’ll be introducing generative AI into his development or production pipeline; the example he shared was just him fooling around with the tools. Even so, it’s good to have another veteran director willing to at least begin to engage on the question of where we do want to use AI in film, and where we don’t.

All that and Tex-Mex too! Truly, I couldn’t have asked for a better Austin weekend.

Virtual Studios: What’s the Difference Between Sin City and Generated Cities?

The new AI-driven virtual studio—the gen-AI iteration of the green-screen studios used by Robert Rodriguez on his Sin City films or Lucas on his Star Wars prequels—isn’t coming soon. Rather, it’s already here, with news this week of both a major feature film and a major streaming series soon to be released.

First up is news of director Doug Liman (The Bourne Identity, Mr. & Mrs. Smith) completing principal photography on Bitcoin: Killing Satoshi, his $70 million (?!) generative AI feature about the mysterious inventor of the cryptocurrency. Starring Gal Gadot, Pete Davidson, Isla Fisher, and Casey Affleck (AI runs in the family!), this “globe-trotting thriller” with over 200 locations purportedly would have cost $300 million if shot IRL. Instead, though, it was shot in a small gray warehouse with generated backgrounds to be added later.

Obviously that script would never have been produced as written and locations would’ve been pared down on a traditional shoot, so that Avatar-level number is a bit ridiculous. And the claim that this will be the first 100% generated film is also a bit misleading even if technically true. Presumably, every pixel will indeed be generated—including reproduction of the actors performances, in a video-to-video (as opposed to text-to-video) generative pipeline—rather than recorded performances simply being composited on top of generated backgrounds. Their process likely looks more like that used by this new and technically impressive AI-generated Spanish horror short film completed with consumer-grade tools (which raises the question of how this thing still cost $70 million). But saying “fully AI-generated” evokes completely generated performers as well, which this definitely isn’t.

Next up is the similar announcement from Luma Labs and production company Wonder Project, the producers of the Amazon streaming hit House of David, that they are teaming up to launch new AI studio called Innovative Dreams. That new studio is making Wonder’s next biblical series The Old Stories: Moses (with Ben Kingsley as the prophet) using what they are calling “hybrid filmmaking,” which appears to be the same sort of video-to-video performance capture and generative pipeline as the other projects mentioned above.

Finally, in a reversal of these stories about real actors and generated backgrounds, there was this past week’s news about a generated actor inserted into a traditional shoot: the digital “resurrection” by AI of deceased actor Val Kilmer in the trailer for the upcoming feature As Deep as the Grave. Although legally blessed by the actor’s family, this development raises the uncomfortable prospect that the digital likenesses of stars, like music libraries, are becoming something akin to tradable financial instruments.

This isn’t just a story about entertainers who have passed away, either: as Taylor Lorenz reported this past week in Vanity Fair, online influencers are increasingly producing content using generated “AI clones.” As one online commentator noted, “there will be very little reason for a Mr. Beast to actually show up to film a super bowl commercial in a few years [since] his identity will be in a .zip file controlled by [his manager].”

Again, all of these stories received an enormous amount of backlash online, but regarding Bitcoin and Moses, I’m left wondering: how is this so different from what Lucas and Rodriguez were already doing in the early 2000s? Does it really matter what kind of software is being used to fill in the backgrounds? Is the concern that these new methods reasonably feel more likely to meaningfully replace location shooting and the jobs that go with them, compared to those previous experiments that didn’t radically change the production ecosystem? (That’s a questionable assertion when you look at how omnipresent green screens are in modern big-budget productions.)

The concern makes some sense, but is it necessarily a bad thing for a domestic film industry that has lost much of its location shooting to foreign shoots anyway? It’s not clear to me that being able to shoot many more low-budget features in a studio, perhaps even in LA again, will employ fewer American cast and crew than producing much fewer big-budget on-location features internationally with the same amount of money. But we’ll definitely need to get that $70 million number down first, and get closer to the “make fifty movies with $100 million instead of one movie” future that Runway’s CEO is promising. And even then, the jobs saved in LA will still cost jobs elsewhere.

So Long Sora, Welcome Back Seedance 2.0, Hello to Netflix’s VOID

All this talk of AI-based production raises the question: what models will Hollywood be using to drive their virtual studios? This past month answered that question in regard to at least one model: it definitely won’t be OpenAI’s Sora!

When OpenAI announced on March 24th that it was shutting down Sora entirely—app dead by April 26th, API dead by September 24th, Disney’s $1 billion licensing deal collapsing within an hour of the news—it wasn’t just a bad day for the “Hollywood’s cooked” crowd on AI Twitter. It was also a load-bearing wall getting yanked out of any Hollywood AI pipeline that had bet on that model as a foundation (potentially including InterPositive, based on their patent). If your post-production toolchain depends on a model whose existence can be terminated overnight by a vendor whose incentives don’t align with yours, you don’t have a pipeline, you have a problem.

Meanwhile, as OpenAI’s Sora is retiring, ByteDance’s controversial Seedance 2.0 model is returning. The aggressively copyright-infringing preview of that model was pulled last month after a flurry of cease-and-desist letters from Hollywood. But it finally had its official release in the United States on April 9th, first via ByteDance’s video editing platform CapCut and then via other third-party model platforms, after a rolling international release.

However, the version that landed here bears only a passing resemblance to the one that generated the now infamous Tom Cruise vs. Brad Pitt fight clip. The Chinese-domestic Jianying version offers photorealistic faces, multi-shot storytelling, and almost no guardrails. The Dreamina Seedance 2.0 that paid CapCut Pro subscribers in the US can now access has been comprehensively defanged: real-face uploads are blocked, intellectual property keywords and visual matches are filtered, every output is watermarked, clips are capped at fifteen seconds, and the content moderation is aggressive enough that some creators are calling it “nerfed.” So now that Sora is dead, this potential back-up vendor for Hollywood’s AI pipelines is delivering a fraction of the capability that made it interesting in the first place.

Which makes the third story from the same news cycle perhaps the most interesting. On April 3rd, Netflix quietly released VOID—Video Object and Interaction Deletion—on Hugging Face under an Apache 2.0 license, its first-ever open-source AI model. VOID isn’t a Sora replacement; it’s a specialized fine-tuned model built on top of CogVideoX, the open source version of Chinese lab Zhipu AI’s proprietary Qingying video generation model. VOID narrowly focuses on physics-aware object removal, such that if you take someone or something out of a shot, VOID will also remove any physical impacts prompted by the now-absent person or item.

But the context is what matters: the same company that just spent up to $600 million acquiring the proprietary InterPositive workflow is also using and releasing its own open source video models. Those moves look like the beginnings of an overall AI pipeline strategy: avoiding reliance on outside proprietary models and instead developing internal proprietary models and using flexible open source models that won’t change or disappear at a moment’s notice.

The lesson for every studio and indie shop drafting its 2026 AI strategy (especially Disney who just got royally burned by OpenAI): better to control your own tech stack wherever possible, rather than rely on outside models that may not survive the brutal competition between labs, and where even if they do survive, the version you’re allowed to use may not be the version you wanted.

Writers vs. AI vs. Writers

Turning away from Hollywood and toward the publishing world, the last three weeks of March 2026 will be remembered as the moment when AI-generated writing stopped being a hypothetical across every institution that publishes words for a living. Five stories broke in tight succession, all variations on a single theme: who actually wrote that, and how much does the answer matter?

Let’s start with the AI resistance. On March 19th, Hachette canceled the US release of Mia Ballard’s horror novel Shy Girl through its Orbit imprint and discontinued the existing UK edition, after a New York Times investigation (and a Pangram analysis flagging ~78% of the text as AI-generated) forced their hand. This is the first known instance of a Big Five publisher walking back a book discovered to be written by AI. That discovery was driven by a user on r/horrorlit who catalogued the linguistic tells (the word “sharp” appearing 186 times, lists of three, em-dash overuse), then escalated through a 1.4-million-view YouTube essay titled “i’m pretty sure this book is ai slop.”

The next day, the New York Times severed ties with freelance critic Alex Preston after a reader noticed that his January book review had lifted phrases and full paragraphs from a Guardian critic’s review of the same novel. Preston confessed he’d used an AI tool to draft the review and “failed to identify and remove overlapping language from another review that the AI dropped in”—a new failure mode adjacent to plagiarism, where the model is the laundering machine.

Then on March 26th came a one-two punch from the “AI can be helpful for writers and publishers, actually” side of the debate. The Wall Street Journal profiled a Fortune business editor who has cranked out 600+ articles since July 2025 using Perplexity and NotebookLM, accounting for ~20% of Fortune‘s web traffic in H2 2025. Fortune‘s EIC told the Journal “more than 50% is Nick”—a quote that is perhaps less reassuring than it was probably intended to be.

Wired dropped a same-day companion profile of independent tech journalist Alex Heath, who uses Claude Cowork (with a custom skill called “10 Commandments for Writing Like Alex Heath”) to draft his Substack pieces end-to-end. Journalists across the internet variously attacked and celebrated these practices, fanning the flames of a fire that started a few weeks before when the editor of the Cleveland Plain Dealer promoted that newsroom’s use of AI to help source and write stories.

Sitting underneath all four new stories was NYT‘s March 9th interactive quiz—“Who’s a Better Writer: A.I. or Humans?”—a kind of Voight-Kampff test for prose, in which 86,000 readers blindly judged five paired passages and 54% picked the AI-generated ones, with one pairing splitting 67-33 in the machine’s favor.

Five stories, three weeks, one underlying question: is using AI to write a craft choice or a category violation? Some writers say one thing, some say the other, and 86,000 quiz-takers suggest that readers may not care which.

Full disclosure for CONVERGER readers: the entirety of this newsletter was originally written by me without AI assistance except for this feature and the previous one about Sora, where I experimented with a different workflow. For these two features, I solicited first drafts from Claude (inputting an outline with the key facts, key sources, and my rough take, then providing the previous features as an example of my style), then I heavily edited them (”more than 50% is Kevin”).

Did you see a difference as you were reading? The Pangram AI text detector didn’t: it concluded with a medium level of confidence that those sections were 100% human-written. Then again, the same tool predicted that a paragraph from Mary Shelley’s Frankenstein was 100% AI-written. So I’d love to hear your feedback on whether you noticed a shift in style.

A Contract That Helps Protect Comic Artists Against AI Training on Their Work

Comic book artists are rightfully concerned about AI being used to copy their styles or their designs and put them out of work. That’s a problem for someone like me, who works in AI but also is a writer currently developing a number of comic book projects and looking for professional artists to work with. Therefore, to reassure the artists with whom I’ve directly contracted to develop my comic ideas, I wrote the following anti-AI-training clause for our agreements:

Writer shall not use, nor license or authorize third parties to use, the Services [i.e., the artwork] in any manner for purposes of training generative artificial intelligence (AI) models to generate text, images, video or audio, including models to generate images or video reproducing the artwork or art style of the Artist, without prior written consent of the Artist. Nothing in this clause shall prohibit the use of generative AI models for routine internal production purposes including format conversion, upscaling, accessibility re-flows, translation, palette adjustment, or comparable non-creative functions.

[Another clause similarly prohibits the Artist from training on the commissioned artwork or my IP without my consent.]

“Generative AI models” include large language models, transformer models, diffusion models, and any other substantially similar types of machine learning models now or in the future that generate text, image, video or audio outputs based on model parameters derived from training on large datasets, regardless of whether those models are offered publicly, shared privately, or used internally, and regardless of whether those models are offered with open source licenses, closed source licenses, or are wholly proprietary. “Training” includes both the pre-training process that generates a model’s parameters and any post-training fine-tuning of a model’s parameters.

Artist and Writer each acknowledge that the other is not responsible for the unauthorized actions and conduct of third parties who attempt to use the Services or IP for generative AI training.

Remember: I’m not your lawyer! Please talk to one before sticking this language in your contracts. And if you have suggestions on how to improve this, let me know.

FRAGMENTS

WGA Deal on AI: Is That All There Is?

Beyond the narrow set of copyright and rights-of-publicity harms that litigation might address for certain actors and creators, organized labor is easily the most powerful lever for protecting entertainment industry workers from seismic displacement by AI. Which makes it all the more disappointing that the draft deal between the Writers Guild of America and the studios contains basically nothing new on AI, despite the WGA’s starting demand of payment for training on guild members’ scripts. As Variety first reported, “the deal largely preserves the status quo” on AI, with the studios only agreeing “to continue to hold meetings with the WGA, and to notify the guild if it licenses writers’ work for AI training.” Hopefully the other guilds, including the Screen Actors Guild, will fare better in their negotiations.

News of the Supreme Court’s Ruling on AI and Copyright Has Been Greatly Exaggerated

On March 2 the Supreme Court declined to review the DC Circuit’s decision in the case of Thaler v. Perlmutter that copyright does not protect works that are generated by AI without any human input; i.e., there must be a human author. This non-decision by the Supremes was immediately and widely touted by anti-AI voices online for the broad proposition that the Supreme Court had ruled that AI-generated content isn’t copyrightable. However, the facts of this case were really narrow: the AI at issue wasn’t modern gen AI but rather an AI art project whereby an algorithm trained on a wide swath of human works of art would self-generate new works with no human instruction or involvement at all; it was literally press-here-to-generate.

The much harder question of how much human guidance is required to create a copyright interest in modern AI-generated content—how detailed or iterative the prompts, how much human-created material uploaded as reference or for generative modification, how much human editing and arrangement of the outputs, etc.—still has yet to be answered by the courts. So, what’s the safe bet right now when working with AI? Lawyers suggest relying as much as possible on your own creative output (hopefully you were already doing that!), and documenting exactly what you personally authored or modified.

Macro-Growth in the Micro-Drama Content Pipeline

Micro-dramas are soapy, cliffhanger-heavy, short-form vertical TV series with sensational hooks (The Double Life of My Billionaire Husband; Tricked Into Having My Ex-Husband’s Baby; Return of the Abandoned Heiress) that are optimized for compulsive mobile viewing. Already a mature multi-billion business in Asia, the US market has finally started to catch up in the past couple years, including an explosion of low-budget microdrama production in Los Angeles and a recent forty-microdrama production partnership between YouTube star Dhar Mann and Fox Entertainment. Now, in just the past few weeks, a number of major content producers have made deals to adapt or produce original work for this exploding medium: HarperCollins partnered with AI-driven animation studio Toonstar to produce a slate of animated microdramas, starting with popular middle grade series Friendship List, while its romance imprint Harlequin signed a similar deal with another animation tech studio, Dashverse; Issa Rae’s Hoorae Media inked a deal to bring microdramas to TikTok, starting with the horror series Screen Time; and finally the National Enquirer is licensing its archives for a microdrama slate with verticals app GammaTime. I can’t wait for the inevitable Batboy microdrama!

Meanwhile, In the YouTube-to-Theaters Pipeline: Backrooms is Coming

Just a few months after YouTube star Markiplier (Mark Fischbach) had modest but definite success with his self-financed and self-produced sci-fi feature Iron Lung, the trailer for the next YouTube-to-feature title has hit. From A24, it’s called Backrooms, based on a YouTube series of horror shorts inspired by a creepypasta meme that originated on 4chan, about being trapped in an eerie dimension of endless empty office hallways. The director of the shorts is making his feature debut, and the trailer appropriately vibes creepy as hell.

Old Music Beats New Music Beats AI Music

Despite concerns about endless new AI-generated music tracks swamping streaming sites, the latest data shows that old music is absolutely dominating over all new music: data from Luminate shows that new music (less than 18 months old) accounted for only 35.8% of what Americans listened to in 2024, compared to 73.3% in 2014, while according to ChartMetric, only 3 of the top 10 songs in 2025 were released in 2025. Meanwhile, streaming demand for original non-AI music—at least according to Universal Music Group—is not meaningfully being affected by the rise of Suno and other AI music apps. That’s what a senior UMG VP said during a recent earnings call, which was probably an unpleasant surprise for UMG’s lawyers: they are suing Suno arguing that music from Suno’s AI models, trained on UMG artists’ music, is diluting the streaming market for the record company’s songs. Interesting litigation strategy!

New Script-Reviewing AI Really Wants Brett Ratner to Direct Your Movie

The Wrap tried out Quilty, a new AI tool promising to analyze and provide helpful creative and business feedback on movie scripts, by feeding it the screenplays for already-produced movies Sinners, Barbie, Christy, and Die Hard. Quilty predicted that the hits would flop and the flops would hit. More bizarrely, the AI script reviewer recommended alleged sex harasser and proven hack Brett Ratner (Rush Hour, Rush Hour 2, Rush Hour 3), whose most recent film was the Melania documentary, as a top director pick for three of the four submitted scripts—including Barbie?! What, do the Ellisons own this company, too?

Is Fan-Created Content Supplanting Canonical Content?

According to a December study from Ogilvy Consulting cited in this excellent Ankler story discussing the role of fandom and using the The Super Mario Galaxy Movie as a hook, “Two-thirds of Gen Zs spend more time with fan-created content than with the official titles.” Makes me wonder: what percentage of their consumption is non-fan, original, nonprofessional content, or even self-created content? And how quickly will those numbers grow in the next few years?

The Future’s So Bright I Have To Enter This Contest

Short story contests inviting visions of the future of a particular issue or technology are such a common feature of the sci-fi and futures toolbox that I programmed a panel on the topic a few years ago. Yet this new Protopian Prize contest in particular caught my eye, though not because of the solicited topics (hopeful futures about AI and governance).

I tend to think “write more optimistic futures!” projects are based on a fallacious take that positive stories help lead to better futures than dystopias, since dystopias have arguably been a much more positive influence by providing self-preventing prophecies that help us guard against their negative futures. For example, 1984 is probably the sci-fi tale that has had the broadest positive impact on technology policy debates, including in my own experience working on privacy and surveillance policy. But the judging committee of this new prize is full of absolutely extraordinary writers and thinkers who are very aware of the value of dark future visions as well as bright, including Annalee Newitz (Automatic Noodle), Hannu Rajaniemi (The Quantum Thief), and Ruthanna Emrys Gordon (A Half-Built Garden, easily my favorite sci-fi novel of 2022). So, I’m very excited to see what they pick. Submissions open May 1st and close July 31st, so start futuring now!

Big Brother, Generating Slop

Speaking of 1984, it turns out Orwell predicted slopaganda (AI slop for political purposes, like the mad Lego rap videos coming out of Iran right now) in his classic novel. A poster on Twitter highlighted this passage:

There was a whole chain of separate departments dealing with proletarian literature, music, drama, and entertainment generally. Here were produced rubbishy newspapers containing almost nothing except sport, crime, and astrology, sensational five-cent novelettes, films oozing with sex, and sentimental songs which were composed entirely by mechanical means on a special kind of kaleidoscope known as a versificator.

Oh what a brave new world! (Wait, that’s Huxley…I mean, Shakespeare…)

Webtoon Translations, Digital Comics, Tiny Onions

Pulling together a few different comics-related items:

First up: Webtoon, a site for web-native vertical comics that has already seen a few controversies over allegedly AI-generated comics art, launched its opt-in AI-driven translations tool with only a tiny bit of anti-AI pushback in response.

Second: digital comic book stores—the folks who sell digital versions of the paper comics sold in IRL comic shops through the comic book “direct market”—is getting crowded and confusing as a range of old and new services try to take market share from Amazon’s Comixology. Thankfully The Beat wrote this handy guide to help make sense of the current state of the digital comics landscape.

Finally: I’ll be writing a lot more someday about Tiny Onion, the comics production studio founded by star writer James Tynion IV. The young company has helped enable and solidify Tynion’s rise through the ranks of independent comics creators, with horror hits like Something is Killing the Children that have multiple comic spinoffs and several TV and film adaptations in the pipeline. I’d kill for a comic-nerd Harvard Business Review case study of Tiny Onion’s dominating entrance onto the media scene, but until then here is an insightful interview with Eric Harburn. Harburn is Tiny Onion’s Editor-in-Chief—and now, in consideration of the company’s broad multimedia ambitions, Director of Narrative—and he talks about how Tynion and the company go about building narrative “engines” that can power multiple cross-media properties. If you’re into comics you should consider subscribing to SKTCHD, an excellent comics news site, to read the whole thing.

And that’s what’s converging this week! See you next time.