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Transcript: Ben Affleck Interview at Bloomberg Screentime 2026

In this wide-ranging interview with Bloomberg’s Lucas Shaw, Ben Affleck opens up about founding InterPositive, the AI filmmaking company Netflix acquired, and why he believes AI will be additive rather than destructive for Hollywood. Affleck also discusses his new Netflix thriller Animals, the Joe Rogan clip controversy, and how Artists Equity is pushing performance-based compensation and residuals to realign the economics of the film industry. Read the full transcript of the interview below:

Why Ben Affleck Started an AI Company

LUCAS SHAW: (00:00:00 – 00:00:15) You are identified as the CEO of Artists Equity. You have a movie coming out that I want to talk about, but I want to start with InterPositive just because I think a lot of people were maybe not confused but thrown when they found out that you had not only started an AI company, but that Netflix was buying it for a bunch of money.

BEN AFFLECK: (00:00:16 – 00:00:30) It’s the reaction I get anytime I seem to do anything that remotely resembles achievement. It’s a vaguely baffled “is this guy? You got to be kidding me.” Well, you—

LUCAS SHAW: (00:00:30 – 00:00:45) one of the reasons among many I wanted to talk to you is because even prior to that, you had said a lot of very intelligent things about AI and seemed like someone who had been spending time doing the work trying to figure it out. So when and how did you decide to start a company, and what was the goal?

BEN AFFLECK: (00:00:47 – 00:04:19) Well, I’ve had a sort of interest in technology and trying to build— and a number of failed attempts to build companies as a sort of a tandem life going back to the early ’90s, predating most of people’s lifespan here. When I tried to build a nonlinear editing company with PCs to— because Avids are too expensive, that didn’t work because the drives were too slow and they dropped frames.

And then a few years later, as the— but I was always somebody who built computers and liked to play with them and like to program them, mostly for games and stuff like that. But I was always interested in it. And then as filmmaking segued from analog to digital and they started working with the moving image started to be mostly an array of numbers called the tensor. That became part of the visual effects workflow. Machine language is part of that. I learned Python. And so I have had an ongoing relationship with that technology.

I started a company called LivePlanet with Sean Bailey and Matt Damon in 2000, where we did Project Greenlight, and we did a bunch of shows that were new media and old media. And the whole thing was, how can you make money advertising online. There’s not enough people. And we were very proud of us. We said, “we have 40 million people watching a television show. You should be—” but the truth was, it was an interesting idea. And we did some interesting stuff. And I got some exposure to what it meant to raise money and start a business.

And so when I was— I started— had a small visual effects company. And some of the people that I was working with there said, “you should see what Google’s doing with Transformer. And there’s this— then there’s this company OpenAI, and they have this text-to-image thing.” And as I was telling you before, my life has— I’ve learned to take advantage of the opportunities my life has afforded, which is essentially, probably inappropriately, I find often I’m able to just pick up the phone and say, “hi, I’m Ben Affleck, can I just come in and see what you’re doing?” People are like, “sure.” Still baffles me, but nonetheless Went in, looked at what they were doing.

At first kind of had a heart attack because I was like, “holy—” I called Matt Damon, I was like, “dude, we have to do as many movies in the next few years because we’re finished.” Went back, looked at it, and then started saying, “well, hold on a second, why isn’t this working in the way that I think it should work?” And it was a very strange thing to realize that I was dealing with researchers and scientists who were so incredibly smart in this one way. I had so little information about video and how it’s created or how it’s defined and how it’s captioned and how it needs to be organized.

And so having learned the lessons of the previous failed entrepreneurship and having raised money for Artists Equity already, I gambled on this notion that in order to do this in an ethical way and in a way that could take this technology and actually make it work hand in glove with artists in this community, that where there are very fixed, longstanding relationships around likeness and so forth, we had to create our own dataset.

So I raised the money, I shot for about 8 months with a lot of cameras and a lot of equipment and created a dataset that would serve as late-stage training for open models to do discrete tasks, sort of where the training code and the inference code were related to one another and geared toward actual specific tasks that would generate value. As opposed to, “oh, this is novel, that’s kind of cool, look what it can do.” But to sort of say it needs to hit these criteria. And I didn’t tell anybody about it, what they call—

How InterPositive Trains AI Without Using Other Filmmakers’ Work

LUCAS SHAW: (00:04:19 – 00:04:44) and when— sorry, when you were talking about— because you were using, I think, some language that maybe not everyone in the audience is going to know. So can you dumb it down ever when you’re talking? Because my understanding, and correct me if I’m wrong, is you have— you develop tools where you shot something, you would then train the model on what you had shot, and you could then use that to manipulate or adapt things that you had already made, right?