The Oscars’ AI Lie: Don’t Ask, Don’t Tell
Last year’s ‘Brutalist’ controversy gave way to a landscape where the tech is rewarded — as long as it’s cloaked in prestige
I cover the intersection of Hollywood and AI for paid subscribers. I wrote about eight companies doing AI the right way, explored Disney’s deal with OpenAI and dove into what AI performer Tilly Norwood means for actors.
The Academy of Motion Picture Arts and Sciences keeps repeating the same line about artificial intelligence: that its use in filmmaking “neither helps nor harms” a movie’s Oscar chances.
It sounds neutral, even judicious. But neutrality, as the Swiss learned a few decades ago, is a choice — and a consequential one. And it marks a new front in the war over what constitutes “human authorship.” Because the Oscars aren’t facing a hypothetical future shaped by AI. They’re already adjudicating films made inside the frameworks of this technology. By refusing to draw clearer lines, the Academy has turned this year’s awards into a referendum on how much machine assistance Hollywood is willing to bless as human achievement.
For the record, the Academy’s official guideline on the matter: “With regard to Generative Artificial Intelligence and other digital tools used in the making of the film, the tools neither help nor harm the chances of achieving a nomination. The Academy and each branch will judge the achievement, taking into account the degree to which a human was at the heart of the creative authorship when choosing which movie to award.”
This year’s best picture frontrunners are One Battle After Another and Sinners — two very different films that nonetheless share one defining trait: They were made by an industry where AI is already part of the air, even when no one bothers to mention it. None of the producers of these films have been compelled to disclose AI workflows. And that silence may be the most telling data point of all.
Take One Battle After Another. The film has been praised for its performances, its exquisite crafts and its classical restraint — precisely the kinds of qualities the Academy frames as proof of “human authorship.” You don’t hear a lot about any AI-assisted post-production tools that were likely used for dialogue cleanup, automated sound balancing, stabilization and editorial efficiencies that compress timelines and costs. And why would you? That’s all pretty standard across cinema, including prestige auteur projects. A representative for One Battle After Another did not respond to request for comment.
Sinners is maximalist, technically ambitious and the most aggressively rewarded film of the year, landing a staggering 16 nominations. Publicly, it’s being framed as a triumph of vision and execution. Privately, it’s also understood as a model of contemporary studio filmmaking, where AI-assisted pre-visualization, planning tools and post workflows are simply assumed. Michael B. Jordan’s virtuosic performance as twins — rightly rewarded with a best actor nomination — was refined with cutting-edge VFX work, including a toolset from Rising Sun Pictures called REVIZE that uses machine learning techniques for face replacement.
The conversation has shifted. Films can score multiple Oscar nominations without Academy voters being asked to factor in whether machine intelligence helped make them more efficient, more polished or more competitive. The Academy doesn’t interrogate. Campaigns determine how much they volunteer. Don’t ask, don’t tell.
And the big question: Does it even matter anymore?
Today I dig into what this standoff means for the Oscar race and for the encroachment of AI tech into new arenas of Hollywood, including:
What a best picture snub for Avatar: Fire and Ash reveals about the industry’s rapidly shifting perspective on technology
How last year’s brouhaha about The Brutalist’s AI-assisted Hungarian dialogue — and the Academy’s silence — reset the debate over the tech
The auteurs still holding the line against AI, and which Academy constituencies fall on which side of the fence
The long-term consequences of the Oscars’ agnostic approach to AI