Cross-posted from C4C’s LinkedIn page – see the original article

In late January, the Motion Picture Association (MPA) co-organised an exclusive screening in Brussels of Brady Corbet’s movie ‘The Brutalist’, which was awarded three Golden Globes.

Budapest, the Hungarian capital, was the prime filming location for this movie, which stars Adrien Brody as a Hungarian-born Jewish Holocaust survivor who emigrated to the US. Zoltán Tarr, a Hungarian Member of the European Parliament (MEP) who is the European People’s Party (EPP) coordinator for the EP’s Culture and Education (CULT) Committee, delivered the opening remarks at this Brussels screening.

The film’s editor, Dávid Jancsó, discusses AI’s role in the (post-)production process in an interview with RedShark Media, which explores the technical intricacies of making this movie. This article set off a snowball effect, creating controversy about the movie’s Oscar-worthiness for its use of AI, to the point that Corbet felt the need to issue a reaction to Deadline.

What’s the Fuss About?

A Ukrainian AI tool, Respeecher, was used to perfect the Hungarian pronunciations in some dialogues.

Jancsó, a native Hungarian speaker, considers it “one of the most difficult languages to learn to pronounce” and points out that the actors did “a fabulous job”. Then why the turn to AI? It was to “perfect it so that not even locals will spot any difference,” he explained.

“It is controversial in the industry to talk about AI, but it shouldn’t be,” Jancsó said, as he reminded, “There’s nothing in the film using AI that hasn’t been done before. It just makes the process a lot faster”. Deadline makes an interesting observation in this context: “We understand that the use of AI on The Brutalist didn’t eliminate jobs, rather created them.”

Garbage Out Due to Garbage In Is Likely to Affect EU Quality Content Most

Putting aside all the controversy around human creativity and the use of AI, this debate highlights broader policy implications. Using AI tools for applications in local languages requires that these models ingest quality training data in those languages to avoid a “garbage in, garbage out” scenario.

This raises an important question: What if quality Hungarian audio data had not been available for training AI tools like Respeecher?

If AI models lack diverse and representative linguistic data, the ability to refine pronunciation and enhance linguistic authenticity in films diminishes. This directly affects how local languages—especially those with smaller global reach—are represented in creative productions. The fact that The Brutalist benefited from AI-assisted pronunciation refinement suggests that Hungarian speech data was accessible for AI training. However, restrictive policies that limit the availability of local-language content for AI model training could jeopardize future applications of these technologies, to the detriment of the production of content in local languages.

This case exemplifies a broader reality: discussions about AI should not just be about the potential threat to the creative sector—we need to acknowledge AI is also a powerful enabler of authenticity, efficiency, and new creative possibilities. The challenge ahead for policymakers is not to block AI’s access to cultural and linguistic diversity but to ensure that AI systems are built in a way that respects creators while enabling innovation.

If we strip AI of the ability to learn from local content, the first victim may well be the very authenticity and cultural richness the EU seeks to preserve.