Watching you, watching it: Disney turns to AI to track filmgoers’ true feelings about its films – Technology & Science

Movie studios have a long tradition of testing out new films to see how audiences react before launching them in wide release. But with their latest research innovation, Disney is taking it to a whole new level.

Now as you’re settling in to watch the latest Disney blockbuster, the movie could also be watching you.

And while this could signal an exciting new era of responsive storytelling in which movies are shaped around our likes and dislikes in real time, it also raises some red flags about yet another frontier in personal data collection.

At a conference in July, Disney Research presented a new process called factorized variational autoencoders (FVAEs). Put in plain English, it measures complex audience reactions by assessing facial expressions. 

This deep-learning system has been trained to watch an audience of hundreds of faces in a darkened theatre, and to track their reactions: Are they smiling or crying? Bored or asleep, even? 

This graphic, included in an online publication from Disney Research, shows how factorized variational autoencoders (FVAEs) work, as ‘facial landmarks’ are detected on audience members throughout the duration of a film. (Disney Research)

Disney Research is able to generate far more data than human intelligence is able to process. In their tests, they generated 16 million data points derived from 3,179 viewers.

And that’s where artificial intelligence (AI) plays a role. As Disney Research scientist Peter Carr explained to, computers can much more easily synthesize that massive yield of data, allowing Disney to measure the success of a film with a granularity that goes far beyond a subjective “did you like the movie?”

In fact, not only can FVAE measure reactions, Disney says the process can reliably predict them, too.

After observing an audience member’s reactions for just a few minutes, the system is able to predict his or her facial expressions for the rest of the film using a pattern-recognition technique that functions similarly to a recommendation engine; it can generalize the reactions of an entire audience, and measure those reactions against an input that states how viewers “should” be reacting.

So you know all of those times you started watching a movie, thinking you’d hate it, but actually ended up loving it? It could now be possible for Disney to predict your enthusiasm for the flick before you were even consciously aware of your change of heart.

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