Computers can predict our preferences directly from our brain
A research team from the University of Helsinki and University of Copenhagen demonstrates it is possible to predict individual preferences based on how a person’s brain responses match up to others. This could potentially be used to provide individually-tailored media content — and perhaps even to enlighten us about ourselves.
We have become accustomed to online algorithms trying to guess our preferences for everything from movies and music to news and shopping. This is based not only on what we have searched for, looked at, or listened to, but also on how these activities compare to others. Collaborative filtering, as the technique is called, uses hidden patterns in our behavior and the behavior of others to predict which things we may find interesting or appealing.
But what if the algorithms could use responses from our brain rather than just our behavior? It may sound a bit like science fiction, but a project combining computer science and cognitive neuroscience showed that brain-based collaborative filtering is indeed possible. By using an algorithm to match an individual’s pattern of brain responses with those of others, researchers from the University of Copenhagen and the University of Helsinki were able to predict a person’s attraction to a not-yet-seen face.
The research article has just been presented at The Web Conference 2021.
The researchers behind the study are Keith M. Davis III and Dr. Michiel Spapé of the University of Helsinki and Dr. Tuukka Ruotsalo.
Ruotsalo’s research at the University of Copenhagen’s Department of Computer Science focuses on developing cognitive models that combine machine learning and human-computer interaction. Tuukka Ruotsalo develops new types of machine learning methods that can learn user intentions and preferences by measuring human cognition.