In a small study, an AI ‘brain decoder’ inches toward reading minds
In a new Nature Neuroscience paper published Monday, Huth and a team of researchers from the University of Texas at Austin introduced a new “brain decoder” enabled by GPT-1, an earlier version of the artificial neural network technology that underpins ChatGPT. After digesting several hours of training data, the new tool was able to describe the gist of stories the three participants in the proof-of-concept experiment listened to — just by looking at their functional MRI scans.
Very cool stuff. And I am happy to see the ethical considerations have been considered:“It is important to constantly evaluate what the implications are of new brain decoders for mental privacy,” said Jerry Tang, a Ph.D. candidate in Huth’s lab and lead author on the paper, in a press briefing. In devising ways to protect privacy, the authors asked participants to try to prevent the decoder from reconstructing the words they were hearing several different ways. Particularly effective methods included mentally listing off animals, and telling a different story at the same time the podcast was playing were particularly effective at stopping the decoder, said Tang. The authors also found that the decoder had to be trained on each subject’s data and wasn’t effective when used on another person. Between these findings and the fact that any movement would make the fMRI scans worse, the authors concluded that it’s not currently possible for a brain decoder to be used on someone against their will.