At least occasionally, a narrative that you imagine will materialize.
Though it may sound like something out of science fiction, a new artificial
intelligence (AI) model created at the University of Texas at Austin has
been successful in doing just that. The model may be trained to decipher
sophisticated language from someone's thoughts for lengthy periods of time
using simply noninvasive scanning techniques.
"For a noninvasive method, this is a real leap forward compared to what's
been done before, which is typically single words or short sentences,"
research co-leader Alex Huth, an assistant professor of neurology and
computer science, said in a release.
Other systems with a similar function are being developed, but this one
stands out because participants don't have to have surgery to have implants
fitted, and they aren't limited to a vocabulary list.
The model, known as a semantic decoder, is trained on hours of data from an
individual while they listen to podcasts while having their brain scanned
using functional magnetic resonance imaging (fMRI), using technology similar
to that used in Open AI's ChatGPT and Google's Bard chatbots. With the
participant's permission, the model will later produce a stream of text by
decoding their thoughts when they are listening to a new narrative or
envisioning telling one.
The results were as follows: While the decoder is unable to synthesis a
person's ideas word for word, it frequently manages to catch the essence of
what they are thinking. After extensive training, it is capable of producing
text that, about half the time, accurately captures the author's
thoughts.
The study extended beyond only hearing or contemplating stories. This video
demonstrates what the model was able to interpret from a subject's brain
activity while they were silently watching a movie clip:
Even if it's not ideal, the fact that it's all non-invasive is a major
bonus. It's believed that in the future, technological advancements like
these can benefit people who are no longer able to physically communicate
through voice, such as certain stroke survivors.
However, you're not alone if looking at this type of technology makes you
feel uneasy. A technology that can read your thoughts is more often the
stuff of dystopian fears than science fiction for many people.
The study's co-lead and PhD student Jerry Tang addressed these
understandable worries by stating, "We take very seriously the concerns that
it may be utilized for negative ends and have endeavored to avoid that. We
want to ensure that individuals only use these technologies when they want
to and when they are beneficial to them.
The first practical issue is that this system must first undergo hours of
training before it can start to function. Before this actually works on a
person, Huth said, "they need to spend up to 15 hours lying in an MRI
scanner, being perfectly still, and paying good attention to stories that
they're listening to."
In addition, there is a failsafe: simply thinking of anything unrelated,
like animals, even someone who had helped train the model might stop it from
deciphering their inner speech.
Privacy and safety, however, remain a top priority as the researchers try
to advance this technology. "I think it's important to be proactive by
enacting policies that protect people and their privacy right now, while the
technology is in such an early stage," said Tang. "Regulating the purposes
for which these devices may be used is also crucial."
The study is published in
Nature Neuroscience.
