Mind reading machines - meh

An interesting article at Nature about some advance in looking at how brains are working while thinking stuff, and being able to interpret the thoughts:

In a study published in Nature Neuroscience on 1 May, the researchers got 3 volunteers to lie in an fMRI scanner and recorded the individuals’ brain activity while they listened to 16 hours of podcasts each¹. By measuring the blood flow through the volunteers’ brains and integrating this information with details of the stories they were listening to and the LLM’s ability to understand how words relate to one another, the researchers developed an encoded map of how each individual’s brain responds to different words and phrases.

Next, the researchers recorded the participants’ fMRI activity while they listened to a story, imagined telling a story or watched a film that contained no dialogue. Using a combination of the patterns they had previously encoded for each individual and algorithms that determine how a sentence is likely to be constructed on the basis of other words in it, the researchers attempted to decode this new brain activity....

The decoder generated sentences that got the gist of what the person was thinking: the phrase ‘I don’t have my driver’s license yet’, for instance, was decoded as ‘she has not even started to learn to drive yet’. And it did a fairly accurate job of describing what people were seeing in the films. But many of the sentences it produced were inaccurate.

The researchers also found that it was easy to trick the technology. When participants thought of a different story while listening to a recorded story, the decoder could not determine the words they were hearing. The encoded map also differed between individuals, meaning that the researchers could not create one decoder that worked on everyone. Huth thinks that it will become even more difficult to develop a universal decoder as researchers create more detailed maps of individuals’ brains.

Determining how the brain creates meaning from language is enormously difficult, says Francisco Pereira, a neuroscientist at the US National Institute of Mental Health in Bethesda, Maryland. “It’s impressive to see someone pull it off.”‘

Given that it sounds and expensive and time consuming to get it to work with modest accuracy,  and is easily confused, I don't see any real reason to fear widespread implementation.