Outsourcing work to AI also risks losing much of the creativity that produces original work, warns Kosmyna. The essays that students in her study wrote with ChatGPT looked very similar and were described by the teachers marking them as “soulless”, lacking originality and depth, Kosmyna says. “One of the teachers asked if students were sitting next to each other because the essays were so similar.”
While studies such as these illustrate the short-term effects LLMs can have on the brain, the long-term impacts are far less clear. The study by Kosmyna and her colleagues provides a glimpse. Four months after the initial study they asked the students to write another essay, but this time those who had used ChatGPT were told to work without LLM support. The neural connectivity in their brains was lower than those who switched the opposite way, perhaps indicating that they had not engaged with the topics properly in the first place.
Cognitive decline
Yet, LLMs can be a positive tool to aid thinking, but only if we don’t rely on them by outsourcing our mental tasks in the process, says computational neuroscientist Vivienne Ming, author of Robot Proof. She’s concerned though that this is not how most people interact with this technology.
Her reasoning comes from research she conducted for her book, during which Ming asked a group of students at the University of Berkeley to predict real-world outcomes, such as the price of oil. She found that the majority of participants simply asked AI and copied the answer.
She measured their brains’ gamma wave activity – a marker of cognitive effort – finding it showed very little activation. Again her research is yet to published, but Ming worries that if her findings are borne out in further studies it could have long-term implications. Other research, for example, has linked weak gamma wave activity to cognitive decline later in life.
“That’s really worrying,” Ming says. “If that is a natural mode for people to interact with these systems – and these are smart kids – that’s bad.” Deep thinking, she says, is our superpower. “If we don’t use it, the long-term implications for cognitive health are pretty strong.”
That’s because when we rely on LLMs it requires very little cognitive effort, Ming adds, which is exactly what’s needed for a healthy brain.
A small subset of participants though – less than 10% – worked differently and used AI as a tool to gather data that they then analysed themselves. These individuals made more accurate predictions than others participants and showed stronger brain activation too.
For long-term brain health we need to continue to challenge ourselves
READ MORE ON THE NEXT PAGE..
