A new study shows that, while using AI in research can increase productivity, it also risks reducing job satisfaction for scientists From the Future of Being Human Substack.
I’ve written quite a bit about the role of artificial intelligence in accelerating research and discovery recently — including this article on supercharging research using AI, and the writeup on AI for scientific discovery in this year’s list of World Economic Forum Top Ten Emerging Technologies.
And so I was quite shocked to see an article this weekend from good friend and Chief AI Officer at Western University Mark Daley titled “Misery and Meaninglessness in the Lab: A divisive journey to the heart of AI’s impact on discovery”.1
Mark’s article refers to a just-published study from MIT’s Aidan Toner-Rodgers that looked at the impact of AI on materials science innovation the R&D lab of a large U.S. firm.2
Toner-Rodgers’ paper is wide ranging and worth reading just for its insights into the use of AI to boost productivity in scientific discovery. In particular, the research shows a significant increase in research and development productivity when scientists used an AI tool designed specifically to increase the rate of discovery of new materials.
However — and this is what stuck out for me in Mark’s article — the research also showed that (quoting Toner-Rodgers) “while enjoyment from increased productivity partially offsets this negative effect—especially for high-ability scientists—82% of researchers see an overall decline in satisfaction” …