82% workers who use AI at work are unhappy, finds study: 'Much of my education is now worthless'

The study, conducted on 1,018 scientists working at a large US-based research and development lab since May 2022. (Representational image)

While the use of artificial intelligence (AI) tools in workplaces has increased, a recent study has found that it has certainly enhanced productivity, but at a cost. More than 80 percent of the workers evaluated said that they have been unhappy at work and reported reduced job satisfaction, the study by a doctoral student at MIT found. In comparison, the AI tools led to a 17 percent increase in new product creation amongst these workers.

"The technology has strikingly disparate effects across the productivity distribution: while the bottom third of scientists see little benefit, the output of top researchers nearly doubles," the study, conducted on  1,018 scientists working at a large US-based research and development lab since May 2022, found. "Survey evidence reveals that these gains come at a cost, however, as 82 percent of scientists report reduced satisfaction with their work due to decreased creativity and skill underutilisation."

One of the scientists who took part in the study told the Wall Street Journal: “I couldn’t help feeling that much of my education is now worthless.”

But the AI tool also had other impacts, pointed out researcher Aiden Toner-Rodgers. It helped generate various “recipes” for new chemical compounds, and accounted for 57 percent of scientists’ “idea generation.”  That means that a “key, creative part of the process was automated,” he told the publication. “Maybe the most exciting thing about AI is that it could accelerate scientific discovery and innovation. This would be a huge benefit.”

Further, adding to the debate about human expertise and creativity in a world of AI, Toner-Rodgers said he found that AI substantially boosted materials discovery, leading to an increase in patent filing and a rise in
downstream product innovation. "However, the technology is effective only when paired with
sufficiently skilled scientists," he said. "The model must be complemented by domain experts who can evaluate and refine its predictions."