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MIT Says It No Longer Stands Behind Student's AI Research Paper
MIT said Friday it can no longer stand behind a widely circulated paper on AI written by a doctoral student in its economics program. The paper said that the introduction of an AI tool in a materials-science lab led to gains in new discoveries, but had more ambiguous effects on the scientists who used it. WSJ: MIT didn't name the student in its statement Friday, but it did name the paper. That paper, by Aidan Toner-Rodgers, was covered by The Wall Street Journal and other media outlets. In a press release, MIT said it "has no confidence in the provenance, reliability or validity of the data and has no confidence in the veracity of the research contained in the paper." The university said the author of the paper is no longer at MIT. The paper said that after an AI tool was implemented at a large materials-science lab, researchers discovered significantly more materials -- a result that suggested that, in certain settings, AI could substantially improve worker productivity. But it also showed that most of the productivity gains went to scientists who were already highly effective, and that overall the AI tool made scientists less happy about their work. Read more of this story at Slashdot.
MIT said Friday it can no longer stand behind a widely circulated paper on AI written by a doctoral student in its economics program. The paper said that the introduction of an AI tool in a materials-science lab led to gains in new discoveries, but had more ambiguous effects on the scientists who used it. WSJ: MIT didn't name the student in its statement Friday, but it did name the paper. That paper, by Aidan Toner-Rodgers, was covered by The Wall Street Journal and other media outlets. In a press release, MIT said it "has no confidence in the provenance, reliability or validity of the data and has no confidence in the veracity of the research contained in the paper."
The university said the author of the paper is no longer at MIT. The paper said that after an AI tool was implemented at a large materials-science lab, researchers discovered significantly more materials -- a result that suggested that, in certain settings, AI could substantially improve worker productivity. But it also showed that most of the productivity gains went to scientists who were already highly effective, and that overall the AI tool made scientists less happy about their work.
Read more of this story at Slashdot.
