Famous economists Daron Acemoglu and David Autor have recently raised an alarm over a doctoral student’s working paper. Here’s why they doubt the accuracy of the memo’s assertions about the productivity boon AI is expected to bring. So in January, a new assistant professor of computer science with an impressive background in materials science brought it up. They challenged the data and conclusions reported in the research paper.
The event has drawn the attention of multiple national media outlets, including The Wall Street Journal. Perhaps most tellingly, it highlights the increasing pressure being placed on controversial AI research. Acemoglu and Autor emphasized their doubts, stating that they have “no confidence in the provenance, reliability or validity of the data and in the veracity of the research.” They noted that while the concepts discussed in the paper are “already known and discussed extensively in the literature on AI and science,” they have yet to find a place in any refereed journal.
Acemoglu, a prominent economist at the Massachusetts Institute of Technology (MIT), and Autor, a respected colleague, were approached separately by the computer scientist, who expressed serious concerns about the integrity of the research. This recent example underscores the continued need for rigorous peer review as a cornerstone of academic research. It’s important everywhere, but particularly in fast-changing areas such as AI.
Anthony is the weekend editor at TechCrunch. An accomplished journalist, he draws on years of experience as tech reporter at Adweek, and as a senior editor at VentureBeat. His conception comes from experience reporting on local government at the Hollister Free Lance. Prior to CityLab, Ha was vice president of content at the venture capital firm 500 Startups. Serving in this role further intensified his interest in technology and innovation.
Having lived in New York City, Ha’s perspective on tech trends and developments are uniformly celebrated. The scrutiny of the AI research paper reflects broader concerns within the academic community regarding data integrity and ethical standards in research practices.
