3 Questions: What is the best path forward for AI in academia?
With artificial intelligence capabilities continuing to expand, universities now face complex, urgent questions about how to navigate increasing challenges, as well as new opportunities. Much attention is now directed toward this, including an MIT report on AI and education published this summer.
A new essay from MIT Statistics and Data Science Center Director Sasha Rakhlin, the Distinguished Professor in Data, Systems, and Society, IDSS and Brain and Cognitive Sciences, synthesizes recent discussions and readings about how AI is changing academia — particularly mathematics, statistics, machine learning, and engineering. Here, focusing primarily on graduate research and education, he describes key questions that departments and universities need to think about, and how they can best work with AI going forward.
Q: What is changing in research, and why is it happening so quickly?
A: Mathematics illustrates how quickly AI capabilities are advancing. Last year, a model reached gold-medal level at the...
Copyright of this story solely belongs to news.mit.edu. To see the full text click HERE
