Computer engineers at the world’s largest companies and universities are using machines to scan through tomes of written material. The goal? Teach these machines the gift of language. Do that, some even claim, and computers will be able to mimic the human brain.
But this impressive compute capability comes with real costs, including perpetuating racism and causing significant environmental damage, according to a new paper, “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” The paper is being presented Wednesday, March 10 at the ACM Conference on Fairness, Accountability and Transparency (ACM FAccT).
This is the first exhaustive review of the literature surrounding the risks that come with rapid growth of language-learning technologies, said Emily M. Bender, a University of Washington professor of linguistics and a lead author of the paper along with Timnit Gebru, a well-known AI researcher.
“The question we’re asking is what are the possible dangers of this approach and the answers that we’re giving involve surveying literature across a broad range of fields and pulling them together,” said Bender, who is the UW Howard and Frances Nostrand Endowed Professor.
Read more at University of Washington
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