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With A Rush To Create Larger Language Models, Are We Beating Their Purpose

Language Models trained on large, uncurated, static datasets from Web encode hegemonic views that are harmful to marginalised populations. ....

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UPDATE: How Timnit Gebru's Exit Shook Google and the AI Industry at Tadias Magazine

March 15th, 2021
in Featured and Reviews.
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Timnit Gebru’s exit from Google s ethical AI team kickstarted a months-long crisis for the tech giant s AI division, including employee departures, a leadership shuffle, and widening distrust of the company s historically well-regarded scholarship in the larger AI community. (Getty Images)
CNN Business
How one employee’s exit shook Google and the AI industry
In September, Timnit Gebru, then co-leader of the ethical AI team at Google, sent a private message on Twitter to Emily Bender, a computational linguistics professor at the University of Washington.
“Hi Emily, I’m wondering if you’ve written something regarding ethical considerations of large language models or something you could recommend from others?” she asked, referring to a buzzy kind of artificial intelligence software trained on text from an enormous number of webpages. ....

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How one employee's exit shook Google and the AI industry

In September, Timnit Gebru, then co-leader of the ethical AI team at Google, sent a private message on Twitter to Emily Bender, a computational linguistics professor at the University of ....

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Large computer language models carry environmental, social risks

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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. ....

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Google Grapples with Ethical AI – The New Stack

When Google fired Timnit Gebru, technical co-lead of its ethical artificial intelligence team last year, amid controversy over a paper she was co-authoring with academics and other Google researchers, the company unleashed a firestorm of criticism of the bias apparently shown by its own management, its apparent defensiveness about potential flaws in the AI underpinning its core search service and even the role of corporate research in the field of artificial intelligence as a whole. Can Google get comfortable with the necessary but uncomfortable questions research has to raise?
Gebru’s paper asked some possibly uncomfortable questions about very large language models like the ones used by Google search. ....

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