Pushing for salary transparency & adjusting to be equitable --> resulted in every woman getting a raise & 3 men who had been there longest getting raises (since their pay hadn't been keeping up with market) @nancy_hawa #WSC2019Conf pic.twitter.com/9agAts4jOV
— Rachel Thomas (@math_rachel) August 16, 2019
35% of people would forgo a raise to see their bias fired. A lot of people are unhappy at work. @duretti #WSC2019Conf pic.twitter.com/HQw8nZPkch
— Rachel Thomas (@math_rachel) August 16, 2019
For anyone who's under the impression that working on machine learning projects is just training & tuning models, I'd recommend this blog post about how hard it can be to just get your hands on data in the first place! https://t.co/nGCj9xfvuC
— Rachael Tatman (@rctatman) August 15, 2019
“algorithms—and content moderators who grade the test data that teaches these algorithms how to do their job—don’t usually know the context of the comments they’re reviewing”
— Angela Bassa (@AngeBassa) August 15, 2019
Then what even is the point of the labeling exercise?! https://t.co/G7qtiMJJqV
Whiteboard coding interviews are the new college entrance exam - a separate skill, unrelated to what you’ll do afterward and uncorrelated with how well you’ll do it.
— Brandon Rohrer (@_brohrer_) August 15, 2019
Article by @GaryMarcus looks at the bigger picture of the AI research landscape. Whether you agree with him or not I think it’s worth a read. https://t.co/Lpa36bZIyb https://t.co/GeAKWQqAAi pic.twitter.com/h3tnkXQgRZ
— hardmaru (@hardmaru) August 14, 2019
Years ago I once naively asked a VC if something was a conflict of interest.
— Hilary Mason (@hmason) August 14, 2019
He looked at me and I will never forget what he said: "Hilary, if there's no conflict, there's no interest." https://t.co/QofRXGOnIY
I highly recommend following @rickwierenga's ongoing series of deep learning posts - they are an excellent overview of the key issues for deep learning practitioners.
— Jeremy Howard (@jeremyphoward) August 14, 2019
(The fact that he's only 16 years old is icing on the cake! ;) ) https://t.co/ZGPq7hjadd
{holepunch} by @_inundata makes using @mybinderteam w/ RStudio ridiculously smooth!https://t.co/I9CmeJM7Mc #rstats https://t.co/quRs2F0xoY
— Mara Averick (@dataandme) August 14, 2019
Learn how we trained BERT-Large in 53 minutes and built an 8.3 billion parameter language model based on GPT-2 in this technical blog: https://t.co/d3cAcXb5Wt
— NVIDIA AI Developer (@NVIDIAAIDev) August 14, 2019
a blog post that nicely describes not only whether she's SOTA'd (whatever that means) but also a stream of scientific process behind this work. https://t.co/gYHjJdAkSm
— Kyunghyun Cho (@kchonyc) August 14, 2019
The solution is not to stop building AI. Instead, we need public accountability and oversight of AI development, both to ensure the privacy and rights of users, and the ethical treatment of the *workers* who generate training data.
— Arvind Narayanan (@random_walker) August 13, 2019
