Google AI Research Manager Quits After Two Ousted from Group
bloomberg.com
bloomberg.com
You can take a chance on someone and find out they need a lot more training, or you can take a chance on someone only to discover they are trying to crash the system.
It is believed that having a set of strong ethical guidelines and representation can often lead to a high functioning research team, compared to a traditional monoculture team of researchers and developers.
Happy to be proved wrong though.
There is a lot (really a lot!) of discoveries that are needed to identify and "fix" biases in DL models. The current method actually used is to test the obvious. i.e. "does our model work as well on all skin colors" which is far from being a robust and systematic method.
That's what Google actually needs and there is still a lot of fundamental research to do before getting there. Having ethics researchers writing papers on BERT generating too much CO2 is not only something an accountant could tell you, it's also not actionable as they are already trying to use zero-carbon electricity. Having researchers focus on inequalities in the US is good but it's again not actionable without the fundamental methods that need to be developed.
TLDR: Google needs researchers that are trying to solve the hard problems of the DL algorithms, not that get side-tracked by problems that are a matter of public policy.
> Gebru had co-authored a paper on the risks of very large language models, regarding their environmental and financial costs, inscrutability leading to unknown dangerous biases, inability of the models to understand the concepts underlying what they learn, and the potential for using them to deceive people.
Environmental/financial costs are pretty "woke" I guess (in that it's stupid to complain about them; they're just a fact). Maybe the deception issue is "woke" too because it's pretty much inevitable and therefore uninteresting.
But hidden biases and lack of real understanding are definitely legit problems.
In any case she was fired for not highlighting new research into solutions for biases, not for being too woke.
There's definitely more to the story than we've heard though. I generally believe the company doing the firing in these instances because they normally can't give their side of the story so everything you hear is biased towards the person that was fired. That and firing people is really hard in most civilised countries. You have to really screw up for them to resort to firing.