To be fair, the article is not about the firing. In any case, the two researchers who got fired did more harm to Google than good. Internally no one cares they left. AI etichs is an esoteric academic research field.
I'm in the research community and I think you're significantly underetsimating the effect of firing Gebru and Mitchell. Machine learning is the hottest research area in computer science and ethics of ML is possibly its hottest subfield. And people pay attention to employers' actions. I think Microsoft Research is still feeling reputation effects from closing down its Silicon Valley lab 10 years ago with no warning. It sent a message to everyone who worked there that they had no job security, and plenty left for academia. The research community is not going to forget about Google's actions here nor, for the most part, will it view Google very favorably.
I think you're very wrong. Yes, there's hype around ML etichs. Trends in ML come and go. Do you see any VC investing in etichs in ML startups? As I said, it's an esoteric academic field.
How do you even compare between the two? MSR closed an entire lab out of the blue of some great researchers who didn't do anything wrong. Here you have two employees going against their company and shitting on it publicly. The only researchers who will not want to work at Google after this saga are the ones Google better off without.
> Do you see any VC investing in etichs in ML startups?
Perhaps you should pay less attention to VCs and more attention to governments and academic institutions, who for example in Canada are investing 10s of millions of dollars into AI ethics/FATE/AI for good research.
Sometimes, the point isn't just to make money, it's to actually improve humanity.
The point is not just making money. The point is solving real world problems. AI ethics focus on esoteric problems that don't solve any real world problems. AI ethics research has very little impact if at all on real issues.
Systemic discrimination is indeed a real world problem. That's exactly the problem. AI ethics doesn't help solving systemic discrimination for the simple reason that AI is not causing systemic discrimination.
AI systems are trained on data. There's an abundance of English data which is why systems are often biased to work better on English. Similarly, an image recognition system might be biased if you don't provide it with data representing all demographics. There's nothing new about this and you don't need AI ethics research to solve these issue.
Focusing on AI ethics thinking it has impact on systemic discrimination, instead of focusing on real issues that cause systemic discrimination, is my main issue with all of this.
why on earth should i care any more or less about systemic racism just because some charlie tells me it's unethical? Inventing ethics for machines helps cure exactly nothing. Only that i may be deemed by a machine to be an inferior human and less worthy than a "superior" being. Pushing technology that enforces your ideology is a horrible idea.
So, could you tell me for example, what this relatively often cited paper solves or where it's actually applied to solve a real world problem? https://openreview.net/forum?id=Sy2fzU9gl
I don't know this paper but it doesn't matter. I didn't say only ethics in AI research doesn't solve real world problems. It's a research field mostly for academia not industry IMHO. Obv many ethics researchers would disagree with me on this and that's OK. Partly because they would rather have the option to work at Google with FAANG salary vs a middle tier university in the middle of nowhere.
You seem to have an already strongly formed opinion on the topic, and it seems it would be very hard for people to have you even acknowledge that they may have valuable diverging views.
Starting from that point, what do you expect from a discussion? What kind of information would lead you to think again about the situation?
In terms of attracting AI researchers, think of this:
Gebru has very publicly got into fights with Yann LeCunn and now with Jeff Dean. If you are building AI, who would you rather build your team around, Dean/LeCunn or Gebru? If you are an AI researcher, do you want a join a team where one of the team members is in the habit of aggressively accusing other researchers of racism? Would you be worried that your research might fall within their crosshairs for some reason or another? For example, if you are working on natural language research, and your model ends up doing better with Indo-European languages versus those from other families, do you want to be accused of propagating racist power structures on Twitter?
Is this really true? I don't see ethics in ML papers getting the same attention in major conferences as theoretical or experimental breakthroughs in deep / reinforcement learning.
Don't get me wrong, ethics could be hot outside the ML academia, but I very much doubt it's something majority of grad students in ML are dying to get into.
i guess you are right that potential employees will consider this behaviour in their calculations. for the most part by adjusting their salary demands with an additional "risk adjustment bonus". as the FAANG can easily swallow that additional cost and are still incredibly attractive i doubt there will be a big effect besides loosing some value-oriented people. i doubt this will make a difference numbers-wise. nonetheless i applaud employees sharing their view of a companies inner workings for us others to have more information to make an informed decision themselves - yeah transparency
More importantly it has no connection to the bottom line, which is why Google management doesn't seem particularly concerned with disquiet in that research group, as long as it doesn't spread to the rest of the company.
Google and other companies should regard rigorous research and discussion about AI ethics as long-term protection of their bottom lines. If they start launching products and selling services that are found to unfairly favor or disfavor certain groups of people, they will be vulnerable to lawsuits, government regulation, and damage to their reputations.
One of the core issues in AI ethics, really the core issue currently, is that any product you launch or service you run will be found by some subset of the population to unfairly favor certain groups of people. No amount of research will allow Google to build a model so neutral everyone has to agree with it, because people want different things and have different ideas and assumptions about what's fair. As they found in 2019 with their AI ethics board, even basic ideas like "let's listen to everyone" are subject to this dilemma, because some groups feel that it's unfair to listen to other groups.
I think it is important to shift AI ethics to become more of an investment but that requires more tooling to evaluate AI ethics problems and the business risks.
This may not change end of year results, but this kind of research is what gives Google a credible voice when it comes to shaping public discourse and influencing legislative process, for instance.
But when you write something like this, do you also understand that their actual research is widely considered to be of a high quality and very important? So if you agree that ethics is important, would you leave them off a top 10 list (and who would you put on)?