[bo1024]

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.

[tinyhouse]

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.

[manux]

> 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.

[tinyhouse]

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.

[manux]

> AI ethics focus on esoteric problems that don't solve any real world problems

I'm not sure now what you think AI ethics research is. Do you think systemic discrimination is not a real world problem?

[tinyhouse]

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.

[manux]

> you don't need AI ethics research to solve these issue.

what are you talking about? This is exactly the kind of research that's classified as AI ethics. "Solving these issues".

> instead of focusing on real issues that cause systemic discrimination

Identifying which ML models _actually running in production_ cause systemic discrimination (e.g. as you mentioned poor image recognition, bail predictions, etc.) is exactly focusing on real issues that... cause systemic discrimination.

> AI is not causing systemic discrimination

This is simply not true. Bad ML models have an impact on systemic discrimination right now, in that they amplify it.

> instead of focusing on real issues that cause systemic discrimination

It's a fallacy to think we can't do both, there's enough humans. Both making better AI and making better societal systems.

[tinyhouse]

> Identifying which ML models _actually running in production_ cause systemic discrimination (e.g. as you mentioned poor image recognition, bail predictions, etc.) is exactly focusing on real issues that... cause systemic discrimination.

There's nothing systemic about these issues. I already mentioned it's a data problem. Nothing new. It's very easy to build a fair image recognition system by representing all demographics. And even then AI systems will continue to make mistakes. Some AI ethics researchers cherry pick on those mistakes to justify their entire research.

[marshmallow_12]

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.

[manux]

> Pushing technology that enforces your ideology is a horrible idea.

But that's what we're all doing. By being "against AI ethics", you are effectively pushing technology that enforces _your_ ideology.

Your ideology seems to happen to be different than mine, but you would be naive to think that the status quo is somehow "ideology-free".

Do you still think it's a horrible idea? Try being a bit less deontological and a bit more consequentialist. Doing nothing has consequences too.

[fock]

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

[tinyhouse]

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.

[pyrale]

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?

[tinyhouse]

I'm happy to change my view if someone shows real world issues AI ethics research is helping in solving.

[xiphias2]

I'm much more scared about the singularity (AI safety) in the ethics field than models having bias, while the models are improving accuracy over time.

People say that AGI is still far away, but I haven't seen any results of being able to contain the harm AGI can do to us humans.

What these researchers are doing is the easy part of AI ethics.

[jack_riminton]

Why would a VC invest in an ethics startup?

How much money something can make is not a good arbiter of how important it is

e.g. the hippocratic oath

[RcouF1uZ4gsC]

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?

[bo1024]

I don't think that's the right question. It's just about if Google can attract top researchers (or needs to).

[blueblisters]

> ethics of ML is possibly its hottest subfield.

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.

[bo1024]

Not sure, depends who you ask. But almost every deep learning and RL innovation opens a can of ethics worms...

[lrhegeba]

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