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.
> 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.
> 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.
> Some AI ethics researchers cherry pick on those mistakes to justify their entire research.
This is a weird statement. This is like saying police cherry pick on criminals to justify their existence.
Do you not believe in harm reduction? Don't you think some part of AI research should be dedicated to minimizing how many "AI systems will continue to make mistakes"?
Thanks for the references. I will check them out once I get a chance. I do know one of these papers and from my understanding the modeling bias is on underrepresented features or the long tail, which again can be thought as a data problem that can be solved with better data collection.
I do agree that in the real world datasets are often biased because they represent the real world... and there are indeed modeling approaches to address such issues. (e.g., designing a loss function to up/down weight of certain types of examples). There's nothing new about this, it's been known in ML for decades.
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.
>Your ideology seems to happen to be different than mine.
if you're saying i'm a racist, i'm not. Is everything that some people say are racist actually racist? No. Is racism a problem? absolutely!
The status quo, however, should be changed by people,not people with machines. Doing nothing, that involves not using obscure algorithms to force people to think a certain way is better, in my opinion. You can't call something ethical just because you think it should be; it must be argued out. Using AI to shut out some more of that argument will only create a universal standard, not necessarily the correct one.
> The status quo however should be changed by people,not people with machines
I'm not sure I understand what this means. People/companies own machines (and ML models) and use them. So shouldn't we make sure that the machines' decisions align with what people/companies _want_ them to do? (i.e. that the people's ethics align with the ML model's ethical consequences; I'm 100% sure that people who deploy "racist models" don't do it on purpose or out of malice)
> You can't call something ethical just because you think it should be; it must be argued out
On one hand this sounds like a strawman. No one thinks that something is ethical because someone randomly declared it so.
On the other hand... ethics are a human construct, and will continue to evolve as our culture evolves over decades and centuries. Shouldn't we construct ML models which are flexible in that they can align themselves with the ethics we collectively decide? We don't know how to do that yet!
> Using AI to shut out some more of that argument will only create a universal standard, not necessarily the correct one.
You seem to be under the impression that the fields of AI ethics is dedicated to brainwashing people into some particular unpopular moral philosophy. This is simply untrue. Within the field of AI ethics there is a lot of diversity of thought and disagreement on how human morals should be "encoded" so that AI can "align" with these morals. And I'm using the plural of morals because obviously there will never be a humanity-wide consensus on ethics, and if AI is to be deployed in the world it needs to reflect this diversity.
Codifying ethics perpetuates falsehood. Every single generation in history believed that the "had it" only to be denigrated as hopelessly misguided by the next generation. We are making the same mistake, only less people are killed right now, so it looks like we are more successful. Remember the Pacifism of the inter-war years? it bred fascism. The pendulum swings.
AI ethics cannot hope to remain in style for long, while they will almost certainly exist for far too long. Accepted standards of 2 years ago, are already out of date.
I'm lost for a solution.
I do think that the less AI is claimed to be ethical, the less it will be trusted, which is the best cure i can think of. Honesty is the basis of the whole of scientific inquiry, and is probably scarcer in google's ethics research department than anywhere else in the building. (programs don't run if the math's wrong, economics as well)
No, you're wrong. Ethics and morals do exist. Money exists. Ideas exist in our brain, functionally.
Are all these things _ideas_? Human creations? Sure. The universe is absolutely indifferent to us. But these _ideas_ have real-world impact, and I'm not indifferent to my own suffering.
Societies function at the scale they do right now because there is enough overlap in how I perceive the world and how another random human perceives the world so that even though we don't know each other, we can still cooperate [see e.g. 1 for great discussions on this] e.g. exchange money for goods.
> AI ethics cannot hope to remain in style for long
Again, you seem to be conflating "AI ethics" with a particular ethical stance, let's call it woke humanism, and you seem to think that the people who work on AI ethics work to enforce this belief on others. This is wrong. We're perfectly aware that humans have a variety of ethical preferences, see my previous post. Lots of people who work in "AI ethics" are definitely not woke humanists.
> Accepted standards of 2 years ago, are already out of date.
I'm not sure what you're trying to say here. Um, sure we keep finding better algorithms... no one ever, ever, ever, has claimed that their paper is the ultimate algorithm and no no one will find better. But 2 years ago, killing a random person in the street was wrong. It's still wrong today, it was wrong 2000 years ago, and it's going to stay this way for the foreseeable future.
> I'm lost for a solution
The research field of AI ethics exists because we don't know what the solution is!!! Come join us if you're so concerned.
> Honesty is the basis of the whole of scientific inquiry
If you value honesty, then you should value research that tries to make ML models "honest", by revealing how they make the predictions they do and where that fails. I don't understand your antagonism towards ML FATE (fairness accountability transparency and ethics) research
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.