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Who Should Stop Unethical A.I.?

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Re: Who Should Stop Unethical A.I.?

#61

Earlier quoted context omitted.

In US society/laws, it seems that the vast majority of blame is ascribed to the entity who last causes an event to occur. So the blame in the following sequence: 1. Miner mines iron 2. Manufacturer makes knife 3. Retailer sells knife to person A 4. Person A kills person B with the knife I think most people living in the US would be ok with the general idea that person A should be held responsible for killing person B…

Not so fast. Virtually everywhere there are concepts like "accessory to murder", "criminal organization" and many more.

Definitely. Also my example was fairly simplistic.

However, to my knowledge, neither of "accessory to murder" and "criminal organization" have been applied to the manufacturer of a legal-to-own object.

This comment is meant to make an analogy between the manufacturer of a legal-to-own object and the publishers of an ML algorithm.

Re: Who Should Stop Unethical A.I.?

#62

The real problem with AI ethics and fairness is that nobody actually listens to ethicists or philosophers. Nobody takes the subject seriously. It’s just a hype vehicle to cram in whatever social justice outrage du jour that some liberal source wants to push as an agenda. I say this as a liberal who is sympathetic to most of those issues, but finds their representation in AI ethics or fairness debates to be ignorant a…

Could you cite what part of the paper you're talking about? Since it's now public[0], it's fairly easy to verify what you're talking about. The word "woke" doesn't appear in the paper.

If I'm interpreting your argument correctly, I think you're criticizing either section 4.1 Size Doesn’t Guarantee Diversity, or section 4.2 Static Data/Changing Social Views. But your criticisms don't track with either of those sections. 4.2 seems the best fit (since they discuss keeping models up to date with modes of communication). The claim made in the paper seems to be that an LM trained today will fail to keep up with shifts in language (and these can happen quickly, in months, not years in many contexts). This is true whether the context is "woke vocabulary" whatever that means, reclaimed slurs (such as "queer"), or memetic slang/shibboleths ("kek" or "do you listen to girl in red"). I don't see anyone saying that language models or designers are required to agree with "woke vocabulary". The closest I can come is the authors suggesting that models which fail to stay up to date with shifts in vocabulary (including, I guess, woke vocabulary) will be less effective. That seems trivially true. Can you clarify?

[0]: https://faculty.washington.edu/ebender/papers/Stochastic_Par...

Re: Who Should Stop Unethical A.I.?

#63
post #46

Earlier quoted context omitted.

I'm not OP, but I don't think the claim was specifically that models themselves are biased. It is that models are inherently biased because the data they are based on is biased. That might sound the same, but there is a nuanced difference. If you are able to strip the bias from the data, the models will work fine. The problem is the data and not the models.

At what point does this stop being AI's fault and start being an accurate observation of things that are society's fault? Let's say you have a racially-neutral observation of lower income, maybe disability status or a criminal rap in the past. That looks like a bad bet for a loan regardless of color, it just so happens that our society's created a statistical imbalance in those metrics.

> At what point does this stop being AI's fault and start being an accurate observation of things that are society's fault?

AI shouldn't take the blame. Blame the folks collecting biased data, or those making biased decisions encoded in the data. The data is known to be tainted. Blame those using that data to train models, and sell/rent/apply those models for profit. Blame the researchers who know, or should know, better but make breathless claims about how their AI can be used without regard for the impact if people follow their advice

Re: Who Should Stop Unethical A.I.?

#64

> At artificial-intelligence conferences, researchers are increasingly alarmed by what they see. This is because there is an increasing proportion of people that is not going to the conferences for the science and instead to try to hijack the conferences with their own agenda. It's of course their right to make a fuss, but it would be nice to still have venues that are focused on the science and not the other politic…

You are trying to re-frame ethics as "agenda" and "political stuff." Enough said.

Ethics is the shield of idiots and churches.

Re: Who Should Stop Unethical A.I.?

#65
post #8

>Alex Hanna, the Google ethicist who criticized the Neurips speech-to-face paper, told me, over the phone, that she had four objections to the project. First, ...Second, ....Third, ....Finally, the system could be used for surveillance. I'm curious about this. As I understand it, an ethicist is objecting to the publication of software that could be used for surveillance. If that is correct, does it follow that this e…

1. How does one distinguish between software that can be used for surveillance and software that cannot? What is the killer app for the technology under discussion? If the killer app is improving camera filters to make more vibrant pictures but it can also be used for surveillance then you do not worry about it being used for surveillance. If however the killer app is surveillance then you worry about it. As a genera…

From the paper's abstract:

>In this paper, we study the task of reconstructing a facial image of a person from a short audio recording of that person speaking.

I can imagine a potentially interesting application of this that has nothing to do with privacy violation or surveillance (that I can see):

What if we could take an audio recording of an ancestor or someone else of interest, for whom we have no pictures, and output a probable face for that person? Sounds interesting and potentially "killer" to me. Maybe I'm wrong.

Re: Who Should Stop Unethical A.I.?

#66

The more I think about this, the more inclined I am to see this kind of article as a kind of "fake news" that is deliberately (or with willful negligence) misrepresenting facts. I need to be clear that I don't believe in censorship and it's fine if this is what the author wants to write, but it should be called out how irresponsible it is. On a place like HN, the audience is generally able to read such things critica…

Let me guess, it was saying I dont like censorship that set people off :)

Re: Who Should Stop Unethical A.I.?

#67
post #63

Earlier quoted context omitted.

At what point does this stop being AI's fault and start being an accurate observation of things that are society's fault? Let's say you have a racially-neutral observation of lower income, maybe disability status or a criminal rap in the past. That looks like a bad bet for a loan regardless of color, it just so happens that our society's created a statistical imbalance in those metrics.

> At what point does this stop being AI's fault and start being an accurate observation of things that are society's fault? AI shouldn't take the blame. Blame the folks collecting biased data, or those making biased decisions encoded in the data. The data is known to be tainted. Blame those using that data to train models, and sell/rent/apply those models for profit. Blame the researchers who know, or should know, be…

But the underlying situation is biased. The data could be both accurate and unfair.

Is it, just don't do data, same interest rate for everyone, no denials and amortize defaults across higher rates for lower-risk borrowers?

You'd need a law, the first bank to do that would be crushed by other banks that can attract the lower-risk borrowers with lower rates.

Re: Who Should Stop Unethical A.I.?

#68

I find Alex’s comments pretty openly inflammatory and sensationalist. It’s a pretty far throw from a system that predicts a face from a voice to transphobia.

I agree to the extent that labeling something as "transphobic" is a stretch when the researchers probably didn't even think about transgender people at all. Maybe "transinconsiderate" would be a more accurate label? Or Alex could have just said "this research reinforces cultural stereotypes and prejudices in ways that could cause problems for people like me sometime down the line".

On the other hand, I think it's legitimate to criticize research that has many obvious bad applications and few obvious good applications.

(Perhaps an important factor is why this research was being done in the first place? Did they build a "reconstruct what a person probably looks like from their voice" just to see if they could, or did they have some real application in mind? For instance, suppose they were working with a group of oceanographers who wanted a system to infer the characteristics of orcas from their whalesong as part of a project to track their migration habits, and the researchers decided to test their system on people first because it's easier and less expensive. If a project was undertaken for a good reason, but it opens the door to a lot of bad applications as an unintentional side-effect, should the researchers get a free pass on the latter?)

Re: Who Should Stop Unethical A.I.?

#69
post #36
post #25

Earlier quoted context omitted.

What types of models and what types of bias are you referring to?

Any model created using biased data will inherently mirror that bias unless there are active steps made to counteract this effect. For example, basically any financial evaluations of US citizens will likely result in an inherent bias against Black people due to institutional biases such as redlining that have long lasting socioeconomic and demographic repercussions. This might mean that something as simple as incorpo…

In many unbalanced situations you simply can't have an unbiased decision that's fair across all measures, no matter if the decision is done by a model, a human or a deity; you have to trade off between different types of unfairness. Equality of opportunity for individuals will result in unequal results for groups; equality of outcomes requires unequal opportunities if the historical circumstances have resulted in socioeconomic unequalities.

In your financial evaluations example, many biases and disadvantages would remain even if you solely reduce the decision to relevant financial facts for a specific individual, because a poorer individual with lower socioeconomic status and less opportunities actually has a higher risk of non-payment, and a disadvantaged group will have disproportionally more such individuals. Should we accept that? Should we require the other groups to subsidize their non-payment? Both options are unfair in some aspect and fair in another, you can't have your cake and eat it too, and it's not the fault of the model you use - the only difference with a human is that they can better hide the factors they use, lie about the influences (perhaps also lie to themselves) and rationalize/invent factors to justify their decision.

For this topic, perhaps this talk "AI Ethics, Impossibility Theorems and Tradeoffs" https://www.youtube.com/watch?v=Zn7oWIhFffs or its slides https://www.chrisstucchio.com/pubs/slides/crunchconf_2018/sl... might be interesting for you, it has some flaws but is a decent exploration of the problem space.

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