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by BasHamer
2948 days ago
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train it. Give it examples that we consider moral and examples of what we consider immoral and have it figure it out. The solutions that the algorithms create are less complex than the data that they base the solutions on; so it should be relatively easy for it to model these solutions as data. We would have to train it on what we consider moral and immoral; that would require us to visualize the solutions in a way that a human can make the determination and provide the feedback. As far as how we get to the solution, that will probably come when there is a liability for discrimination. So lawsuits like the one mentioned. I think that mandating does not work well, it would be more appropriate to make people liable for the decisions made by amoral systems. This liability would create a demand for moral systems. |
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That's a tall order, honestly. There's a lot of things in the current dominant SV philosophy that are fine and dandy and everybody thinks they agree with everybody else about them as long as everyone carefully agrees to not sit down and actually put numbers on the terms in question ("discrimination is bad!" "I agree!"), but when it comes time to write down concrete rules and provide concrete examples ("hiring a woman is 43.2% preferable to hiring a man; hiring an African American is 23.1% preferable to hiring a Chinese person") are going to make people squirm, and everyone involved in such a project is going to do everything in their power to avoid having to deal with the result.
I bet there's a number of people reading this post right now squirming and deeply, deeply tempted to hit that reply button and start haranguing me about those numbers and how dare I even think such things, as you've been trained to find someone to blame for any occurrence of such words and I'm the only apparent candidate. But I have no attachment to the numbers themselves and I pre-emptively acquiesce to any corrections you'd care to make to them, for the sake of argument. I expect a real model would use more complicated functions of more parameters, I just used simple percentages because they fit into text easily. But any algorithm must produce some sort of result that looks like that, and once you get ten people at a table looking at any given concrete instantiation of this "morality", 9.8 of them are not going to agree it's moral.
I cite the handful of articles we've even seen in peer-reviewed science journals, sometimes linked here on HN, which discuss the discriminatory aspects of this or that current ML system, while scrupulously avoiding answering the question of what exactly a "non-discriminatory" system actually is. It's one of those things that once you see it you can't unsee it. (And given that these papers are nominally mathematical papers by nominally "real scientists", if I were a reviewer I'd "no publish" these papers until they fix that oversight, because it isn't actually that useful to point out that an existing mathematical system fails to conform to a currently-not-existing mathematical standard.)