There's a sense of starting small - redlining is illegal. No company wants to redline - it cuts into their profits and dings their compliance scores. So they're willing to work with us. Once we get that right, then, maybe we can start dealing with the cases where there aren't millions of dollars of funding assisting with making the tech more ethical -- and then, cases where it may actually be working against the money.
They have their proprietary algorithm to calculate a credit score, for example you almost cannot find an apartment without presenting your SCHUFA review and there is now way to know how their score is calculated (it has even been shown in the past that they use incorrect or outdated data for their calculation).
That’s the definition of a black box in my book.
Is there an analysis comparing the automated to manual approaches? I mean, people are biased, too. The models are more systematically biased, but can also be more systematically evaluated and de-biased. Which is better, the old or the imperfect new?
0: https://arxiv.org/abs/1809.07842 2: https://arxiv.org/abs/2004.07213 also has an overview of our current combative systems.
For example, there's also prevention of mass manipulation (AI learns human psychology, $BAD_ACTOR uses that to manipulates masses) and AI based profile generation of individuals with the goal of creating leverage for blackmail/extortion/whatever. Or, how would one form a controlling body of unethical usage in AI in such areas. There are quite a few aspects never mentioned in these discussions, and a search via google scholar turns up lots of the sex/gender/race papers, but none of the others (at least on the first few pages)-