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Money laundering is a crime in which one takes money or goods taken through criminal activities (e.g., theft) and sends it through some process, usually a cover
by derbOac 6y ago
Money laundering is a crime in which one takes money or goods taken through criminal activities (e.g., theft) and sends it through some process, usually a cover, like a business or something, to make it appear legitimate. More generally, it refers to the process by which money or resources obtained through ethically questionable means is passed through layers of other activities so as to obscure its original source.
https://en.wikipedia.org/wiki/Money_laundering https://en.wikipedia.org/wiki/Money_laundering
So the idea is, you have some bias in some process (racial, religious, whatever). You set up some algorithm that relies on the bias to make predictions or classifications. Now you can say it's not you that's biased, it's just the algorithm. The algorithm is some process by which your bias is "made legitimate".
- bisectable 6y agoThe solution to this conundrum is to aggressively encode explicit biases into the algorithm. The only requirement is that the explicit biases favor certain demographics that are politically deemed more equal than others.
- dang 6y agoWe've banned this account and a bunch of related accounts for abusing HN and breaking the site guidelines. If you do it again we will ban your main account as well. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
- reader_mode 6y ago> You set up some algorithm that relies on the bias to make predictions or classifications. Now you can say it's not you that's biased, it's just the algorithm. It's not that you set up the algorithm to rely on the bias - ML trains on data produced by a biased system and ends up building a model containing the same biases - you don't need to "set-up" anything - if you're fine with the existing biases you can "launder" them through ML.
- derbOac 6y agoRight -- I didn't mean to imply that... I just meant that there's some predictive information in the bias the algorithm can take advantage of.