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Is it important for the algorithm to "do well" on the non-obvious stuff? Why not handle low-hanging fruit first, and then try progressively (heh) harder situat
by erichocean 4y ago
Is it important for the algorithm to "do well" on the non-obvious stuff?
Why not handle low-hanging fruit first, and then try progressively (heh) harder situations?
- zoover2020 4y agoIt's the risk of bias slipping into the algorithms. See news coverage on Dutch cities using algorithms to predict financial crime/fraud. Ethnic profiling quickly becomes a thing.
- dunefox 4y agoIf the dataset is unbalanced a model that predicts the majority class only can have a very high accuracy, while being useless.
- dagw 4y agoWhy not handle low-hanging fruit first Because we don't need help on the obvious stuff. Cops already know where the low level drug dealers hang out and where the prostitutes work, they don't need a computer to tell them that. Also things like 'there will probably be a shooting in this violent neighborhood sometime within the next 7 days' is completely useless information, even if correct. There is no new actionable information that can improve on the current policing situation.
- pfisherman 4y agoIt is important because otherwise it has negative utility. There is a cost associated with building, deploying, operating and maintaining it. What value is this adding if it only tells me stuff I already know?