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In general, automated decision systems tend to inherit the biases of the human-driven process that they replace. Unfortunately, these biases start to acquire a veneer of objectivity, and become harder to inspect, or fix.
With humans at least, new generations bring change. Algorithmic bias may prove to be more entrenched than human-driven bias, due to the greater indirection and continuity brought by datasets and algorithms, as opposed to someone's judgment...
Very nice thread. Thanks.
Automated biases can exist but they can also be solved by more (unbiased) data and making sure they are not nefariously hard coded. As the more and more data is fed into decision systems, they should become less biased, not more (as suggested by AOC).
Teach an AI any given philosophy and then let it play it out to its extent to expose the flaws.
Biases in machine learning are a small issue which can be addressed with more, better data. The left would use that imprecision as grounds for rejecting the science altogether. Don't enable that ignorance by acquiescing to the spirit of the objection. The science is sound.
No, it cannot. In fact one of the hardest problems right now with machine learning is that more data has diminishing returns. When Amazon's hiring algo started biasing toward men and not merit / skill it was looking for the exactly wrong thing. The bias was inherent in approach.
@threader_app compile
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