They can entrench prejudice from "summary" of Weapons of Math Destruction by Cathy O'Neil
When algorithms are designed with biased data or flawed assumptions, they can reinforce and perpetuate existing prejudices. This is because these algorithms rely on historical data to make predictions about the future, and if that data is tainted by discrimination, the algorithm will simply learn and replicate those biases. This can lead to a vicious cycle where biased outcomes are fed back into the system, further entrenching prejudice. For example, in the criminal justice system, algorithms that predict recidivism rates may use factors like zip code or family history, which can be proxies for race or socioeconomic status. This means that individuals from marginalized communities are more likely to be classified as high risk, leading to harsher sentencing or increased surveillance. As a result, these communities are disproportionately impacted by the criminal ju...
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