Predictive AI is increasingly used to guide decisions on agents. I show that even a bias-neutral predictive AI can … potentially amplify exogenous (human) bias in settings where the predictive AI represents a cost-adjusted precision gain to … increase in aggregate discrimination is possible if this effect dominates. Not accounting for this mechanism may result in AI …

understand bias and discrimination as mechanisms and potential points of intervention. …Most definitions of algorithmic bias and fairness encode decisionmaker interests, such as profits, rather than the … interests of disadvantaged groups (e.g., racial minorities): Bias is defined as a deviation from profit maximization. Future …

amplifying bias, attempts to detect and prevent such biases have intensified. An approach that has received considerable … contributions to understanding and addressing issues around bias in computer systems, outlines the current debates on algorithmic … bias and fairness in machine learning, and discusses how such debates could profit from VSD-derived insights and …

native population nor immigration flows. In the case of AI, we determine an increase in the wage gap as well as the …, AI leads to a significant inflow of immigrants. Policymakers should devote special attention to the migration population …