discrimination, by reducing discretionary and judgmental decisions. As financial institutions continue to explore ML applications in …

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 … belief updating, expected victims of bias become less likely to be saved by randomness under more precise predictions. An …

discrimination is a matter of choice (e.g. sexual orientation), observed discrimination may motivated by animus, which exacerbates or … intensifies the emotional response to the object of discrimination. This paper builds on this insight based on the understanding … be the object of discrimination. A theoretical model is constructed that predicts that the choice to identify interacts …

The paper presents the economic literature on gender bias, illustrating the underpinnings in the psychology of bias and … on methods to contrast bias presenting evidence (where it exists) of their effectiveness. The second part of the paper … presents results of an experiment in revealing unconscious bias. …

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 …

While the existence of the in-group bias is a well-researched phenomenon in Economics, the established findings are of … is to shed more light on whether intergroup discrimination manifests itself differently in a loss compared to a gain …