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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 …
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Discrimination is a pervasive aspect of modern society and human relations. Statistical discrimination theory suggests …, whereas statistical discrimination theory implies that better predictions can be achieved by using all available information … suggesting that statistical discrimination often results in worse predictions. By understanding when statistical discrimination …
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, we show that regret aversion (unobservable bias) significantly reduces extremeness aversion (observable bias) and … mediates the influence of cognitive regulatory focus (unobservable bias). …
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inequality. Typically, the worry is that when classification algorithms are trained on a dataset that itself reflects bias this … may reinforce bias. However, in the world of digital content many algorithms are making judgements in real time to …
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forecasting experiment, we find monetary incentives to substantially reduce and higher task complexity and risk to increase the … bias. Anchors ubiquitously reduce the forecasts' variance, while individual cognitive abilities and learning effects show …
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