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Modelling dataset bias in machine-learned theories of economic decision-making

Economics

Modelling dataset bias in machine-learned theories of economic decision-making

T. Thomas, D. Straub, et al.

This exciting research by Tobias Thomas, Dominik Straub, Fabian Tatai, Megan Shene, Tümer Tosik, Kristian Kersting, and Constantin A. Rothkopf delves into dataset bias in economic decision-making theories. They reveal intriguing findings about how online data may introduce greater decision noise than laboratory studies, leading to enhanced predictions through a new probabilistic generative model.

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