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econ.GN2026
Learning from an Unknown DGP: Experimental Evidence on Belief Updating with AI Recommendations
Matthew Kovach, Daniel Martin, Gerelt Tserenjigmid
We use a controlled experiment to study how beliefs are updated after receiving qualitative information (AI recommendations) from an unknown data-generating process (DGP). Across 6…
econ.GN2025
Misaligned by Design: Incentive Failures in Machine Learning
David Autor, Andrew Caplin, Daniel Martin +1
The cost of error in many high-stakes settings is asymmetric: misdiagnosing pneumonia when absent is an inconvenience, but failing to detect it when present can be life-threatening…
econ.GN2025
Testing Capacity-Constrained Learning
Andrew Caplin, Daniel Martin, Philip Marx +2
We introduce the first general test of capacity-constrained learning models. Cognitive economic models of this type share the common feature that constraints on perception are exog…