Misaligned by Design: Incentive Failures in Machine Learning PDF
November 2025 - R&R, Review of Economic Studies
Experiments show aligning AI training with users’ goals can weaken learning and yield worse decisions than post-training adjustments.
Papers & Replication Files
Working Papers
Learning from an Unknown DGP: Experimental Evidence on Belief Updating with AI Recommendations PDF
July 2026
We experimentally study belief updating from AI recommendations when the data-generating process is unknown.
Human Responses to AI Oversight: Evidence from Centre Court PDF
June 2026
Using tennis data, we find that AI review improves umpires’ accuracy on close calls and shifts errors toward less disruptive mistakes.
When an AI Judges Your Work: The Hidden Costs of Algorithmic Assessment PDF
January 2026 - R&R, Experimental Economics
In an online work experiment, we find that AI evaluation increases output but lowers quality after accounting for output quantity.
When Crowds Miss Rare Events: Prevalence Bias in Human Annotation and Machine Learning
August 2026
We run a field experiment on DiagnosUs to study the prevalence effect in AI labeling.
Due Diligence: Endogenous Information Acquisition and Offer Quality in Search and Matching PDF
August 2026
Using a search-and-matching model, we show that improving low-quality offers can discourage due diligence and leave more searchers unmatched and worse off.
No working papers match these filters.
Published Papers
Search and Satisficing PDF
American Economic Review, 2011
In laboratory choice experiments, we find that people often search sequentially and stop when an option is good enough, adjusting their stopping thresholds to the decision environment.
A Testable Theory of Imperfect Perception PDF
Economic Journal, 2015
Using revealed-preference analysis, we characterize when observed choices are consistent with Bayesian expected utility maximization without observing the decision maker’s private information.
Measuring Rationality with the Minimum Cost of Revealed Preference Violations PDF
Review of Economics and Statistics, 2016
We develop a revealed-preference measure that captures both the number and severity of choice inconsistencies and apply it to household consumption data.
- Online appendix (click on Supplementary data link).
The Dual-Process Drift Diffusion Model: Evidence from Response Times PDF
Economic Inquiry, 2016
We propose a response-time and choice model that combines dual-process models with the drift diffusion model.
Strategic Pricing with Rational Inattention to Quality PDF
Games and Economic Behavior, 2017
I study how sellers set prices when facing buyers who are rationally inattentive to product quality.
Defaults and Attention: The Drop Out Effect PDF
Revue Économique, 2017
We measure the drop out effect, where a default option is accepted with little regard for personal suitability.
What Do Consumers Learn from Regulator Ratings? Evidence from Restaurant Hygiene Quality Disclosures PDF
Journal of Economic Behavior & Organization, 2021
Using belief elicitation and informational interventions, we show that consumers misinterpret restaurant hygiene ratings and that clarifying their meaning changes beliefs and willingness to pay.
Is No News (Perceived As) Bad News? An Experimental Investigation of Information Disclosure PDF
American Economic Journal: Microeconomics, 2021 [AEJ: Micro Best Paper Award]
In laboratory disclosure experiments, we find that informed parties strategically withhold bad news and that recipients are often insufficiently skeptical when information is withheld.
Predictive Power in Behavioral Welfare Economics PDF
Journal of the European Economic Association, 2021
We empirically evaluate the predictive power of two behavioral welfare relations.
Comparison of Decisions under Unknown Experiments PDF
Journal of Political Economy, 2021
We identify when every experiment consistent with one set of decisions has a higher value of information than every experiment consistent with another set.
Complex Disclosure PDF
Management Science, 2022 [Featured Article]
In a laboratory disclosure game, we show that senders use complexity to profit from recipients’ systematic mistakes, even when truthful reporting is mandatory.
A Robust Test of Prejudice for Discrimination Experiments PDF
Management Science, 2022 [Fast Track]
We show when average outcomes in a discrimination experiment provide evidence of prejudice, regardless of learning about individuals.
Cognitive Costs and Misperceived Incentives: Evidence from the BDM Mechanism PDF
European Economic Review, 2022
We model agents as paying cognitive costs to better understand BDM incentives and find experimental evidence consistent with the model.
Perceptions and Detection of AI Use in Manuscript Preparation for Academic Journals PDF
PLoS ONE, 2024
We survey academics on AI disclosure norms and test whether AI detectors identify GPT-modified abstracts.
Rational Inattention in Games: Experimental Evidence PDF
Experimental Economics, 2024 [EE Best Paper Award]
We experimentally implement a buyer-seller game to test whether attention responds rationally to strategic incentives.
Rationalizable Learning PDF
Economic Theory, 2024
We study what an analyst can infer from choice data about what a decision maker has learned.
Modeling Machine Learning: A Cognitive Economic Approach PDF
Journal of Economic Theory, 2025
By varying a medical-image classifier’s training incentives, we find behavior consistent with costly learning rather than fixed capacity.
The ABCs of Who Benefits from Working with AI: Ability, Beliefs, and Calibration PDF
Management Science, 2026
In a controlled experiment, we find that AI assistance benefits people most when they have lower baseline ability and well-calibrated beliefs.
Harnessing Human Uncertainty to Train More Accurate and Aligned AI Systems PDF
Decision Analysis, 2026
We show that training AI on bias-corrected human probability judgments improves accuracy and alignment with expert judgments.
Improving Crowdsourcing for AI through Cognitive-Inspired Data Engineering PDF
Behavior Research Methods, 2026
In medical-image experiments, we show that correcting annotators’ judgment biases improves both labels and trained AI models.
Testing Capacity-Constrained Learning PDF
Experimental Economics, Accepted
Applying a new theoretical test to existing perceptual experiments, we find evidence that stronger incentives often expand attention beyond fixed capacity limits.
No published papers match these filters.