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IZA Discussion Paper No. 18678
May 2026
Algorithm Aversion in Prosocial Tasks: Evidence from AI-Based Performance Evaluation
Martin Abel, Raghad S. Dawi, Tyler Lenk, Aidan Singer

How do workers respond when artificial intelligence replaces human judgment in evaluating prosocial work? Partnering with a non-profit addressing food insecurity, we recruit 1,491 U.S. volunteers to write fundraising messages and cross-randomize evaluation by humans versus AI and the presence of performance pay. AI evaluation reduces effort by 11–14 percent among volunteers with low commitment to the cause, while having no effect on those strongly aligned with the mission. Performance pay fails to mitigate these adverse effects. Workers perceive AI as less effective at identifying quality, which appears to be the primary mechanism, and as less fair and transparent than human evaluation. Introducing an AI algorithm that explicitly applies human evaluation criteria does not mitigate these negative effects, suggesting that resistance to AI evaluation reflects deeper skepticism about machines' capacity for subjective judgment.

Kommunikation
Mark Fallak
mark.fallak@liser.lu
+352 585-855-526
World of Labour
Olga Nottmeyer
olga.nottmeyer-ext@liser.lu
+352 585-855-501
Netzwerkkoordination
Christina Gathmann
christina.gathmann@liser.lu

Das IZA@LISER-Netzwerk ist eine weltweite Gemeinschaft für exzellente Forschung in der Arbeitsmarktökonomie und angrenzenden Fachgebieten. Nach dem Wechsel von Bonn wird das Netzwerk nun am Luxembourg Institute of Socio-Economic Research (LISER) koordiniert.

Über das IZA@LISER Network
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