LLM Voting: Human Choices and AI Collective Decision Making
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- Jean-François Laslier & Karine Straeten, 2016.
"Strategic voting in multi-winner elections with approval balloting: a theory for large electorates,"
Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 47(3), pages 559-587, October.
- Jean-François Laslier & Karine van Der Straeten, 2016. "Strategic voting in multi-winner elections with approval balloting: a theory for large electorates," PSE-Ecole d'économie de Paris (Postprint) halshs-01518277, HAL.
- Jean-François Laslier & Karine van Der Straeten, 2016. "Strategic Voting in Multi-Winner Elections with Approval Balloting: A Theory for Large Electorates," PSE Working Papers halshs-01304688, HAL.
- Jean-François Laslier & Karine van Der Straeten, 2016. "Strategic voting in multi-winner elections with approval balloting: a theory for large electorates," Post-Print halshs-01518277, HAL.
- Jean-François Laslier & Karine van Der Straeten, 2016. "Strategic Voting in Multi-Winner Elections with Approval Balloting: A Theory for Large Electorates," Working Papers halshs-01304688, HAL.
- John J. Horton, 2023. "Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?," NBER Working Papers 31122, National Bureau of Economic Research, Inc.
- John J. Horton, 2023. "Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?," Papers 2301.07543, arXiv.org.
- Joshua C. Yang & Carina I. Hausladen & Dominik Peters & Evangelos Pournaras & Regula Hanggli Fricker & Dirk Helbing, 2023. "Designing Digital Voting Systems for Citizens: Achieving Fairness and Legitimacy in Participatory Budgeting," Papers 2310.03501, arXiv.org, revised Mar 2024.
- Jamshid Sourati & James A. Evans, 2023. "Accelerating science with human-aware artificial intelligence," Nature Human Behaviour, Nature, vol. 7(10), pages 1682-1696, October.
- Blanco, Mariana & Engelmann, Dirk & Normann, Hans Theo, 2011.
"A within-subject analysis of other-regarding preferences,"
Games and Economic Behavior, Elsevier, vol. 72(2), pages 321-338, June.
- Blanco, Mariana & Engelmann, Dirk & Normann, Hans-Theo, 2010. "A within-subject analysis of other-regarding preferences," DICE Discussion Papers 06, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
- Edith Elkind & Piotr Faliszewski & Piotr Skowron & Arkadii Slinko, 2017. "Properties of multiwinner voting rules," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 48(3), pages 599-632, March.
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NEP fields
This paper has been announced in the following NEP Reports:- NEP-AIN-2024-03-18 (Artificial Intelligence)
- NEP-BIG-2024-03-18 (Big Data)
- NEP-CDM-2024-03-18 (Collective Decision-Making)
- NEP-CMP-2024-03-18 (Computational Economics)
- NEP-EXP-2024-03-18 (Experimental Economics)
- NEP-INV-2024-03-18 (Investment)
- NEP-POL-2024-03-18 (Positive Political Economics)
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