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Artificial Intelligence often relies on information obtained from others through crowdsourcing, federated learning, or data markets. It is crucial to ensure that this data is accurate. Over the past 20 years, a variety of incentive mechanisms have been developed that use game theory to reward the accuracy of contributed data. These techniques apply to many settings where AI uses contributed data. This survey categorizes the different techniques and their properties and shows their limits and tradeoffs. It identifies open issues and points to possible directions to address these.
Christophe Marcel Georges Galland, Valeria Vento, Sachin Suresh Verlekar, Philippe Andreas Rölli
Andreas Mortensen, David Hernandez Escobar, Léa Deillon, Alejandra Inés Slagter, Eva Luisa Vogt, Jonathan Aristya Setyadji
Thanh Trung Huynh, Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Trung-Dung Hoang