Abstract
Important decisions are often based on a distributed process of information processing , from a knowledge base that is itself distributed among agents . The simplest such situation is that where a decision-maker seeks the recommendations of experts. Because experts may have vested interests in the consequences of their recommendations, decision-makers usually seek the advice of experts they trust . Trust, however, is a commodity that is usually built through repeated face time and social interaction , and thus cannot easily be built in a global world where we have immediate internet access to a vast pool of experts. In this article, we integrate findings from experimental psychology and formal tools from Artificial Intelligence to offer a preliminary roadmap for solving the problem of trust in this computer-mediated environment. We conclude the article by considering a diverse array of extended applications of such a solution.
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See for instance (Lorini and Demolombe 2008) for an analysis of the semantics of these operators, their relationships, and their correspondence with the structural conditions on the models of the logic \({\mathcal{T}\mathcal{R}\mathcal{U}\mathcal{S}\mathcal{T}}\)
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Ben-Naim, J., Bonnefon, JF., Herzig, A., Leblois, S., Lorini, E. (2017). Computer-Mediated Trust in Self-interested Expert Recommendations. In: Cowley, S., Vallée-Tourangeau, F. (eds) Cognition Beyond the Brain. Springer, Cham. https://doi.org/10.1007/978-3-319-49115-8_12
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