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 interactio…
Read moreImportant 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.
