In a Bayesian account of knowledge, for example, I make a rough estimate of the truth of some claim—such as that you will be trustworthy under certain conditions—and then I correct my estimate, or “update,” as I obtain new evidence on you. If I take the risk of cooperating with you, I soon have some evidence on whether you are trustworthy in that single context. I might test further and further, updating until I have a good sense of your degree of trustworthiness in various contexts. I might do this—indeed, typically would do it—not necessarily to test you but rather to benefit from cooperating in new ways. Hence trust—the belief in another's trustworthiness—has to be learned, just as any other kind of knowledge must be learned.

DEFINE: Explains Bayesian updating as applied to trust — a conceptual framework for how trust is acquired incrementally rather than given wholesale. XREF: Connects to game theory and iterated cooperation models, where reputation is built through repeated interactions in prisoner's dilemma-type scenarios.

Russell Hardin, Trust and Trustworthiness, loc. 527