A Practical Guide to Updating Beliefs From Contradictory Evidence

We often make high stakes choices based on complex information that we have no way to verify. Careful Bayesian reasoning—assessing every reason why a claim could be false or misleading—is not feasible, so we necessarily act on faith: we trust certain sources and treat claims as if they were direct observations of payoff relevant events. This creates a challenge when trusted sources conflict: Practically speaking, is there a principled way to update beliefs in response to contradictory claims? I propose a model of belief formation along with several updating axioms. An impossibility theorem shows there is no obvious best answer, while a representation theorem delineates the boundary of what is possible.

• Publication year

  2021

• Venue

  Econometrica

• Publication date

  Unknown publication date

• Fields of study

  Philosophy, Computer Science

• Identifiers
  DOI 10.3982/ECTA17378
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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