chapter seven
7 From inference to choice: Howard Raiffa, Robert Schlaifer, and the Bayesian revolution
This chapter covers
- Raiffa and Schlaifer’s Applied Statistical Decision Theory (1961) and how it extended Bayesian inference into a framework for rational decision-making
- How posterior probabilities and subjective utilities combine to govern optimal decisions
- How decision trees structure and clarify choices under uncertainty
- How expected utility, opportunity loss, and value of information are used to evaluate and compare alternative actions
- Why Raiffa and Schlaifer’s framework continues to shape decision science, economics, and artificial intelligence
Two centuries after Thomas Bayes published An Essay Towards Solving a Problem in the Doctrine of Chances, the problem of reasoning under uncertainty remained incomplete. Bayes showed how evidence updates belief—how an observation changes the probability assigned to competing explanations through what is now called Bayes’ Theorem. But this framework stops at inference. It answers what is likely, not what should be done.