Simplicity as a Cue to Probability: Multiple Roles for Simplicity in Evaluating Explanations

Area of Science:

• Cognitive Science
• Decision Making
• Philosophy of Science

Background:

• Evaluating competing explanations is a common challenge.
• Two approaches include assessing probabilities (e.g., Bayesian inference) and considering explanation virtues like simplicity.
• The relationship between these approaches is not fully understood.

Purpose of the Study:

• To investigate how explanation simplicity relates to Bayesian inference.
• To determine if simplicity influences the inputs (priors, likelihoods) and outputs (posteriors) of Bayesian inference.
• To explore roles of simplicity beyond probability approximation.

Main Methods:

• Two studies were conducted, involving participants evaluating explanations.
• Study 1 elicited priors and likelihoods, while Study 2 provided them.
• Simplicity was manipulated or measured, and its effect on probability judgments and explanation satisfaction was assessed.

Main Results:

• Simplicity was used to infer Bayesian inference inputs (priors and likelihoods).
• Simplicity directly influenced posterior probability estimates, especially when computations were uncertain.
• Simplicity also affected explanation satisfaction, independent of probability estimation.

Conclusions:

• Simplicity serves multiple roles in approximating probabilities, particularly under uncertainty.
• The influence of simplicity extends beyond probability estimation, affecting subjective satisfaction.
• Understanding simplicity's multifaceted role is crucial for cognitive and decision-making research.