Learning From Aggregated Opinion.

The capacity to leverage information from others' opinions is a hallmark of human cognition. Consequently, past research has investigated how we learn from others' testimony. Yet a distinct form of social information-aggregated opinion-increasingly guides our judgments and decisions. We investigated how people learn from such information by conducting three experiments with participants recruited online within the United States (N = 886) comparing the predictions of three computational models: a Bayesian solution to this problem that can be implemented by a simple strategy for combining proportions with prior beliefs, and two alternatives from epistemology and economics. Across all studies, we found the strongest concordance between participants' judgments and the predictions of the Bayesian model, though some participants' judgments were better captured by alternative strategies. These findings lay the groundwork for future research and show that people draw systematic inferences from aggregated opinion, often in line with a Bayesian solution.

Philosophy instruction changes views on moral controversies by decreasing reliance on intuition.

What changes people's judgments on moral issues, such as the ethics of abortion or eating meat? On some views, moral judgments result from deliberation, such that reasons and reasoning should be primary drivers of moral change. On other views, moral judgments reflect intuition, with reasons offered as post-hoc rationalizations. We test predictions of these accounts by investigating whether exposure to a moral philosophy course (vs. control courses) changes moral judgments, and if so, via what mechanism(s). In line with deliberative accounts of morality, we find that exposure to moral philosophy changes moral views. In line with intuitionist accounts, we find that the mechanism of change is reduced reliance on intuition, not increased reliance on deliberation; in fact, deliberation is related to increased confidence in judgments, not change. These findings suggest a new way to reconcile deliberative and intuitionist accounts: Exposure to reasons and evidence can change moral views, but primarily by discounting intuitions.

Deciding to be authentic: Intuition is favored over deliberation when authenticity matters.

Deliberative analysis enables us to weigh features, simulate futures, and arrive at good, tractable decisions. So why do we so often eschew deliberation, and instead rely on more intuitive, gut responses? We propose that intuition might be prescribed for some decisions because people's folk theory of decision-making accords a special role to authenticity, which is associated with intuitive choice. Five pre-registered experiments find evidence in favor of this claim. In Experiment 1 (N = 654), we show that participants prescribe intuition and deliberation as a basis for decisions differentially across domains, and that these prescriptions predict reported choice. In Experiment 2 (N = 555), we find that choosing intuitively vs. deliberately leads to different inferences concerning the decision-maker's commitment and authenticity-with only inferences about the decision-maker's authenticity showing variation across domains that matches that observed for the prescription of intuition in Experiment 1. In Experiment 3 (N = 631), we replicate our prior results and rule out plausible confounds. Finally, in Experiment 4 (N = 177) and Experiment 5 (N = 526), we find that an experimental manipulation of the importance of authenticity affects the prescribed role for intuition as well as the endorsement of expert human or algorithmic advice. These effects hold beyond previously recognized influences on intuitive vs. deliberative choice, such as computational costs, presumed reliability, objectivity, complexity, and expertise.