Recurring suboptimal choices result in superior decision making

Abstract

In real-life situations involving risk and uncertainty, optimal policy hinges on selecting a course of action characterized by the highest expected value (i.e., future outcomes weighted by their probabilities). Nevertheless, a vast body of findings from economic and psychological studies indicate that people rarely follow this principle1–3. The attempts to make optimal decisions are impeded by the complexity of a task and the computational capabilities of decision makers, often leading to suboptimal choices4. Recent research has demonstrated that decision makers are systematically biased toward suboptimal options5. However, little is known about the nature of this bias. Here we show that recurring suboptimal choices result in superior decision making. In one simulation study and three well-powered (N = 1,046) fully-incentivized empirical studies employing a task to mimic decision making under uncertainty, we demonstrated that people who traded off their decision accuracy for the number of possible choices performed better (i.e., they earned more money) than those who made optimal decisions in terms of maximizing the expected value. Our results demonstrate that decision makers can adapt to the requirements of a decision task. They are inclined to make more suboptimal decisions, resulting in better overall performance than normatively better choices.