Heuristics and Biases are (Nearly) Optimal: A Fresh Programmatic Study of Heuristics and Biases in Human Decision-Making

点击翻译按钮获取中文摘要

Our decisions shape our lives: what career path to choose; how to invest; choice of partner; how to achieve happiness. Our application proposes computer simulations, math modeling, and psychology experiments to understand and explain central issues in human decision-making. The broad goal of our research program is to provide a new way of understanding heuristics and biases in human decision-making, by systematically developing a rational basis for them. Our research program challenges the widely held view that human cognition is systematically erroneous, offering instead a new and positive view of cognition by demonstrating that decision-making is nearly optimal given environmental conditions and cognitive limitations. The prevailing view is that judgment and decision-making are filled with cognitive biases and deviations from rationality, because people use fast but inaccurate (sub-optimal) heuristics. We will establish mathematically rigorous optimality guarantees for heuristics that strongly challenge this dominant view, thus offering a radically different perspective on heuristics. Our new framework complements rationality research, developing it into a richer research program by attempting to show that heuristics are nearly optimal given environmental conditions and cognitive limitations. Providing supporting evidence for this line of work, our preliminary work shows that our framework yields strong optimally guarantees for a well-known heuristic, Take-the-Best. Also, in contrast to Nobel-winning Prospect Theory and other current approaches, we present a new heuristic model of decision-making, called SbEU (Sample-based Expected Utility). Effectively combining two highly successful theories of cognition, expected utility theory and bounded optimality, SbEU uniquely simulates and thus explains a wide range of major findings in human decision-making. Notably, SbEU is the first, and so far the only, boundedly-optimal heuristic model that bridges between risky, value-based, and game-theoretic decision-making. Our research program provides a novel, unified, precise, formal explanation of several vast literatures on human decision-making. Our preliminary models will be refined, extended, and applied to more empirical findings. Novel predictions of our models will be empirically tested in new psychology experiments. Our hypothesis is that humans make decisions in a boundedly-optimal fashion: making rational decisions, subject to environmental conditions and the computational and cognitive limitations they are faced with. We expect this work to provoke a major paradigm shift in cognitive science, from a seemingly endless list of unexplained biases to a unified theory of bounded rationality. This would fundamentally change the way we currently understand human cognition, with far-reaching implications for decision sciences, policymaking, and daily-life decisions. As such, our research is of great importance for scientists and laypeople alike.