Simple Heuristics That Make Us Smart

Simple Heuristics That Make Us Smart invites readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional views of rationality tend to see decision makers as possessing superhuman powers of reason, limitless knowledge, and all of eternity in which to ponder choices. To understand decisions in the real world, we need a different, more psychologically plausible notion of rationality, and this book provides it. It is about fast and frugal heuristics--simple rules for making decisions when time is pressing and deep thought an unaffordable luxury. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality. But when and how can such fast and frugal heuristics work? Can judgments based simply on one good reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? Simple Heuristics explores these questions, developing computational models of heuristics and testing them through experiments and analyses. It shows how fast and frugal heuristics can produce adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop out rates, and playing the stock market. As an interdisciplinary work that is both useful and engaging, this book will appeal to a wide audience. It is ideal for researchers in cognitive psychology, evolutionary psychology, and cognitive science, as well as in economics and artificial intelligence. It will also inspire anyone interested in simply making good decisions.

Fast and frugal heuristics - simple rules for making decisions with realistic mental resources - are presented here. Developing computational models of heuristics shows how fast and frugal heuristics can yield adaptive decisions.

In a complex and uncertain world, humans and animals make decisions under the constraints of limited knowledge, resources, and time. Yet models of rational decision making in economics, cognitive science, biology, and other fields largely ignore these real constraints and instead assume agents with perfect information and unlimited time. About forty years ago, Herbert Simon challenged this view with his notion of "bounded rationality." Today, bounded rationality has become a fashionable term used for disparate views of reasoning. This book promotes bounded rationality as the key to understanding how real people make decisions. Using the concept of an "adaptive toolbox," a repertoire of fast and frugal rules for decision making under uncertainty, it attempts to impose more order and coherence on the idea of bounded rationality. The contributors view bounded rationality neither as optimization under constraints nor as the study of people's reasoning fallacies. The strategies in the adaptive toolbox dispense with optimization and, for the most part, with calculations of probabilities and utilities. The book extends the concept of bounded rationality from cognitive tools to emotions; it analyzes social norms, imitation, and other cultural tools as rational strategies; and it shows how smart heuristics can exploit the structure of environments.

This title invites readers to discover the simple heuristics that people use to navigate the complexities and surprises of environments populated with others.

Where do new ideas come from? What is social intelligence? Why do social scientists perform mindless statistical rituals? This vital book is about rethinking rationality as adaptive thinking: to understand how minds cope with their environments, both ecological and social. Gerd Gigerenzer proposes and illustrates a bold new research program that investigates the psychology of rationality, introducing the concepts of ecological, bounded, and social rationality. His path-breaking collection takes research on thinking, social intelligence, creativity, and decision-making out of an ethereal world where the laws of logic and probability reign, and places it into our real world of human behavior and interaction. Adaptive Thinking is accessibly written for general readers with an interest in psychology, cognitive science, economics, sociology, philosophy, artificial intelligence, and animal behavior. It also teaches a practical audience, such as physicians, AIDS counselors, and experts in criminal law, how to understand and communicate uncertainties and risks.

Decision Science and Technology is a compilation of chapters written in honor of a remarkable man, Ward Edwards. Among Ward's many contributions are two significant accomplishments, either of which would have been enough for a very distinguished career. First, Ward is the founder of behavioral decision theory. This interdisciplinary discipline addresses the question of how people actually confront decisions, as opposed to the question of how they should make decisions. Second, Ward laid the groundwork for sound normative systems by noticing which tasks humans can do well and which tasks computers should perform. This volume, organized into five parts, reflects those accomplishments and more. The book is divided into four sections: `Behavioral Decision Theory' examines theoretical descriptions and empirical findings about human decision making. `Decision Analysis' examines topics in decision analysis.`Decision in Society' explores issues in societal decision making. The final section, `Historical Notes', provides some historical perspectives on the development of the decision theory. Within these sections, major, multi-disciplinary scholars in decision theory have written chapters exploring some very bold themes in the field, as an examination of the book's contents will show. The main reason for the health of the Decision Analysis field is its close links between theory and applications that have characterized it over the years. In this volume, the chapters by Barron and Barrett; Fishburn; Fryback; Keeney; Moreno, Pericchi, and Kadane; Howard; Phillips; Slovic and Gregory; Winkler; and, above all, von Winterfeldt focus on those links. Decision science originally developed out of concern with real decision problems; and applied work, such as is represented in this volume, will help the field to remain strong.

Gerd Gigerenzer's influential work examines the rationality of individuals not from the perspective of logic or probability, but from the point of view of adaptation to the real world of human behavior and interaction with the environment. Seen from this perspective, human behavior is more rational than it might otherwise appear. This work is extremely influential and has spawned an entire research program. This volume (which follows on a previous collection, Adaptive Thinking, also published by OUP) collects his most recent articles, looking at how people use "fast and frugal heuristics" to calculate probability and risk and make decisions. It includes a newly writen, substantial introduction, and the articles have been revised and updated where appropriate. This volume should appeal, like the earlier volumes, to a broad mixture of cognitive psychologists, philosophers, economists, and others who study decision making.

How to stay in charge in a world populated by algorithms that beat us in chess, find us romantic partners, and tell us to “turn right in 500 yards.” Doomsday prophets of technology predict that robots will take over the world, leaving humans behind in the dust. Tech industry boosters think replacing people with software might make the world a better place—while tech industry critics warn darkly about surveillance capitalism. Despite their differing views of the future, they all agree: machines will soon do everything better than humans. In How to Stay Smart in a Smart World, Gerd Gigerenzer shows why that’s not true, and tells us how we can stay in charge in a world populated by algorithms. Machines powered by artificial intelligence are good at some things (playing chess), but not others (life-and-death decisions, or anything involving uncertainty). Gigerenzer explains why algorithms often fail at finding us romantic partners (love is not chess), why self-driving cars fall prey to the Russian Tank Fallacy, and how judges and police rely increasingly on nontransparent “black box” algorithms to predict whether a criminal defendant will reoffend or show up in court. He invokes Black Mirror, considers the privacy paradox (people want privacy, but give their data away), and explains that social media get us hooked by programming intermittent reinforcement in the form of the “like” button. We shouldn’t trust smart technology unconditionally, Gigerenzer tells us, but we shouldn’t fear it unthinkingly, either.