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What Makes Us Smart

The Computational Logic of Human Cognition

Samuel J. Gershman

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Princeton University Press img Link Publisher

Sachbuch / Angewandte Psychologie

Beschreibung

How a computational framework can account for the successes and failures of human cognition

At the heart of human intelligence rests a fundamental puzzle: How are we incredibly smart and stupid at the same time? No existing machine can match the power and flexibility of human perception, language, and reasoning. Yet, we routinely commit errors that reveal the failures of our thought processes. What Makes Us Smart makes sense of this paradox by arguing that our cognitive errors are not haphazard. Rather, they are the inevitable consequences of a brain optimized for efficient inference and decision making within the constraints of time, energy, and memory—in other words, data and resource limitations. Framing human intelligence in terms of these constraints, Samuel Gershman shows how a deeper computational logic underpins the “stupid” errors of human cognition.

Embarking on a journey across psychology, neuroscience, computer science, linguistics, and economics, Gershman presents unifying principles that govern human intelligence. First, inductive bias: any system that makes inferences based on limited data must constrain its hypotheses in some way before observing data. Second, approximation bias: any system that makes inferences and decisions with limited resources must make approximations. Applying these principles to a range of computational errors made by humans, Gershman demonstrates that intelligent systems designed to meet these constraints yield characteristically human errors.

Examining how humans make intelligent and maladaptive decisions, What Makes Us Smart delves into the successes and failures of cognition.

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Schlagwörter

Human intelligence, Efficiency, Effectiveness, Ad hominem, Reinforcement learning, Anecdote, Controllability, Normative, Expected value, Ambiguity, Efficient frontier, Bayesian, Bayesian inference, Cognitive style, Conspiracy theory, Principle of rationality, Quantity, Reason, Circular reasoning, Rational agent, Probability, Strong inference, Altruism, Sophistication, Guessing, Utility, Learnability, Predictive power, Rationality, Ad hoc hypothesis, Logical extreme, Uncertainty, Cognitive flexibility, Mutual exclusivity, Likelihood function, Accuracy and precision, Observational learning, Explanation, Behavior, Efficient coding hypothesis, Positive feedback, Prediction, Lightness (philosophy), Approximation, Optimism, Hypothesis, Thought, Credibility, Perfect rationality, Optimism bias, Predictability, Theory, Efficacy, Inference, Opportunity cost, Spontaneous recovery, Inductive bias, Almost surely, Moral hazard, Predictive coding, Action potential, Confidence, Fair coin, Gimmick, Hot Hand, Motivated reasoning, Logical reasoning, Commitment device, Heuristic, Intelligent design