Intelligence as Smart Heuristics

1. Intelligence as Smart Heuristics Markus Raab Gerd Gigerenzer Yi. Sangyoon

2. Intelligence as Smart Heuristics • Intelligence is thought of as an assembly of “factors,” either one(g), a few, or many. • Tool-driven metaphor (factor analysis) • Cannot describe how cognition translates into behavior. • Cognition -----(heuristics)-----Behavior

3. Heuristic • A mental device that can solve a class of problems in situations with limited knowledge and time. • Many classes of problems  Many heuristics

4. Human Intelligence ….. building blocks Cognition Behavior adaptive toolbox Smart heuristics

5. Bounded rationality • 의사결정자는 인지적 한계 때문에 문제의 단순화된 모델을 구성할 수밖에 없다. 그리고 이 단순화된 모델에 의거해서 의사결정자는 합리적으로 행위한다. • Herbert Simon(1955, 1956) • Adaptive toolbox • embodies an ecological and social view of rational behavior. (Bounded Rationality by Herbert Simon)

6. In this chapter • Examples of heuristics • Adaptive toolbox • Ecological Rationality • Building blocks • Domain-specificity of Heuristics • Social / Nonsocial Intelligence • Program Review and Future

7. Examples of Heuristics • Recognition Heuristic • If one of two objects is recognized and the other is not, then infer that the recognized object has the higher value. • Gaze Heuristic • Attending to one variable alone and ignoring all causal relevant variable • Tic-for-Tat Heuristic • Imitates the partner’s behavior

8. Adaptive toolbox • These heuristics illustrate some of the mental tools that underlie intelligent behavior, both social and nonsocial. • Darwinian metaphor for intelligence • Evolution does not follow a grand plan, but results in patchwork of solution for specific problem : domain-specific • Heuristics are not intrinsically good or bad, rational or irrational, but only relative to an environment, just as adaptations are context-bound

9. Ecological Rationality • Intelligent behavior • Bounded rationality (Herbert Simon) • Being able to act fast and on the basis of incomplete information (not need the fiction of a superintelligence) cognition environment

10. Building blocks • Search rules • Search for alternatives and cues • Stopping rules • Without explicit cost-benefit computations • Decision rules • How a decision is made after search has been stopped. • Ex) one-reason decision making

11. Domain-Specificity of Heuristics • Domain-specificity must be discussed relative to the level of analysis • Fast and frugal heuristics • No single statistical method • No optimal algorithm • A general inference machine is not feasible • Human intelligence has to achieve more than correct answers to a test, as is obvious when we come to social or emotional intelligence.

12. Social Intelligence • To discover and model the actual mechanisms the heuristics people use when dealing with others. • The framework of the adaptive toolbox provides precise models and a modular perspective that has different degrees of generality

13. Nonsocial Intelligence • Take The Best • Based on the first cue that favors one option over the other and ignores all other available information • Take The First • Limited search and quick stopping can be beneficial

14. Program Review and Future • Extended the notion of cognitive modules to lower-level system • Such as the sensory and motor domain • Neuropsychological evidence may provide further insights about possible instantiations of proposed cognitive heuristics

15. Program Review and Future • Heuristics cannot do (Shepard, 2001) • Lower cognitive processes • High-level (creative processes..) • There is substantial evidence for a heuristic that describes the discovery of new theories in the cognitive sciences, the tools-to-theories heuristic (Gigerinzer, 2000) • The adaptive toolbox provides a research agenda of how to study cognitive abilities in terms of smart heuristics.