Environments That Make Us Smart: Ecological Rationality

Collective recognition can be more accurate than Wimbledon experts' ratings (e.g., correct on 72% of men's 2003 matches vs. 69%).

“More surprisingly, their collective recognition can be even more accurate (e.g., correct on 72% of men's 2003 matches) than the Wimbledon experts' ratings (69%).”

• cites Gigerenzer, 2007Not checked yet

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Humans rely on multiple simple decision heuristics, not one general-purpose calculus of rationality.

“But now there is an impressive body of experimental evidence showing that people often make decisions in an entirely different way: Humans rely on multiple simple decision heuristics, not one general-purpose calculus of rationality (e.g., Bro ¨der & Schiffer, 2003;Gigerenzer, 2007).”

• cites Bro ¨der & Schiffer, 2003Not checked yet

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• cites Gigerenzer, 2007Not checked yet

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• AssumptionRests on an assumption: Real human minds are computationally bounded.

The recognition heuristic will only perform well in environments where the biggest objects are frequently discussed and hence likely to be recognized.

“But the recognition heuristic will only perform so well in environments that it is suited to-namely, those where the ''biggest'' objects (like the biggest winners in sports) are frequently discussed and hence likely to be recognized.”

Tennis novices make predictions in line with the recognition heuristic about 90% of the time.

“Tennis novices make predictions in line with this heuristic often (90% of the time).”

• cites Gigerenzer, 2007Not checked yet

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Most Americans and French rely on the same simple default heuristic: if there is a default choice, stick with it.

“Rather, most Americans and French seem to rely on the same simple default heuristic: ''If there's a default choice, stick with it.''”

• cites Johnson & Goldstein, 2003Not checked yet

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Individuals can be led to use particular heuristics in inappropriate environments and consequently make errors.

“Individuals can certainly be led to use particular heuristics in inappropriate environments and consequently make errors, as the heuristicsand-biases research tradition emphasized (Kahneman, Slovic, & Tversky, 1982).”

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When environments are moderately unpredictable and learning samples are small, Take The Best tends to make inferences as accurately as or better than multiple regression, neural networks, and other machine-learning models.

“When environments are moderately unpredictable and learning samples are small, as with many social and economic situations, Take The Best also tends to make inferences as accurately as or better than multiple regression, neural networks, and other machine-learning models (Chater, Oaksford, Nakisa, & Redington, 2003).”

• cites Chater, Oaksford, Nakisa, & Redington, 2003Not checked yet

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The interaction between a heuristic and its social, institutional, or physical environment explains behavior.

“It is the interaction between a heuristic and its social, institutional, or physical environment that explains behavior.”

Many environments, such as consumer choice or mate choice, are characterized by a J-shaped distribution of cue importance, where the most influential cue is considerably more important than the second, and so on.

“But many environments, such as those of consumer choice or mate choice, are characterized instead by a distribution of cue importance that falls off rapidly (a ''J-shaped'' distribution), so that the most influential cue is considerably more important than the second, which is considerably more important than the third, and so on.”

Environment structure, in the form of useful patterns of available information in the world, can be exploited by heuristics in the head to produce adaptive behavior.

“We build on the foundations from Darwin, Brunswik, Simon, and others to create a framework for understanding how environment structure-in the form of useful patterns of available information in the world-can be exploited by heuristics in the head to produce adaptive behavior (Gigerenzer, Todd, & the ABC Research Group, 1999;Todd, Gigerenzer, & the ABC Research Group, in press).”

• cites Gigerenzer, Todd, & the ABC Research Group, 1999Not checked yet

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• cites Todd, Gigerenzer, & the ABC Research Group, in pressNot checked yet

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In J-shaped environments, Take The Best can outperform the weighted additive model, particularly when generalizing to new decisions.

“In such environments, Take The Best can outperform the weighted additive model, particularly when generalizing to new decisions (Gigerenzer et al., 1999;Hogarth & Karelaia, 2006).”

• cites Gigerenzer et al., 1999Not checked yet

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• cites Hogarth & Karelaia, 2006Not checked yet

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Changing the legal default should be more effective than pro-donor information campaigns at increasing organ donation.

“This adaptive view has policy consequences: It explains why pro-donor information campaigns have had only limited success and indicates that changing the legal default should be more effective.”

• AssumptionRests on an assumption: Pro-donor information campaigns have had only limited success.

Few people rely on name recognition when they know that they have heard of a city for a reason that is uncorrelated with its size.

“For instance, few people rely on name recognition when they know that they have heard of a city (e.g., Chernobyl) for a reason that is uncorrelated with its size.”

• cites Gigerenzer, 2007Not checked yet

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Humans and other animals searching for resources that occur in patches do best using incremental or decremental rules, depending on whether patches have widely varying or roughly equal numbers of resources.

“And humans and other animals searching for resources that occur in patches (such as fruits on bushes or information on Web sites) do best using incremental or decremental rules, which increase or decrease the tendency to stay in a patch with each resource item found, depending on whether patches have widely varying or roughly equal numbers of resources (Hutchinson & Gigerenzer, 2005).”

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Patterns of recognition knowledge gained by individuals via social exchange can be exploited by the recognition heuristic to decide which of two items is larger or more successful.

“Patterns of recognition knowledge gained by individuals via social exchange can be successfully exploited by the recognition heuristic mentioned earlier (Gigerenzer et al., 1999) to decide which of two items is larger (e.g., cities) or more successful (e.g., tennis players or stocks), and such recognition patterns are also given prominence in group decision making (Reimer & Katsikopoulos, 2004).”

• cites Gigerenzer et al., 1999Not checked yet

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• cites Reimer & Katsikopoulos, 2004Not checked yet

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Environment structures are specifically created by cultures or institutions to influence the behavior of others.

“Environment structures are also specifically created by cultures or institutions to influence the behavior of others, as in the organ-donor example earlier.”

People can use satisficing heuristics to make ecologically rational decisions about other people as potential mates based on the sequential pattern of people they have previously encountered.

“We can use satisficing heuristics to make ecologically rational decisions about other people as potential mates based on the sequential pattern of people we have previously encountered (Gigerenzer et al., 1999).”

• cites Gigerenzer et al., 1999Not checked yet

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People tend to be ecologically rational themselves, often using simple decision heuristics that confer speed and accuracy in particular environments.

“Furthermore, because the human mind has been shaped by the adaptive processes of evolution and learning, we predict that people will tend to be ecologically rational themselves, often using simple decision heuristics that confer the twin advantages of speed and accuracy in particular environments.”

• AssumptionRests on an assumption: Real human minds are computationally bounded.

In challenging environments with high variability, low predictability, and little opportunity for learning, good decisions may be made more often by simple mechanisms than by complex ones.

“Thus, in challenging environments with high variability, low predictability, and little opportunity for learning, good decisions may nonetheless be made more often by simple mechanisms than by complex ones.”

This structure can be exploited by heuristics for choice or estimation that rely on the fact that most objects are not big.

“This structure can in turn be exploited by heuristics for choice or estimation that, for instance, rely on the fact that most objects are not big (Gigerenzer et al., 1999).”

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People can use the majority rule and other heuristics to make group decisions about people as potential employees based on the distribution of information within the group.

“We can use the majority rule (which simplifies computation by just tallying yes/ no judgments rather than, for instance, weighting them according to importance of different judges) and other heuristics to make group decisions about people as potential employees, based on the distribution of information within our group (Todd et al., in press).”

• cites Todd et al., in pressNot checked yet

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Drivers may choose a parking space using a particular satisficing heuristic that creates a pattern of taken and still-available spots that serves as the environment for future drivers to search through with their own heuristic.

“Similarly, drivers may choose a parking space using a particular satisficing heuristic that creates a pattern of taken and still-available spots that serves as the environment for future drivers to search through with their own heuristic (Hutchinson & Gigerenzer, 2005).”

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Individuals, through the effects of their own choices, shape the environment in which they and others must make further choices, creating the possibility of a coadapting loop between mind and world.

“In these cases, individuals are, through the effects of their own choices, essentially shaping the environment in which they and others must make further choices, creating the possibility of a coadapting loop between mind and world.”

Such an emergent distribution can be seen in many domains where people make active choices, such as buying books or visiting Web sites.

“Such an emergent distribution can be seen in many domains where people make active choices, such as buying books (leading to a few bestsellers and many languishing titles) or visiting Web sites (a few Yahoos versus countless low-traffic personal Web pages).”

People are sensitive to the distribution of cues in an environment, appropriately applying either Take The Best or a weighted additive mechanism depending on which will be more accurate.

“Moreover, people are sensitive to the distribution of cues in an environment, appropriately applying either Take The Best or a weighted additive mechanism, depending on which will be more accurate (Rieskamp & Otto, 2006).”

• cites Rieskamp & Otto, 2006Not checked yet

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People use satisficing heuristics that set aspiration levels for searching through sequences of options when it is difficult to return to previously seen options and to tell what options lie ahead.

“People use satisficing heuristics that set aspiration levels (for instance, a minimal acceptable job salary or a maximal acceptable house-buying price) for searching through sequences of options when it is difficult to return to previously seen options and to tell what options lie ahead (as on job, housing, or even mating markets- Gigerenzer et al., 1999).”

• cites Gigerenzer et al., 1999Not checked yet

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Traffic laws determining intersection right-of-way are designed hierarchically to match one-reason decision mechanisms.

“Sometimes this is felicitous, as when traffic laws determining intersection right-of-way are designed hierarchically to match our one-reason decision mechanisms (Todd et al., in press).”

• cites Todd et al., in pressNot checked yet

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