Social rationality

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In behavioural sciences, social rationality is a type of decision strategy used in social contexts, in which a set of simple rules is applied in complex and uncertain situations.

Contents

Definition

Social rationality is a form of bounded rationality applied to social contexts, where individuals make choices and predictions under uncertainty. [1] While game theory deals with well-defined situations, social rationality explicitly deals with situations in which not all alternatives, consequences, and event probabilities can be foreseen. The idea is that, similar to non-social environments, individuals rely, and should rely, on fast and frugal heuristics in order to deal with complex and genuinely uncertain social environments. [1] This emphasis on simple rules in an uncertain world contrasts with the view that the complexity of social situations requires highly sophisticated mental strategies, as has been assumed in primate research[ better source needed ] [2] and neuroscience, [3] among others.

A descriptive and normative program

Social rationality is both a descriptive program and a normative program. The descriptive program studies the repertoire of heuristics an individual or organization uses, that is, their adaptive toolbox. The normative program studies the environmental conditions to which a heuristic is adapted, that is, where it performs better than other decision strategies. This approach is called the study of the ecological rationality of social heuristics. It assumes that social heuristics are domain- and problem-specific. [4] [5]

Applications

Heuristics can be applied to social and non-social decision tasks (also called social games and games against nature), judgments, or categorizations. They can use social or non-social input. Social rationality is thus about three of the four possible combinations, excluding the case of heuristics using non-social input for non-social tasks. 'Games against nature' comprise situations where individuals face environmental uncertainty, and need to predict or outwit nature, e.g., harvest food or master hard-to-predict or unpredictable hazards. [6] 'Social games' include situations, where the decision outcome depends on the choices of others, e.g., in cooperation, competition, mate search and even in morally significant situations. [7]

Social rationality has been studied in a number of other fields than human decision-making, e.g. in evolutionary social learning, [8] and social learning in animals. [9]

Examples

Imitate-the-majority heuristic

An example for a heuristic that is not necessarily social but that requires social input is the imitate-the-majority heuristic, where in a situation of uncertainty, individuals follow the actions or choices of the majority of their peers regardless of their social status. The domain of pro-environmental behavior provides numerous illustrations for this strategy, such as littering behavior in public places, [10] the reuse of towels in hotel rooms, [11] and changes in private energy consumption in response to information about the consumption of the majority of neighbors. [12]

1/N (Equality heuristic)

Following the equality heuristic (sometimes called 1/N rule) people divide and invest their resources equally in a number of N different options. These options can be both social (e.g., time spent with children) and nonsocial entities (e.g., financial investments or natural resources). For example, many parents invest their limited resources, such as affection, time, and money (e.g., for education) equally into their offspring. [13] In highly uncertain environments with large numbers of assets and only few possibilities to learn, the equality heuristic can outperform optimizing strategies and yield better performance on various measures of success than optimal asset allocation strategies. [14]

Social heuristics

Adapted from Hertwig & Herzog, 2009. [4]

See also

Notes

  1. 1 2 Hertwig, Hoffrage, & the ABC Research Group, 2012
  2. Humphrey, 1988
  3. Seymour & Dolan, 2008
  4. 1 2 Hertwig & Herzog, 2009
  5. Gigerenzer, Todd, & the ABC Research Group, 1999
  6. Hertwig & Hoffrage, 2012
  7. Gigerenzer, 2010
  8. Morgan, Rendell, Ehn, Hoppitt, & Laland 2012
  9. Rieucau & Giraldeau, 2011
  10. Cialdini, Reno, & Kallgren 1991
  11. Goldstein, Cialdini, & Griskevicius 2008 [full citation needed]
  12. Schultz, Nolan, Cialdini, Goldstein, & Griskevicius 2007
  13. Hertwig et al., 2002 [full citation needed]
  14. DeMiguel, Garlappi, and Uppal (2009)

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Heuristics is the process by which humans use mental short cuts to arrive at decisions. Heuristics are simple strategies that humans, animals, organizations, and even machines use to quickly form judgments, make decisions, and find solutions to complex problems. Often this involves focusing on the most relevant aspects of a problem or situation to formulate a solution. While heuristic processes are used to find the answers and solutions that are most likely to work or be correct, they are not always right or the most accurate. Judgments and decisions based on heuristics are simply good enough to satisfy a pressing need in situations of uncertainty, where information is incomplete. In that sense they can differ from answers given by logic and probability.

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Heuristics are simple decision making strategies used to achieve a specific goal quickly and efficiently, and are commonly implemented in sports.

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References