The Emergence of Social Norms and Conventions

Hawkins, Robert X. D.; Goodman, Noah D.; Goldstone, Robert L.

doi:10.1016/j.tics.2018.11.003

Cited by 99 publications

(83 citation statements)

References 99 publications

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“…If expectations motivate behavior, then these expectations may begin as historical accidents, but, as they propagate across generations (DeDeo, 2017;Hawkins et al, 2019), they may become cemented into the foundation of social reality (i.e. expectations shared across many people).…”

Section: Implications For Culture Norms and Evolutionary Psychologymentioning

confidence: 99%

“…That is, one individual conforms to another's expectation (or to expectations shared collectively; i.e. norms; Bicchieri, 2006;Hawkins et al, 2019) to "gain or maintain acceptance" (Kelley, 1952, p. 411), to avoid "social sanctions" (Cialdini et al, 1990, p. 1015; see also, Schwartz, 1977, p. 225), to achieve "social success" (Paluck et al, 2016, p. 556), or to "signal belongingness to a group" (Toelch & Dolan, 2015, p. 580).…”

Section: Introductionmentioning

confidence: 99%

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The sense of should: A biologically-based framework for modeling social pressure

Theriault

Young

Barrett

2021

Physics of Life Reviews

107

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We develop a model of social pressure, based on the metabolic costs of information. • We propose that conformity regulates the predictability of social environments. • We suggest that the experience of obligation stems from anticipated uncertainty. • We integrate disparate theories of mental inference with an embodied account. • We discuss the emergent consequences of others' expectations motivating behavior.

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Section: Implications For Culture Norms and Evolutionary Psychologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The sense of should: A biologically-based framework for modeling social pressure

Theriault

Young

Barrett

2021

Physics of Life Reviews

107

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“…However, about 15 years ago, this social preference hypothesis came under critique because some experiments showed that two particular forms of unselfish behaviour, altruistic punishment and altruism (see table 1 for these definitions), could not be entirely explained by preferences defined solely over monetary outcomes. In 2010, building on work on the effect of social norms on people's behaviour [15][16][17][18][19][20][21][22][23][24], Bicchieri & Chavez [25] proposed to explain altruistic punishment assuming that people have preferences for following their 'personal norms' (what they personally believe to be the right thing to do) beyond the monetary consequences that this action brings about. Subsequently, Krupka & Weber [26] proposed to explain altruism using 'injunctive norms' (what one believes others would approve/ disapprove); however, in their analysis, they did not consider a potential role of personal norms.…”

Section: Introductionmentioning

confidence: 99%

Mathematical foundations of moral preferences

Capraro

Perc

2021

J. R. Soc. Interface.

219

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One-shot anonymous unselfishness in economic games is commonly explained by social preferences, which assume that people care about the monetary pay-offs of others. However, during the last 10 years, research has shown that different types of unselfish behaviour, including cooperation, altruism, truth-telling, altruistic punishment and trustworthiness are in fact better explained by preferences for following one's own personal norms—internal standards about what is right or wrong in a given situation. Beyond better organizing various forms of unselfish behaviour, this moral preference hypothesis has recently also been used to increase charitable donations, simply by means of interventions that make the morality of an action salient. Here we review experimental and theoretical work dedicated to this rapidly growing field of research, and in doing so we outline mathematical foundations for moral preferences that can be used in future models to better understand selfless human actions and to adjust policies accordingly. These foundations can also be used by artificial intelligence to better navigate the complex landscape of human morality.

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“…Critically, each object appears as the target multiple times in the trial sequence, allowing the experimenter to examine how referring expressions change as the director and matcher accumulate shared experience. To the extent that the director and matcher converge on an accurate system of stable referring expressions, and these referring expressions differ from the ones that were initially produced, it may be claimed that ad hoc conventions or pacts have formed within the dyad (Hawkins, Goodman, & Goldstone, 2019).…”

Section: Introductionmentioning

confidence: 99%

Characterizing the Dynamics of Learning in Repeated Reference Games

Hawkins¹,

Frank²,

Goodman

2020

Cognitive Science

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The language we use over the course of conversation changes as we establish common ground and learn what our partner finds meaningful. Here we draw upon recent advances in natural language processing to provide a finer‐grained characterization of the dynamics of this learning process. We release an open corpus (>15,000 utterances) of extended dyadic interactions in a classic repeated reference game task where pairs of participants had to coordinate on how to refer to initially difficult‐to‐describe tangram stimuli. We find that different pairs discover a wide variety of idiosyncratic but efficient and stable solutions to the problem of reference. Furthermore, these conventions are shaped by the communicative context: words that are more discriminative in the initial context (i.e., that are used for one target more than others) are more likely to persist through the final repetition. Finally, we find systematic structure in how a speaker's referring expressions become more efficient over time: Syntactic units drop out in clusters following positive feedback from the listener, eventually leaving short labels containing open‐class parts of speech. These findings provide a higher resolution look at the quantitative dynamics of ad hoc convention formation and support further development of computational models of learning in communication.

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The Emergence of Social Norms and Conventions

Cited by 99 publications

References 99 publications

The sense of should: A biologically-based framework for modeling social pressure

The sense of should: A biologically-based framework for modeling social pressure

Mathematical foundations of moral preferences

Characterizing the Dynamics of Learning in Repeated Reference Games

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