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Compare Acerbi: "misinformation can travel wide, far, and long, as it is designed, intentionally or unintentionally, exactly to do this, as it does not need to be constrained by reality. We are not sensitive to an abstract notion of truth, but to various cues that point to the importance of the content and which may be associated only on average with truthfulness." (CEDA 184).
For more on the commonalities and differences of these approaches, see: Sterelny (2017).
It should be said that Mercier’s characterization of reflective beliefs draws upon Sperber’s (1997) characterization of the distinction. It is also related to a charactersation of reasoning and argumentation, especially their notion of reflective conclusions, defended in their joint work (Mercier and Sperber 2017). In both, it is claimed that there are dedicated mechanisms for generating intuitive beliefs (or ‘data-base beliefs’ in the language of Sperber (1997)) and reflective beliefs. The latter are (as far as I can tell) taken to be the exclusive output of metarepresentational mechanisms (Sperber 1997passim; Mercier and Sperber 2017, 145-153). As I note below, in NBY, Mercier does provide many details of the cognitive picture behind the intuitive/reflective distinction, instead emphasizing the potential behavioral implications. But it would be fair to assume that similar adaptationist and metarepresentational assumptions are motivating his claims.
This ‘majority illusion is a phenomenon similar to the famous ‘friendship paradox’; the seemingly paradoxical claim that on average, your friends have more friends than you do (Feld 1991).
Banerjee AV (1992) A simple model of herd behavior. Q J Econ 107(3):797–817
Baumard N (2016) The Origins of Fairness: How Evolution Explains our Moral Nature. Oxford University Press, Oxford
Boyer P (2018) Minds Make Societies: How Cognition Explains the World Humans Create. Yale University Press, New Haven
Centola D, Willer R, Macy M (2005) The emperor’s dilemma: a computational model of self-enforcing norms. Am J Sociol 110(4):1009–1040
Feld SL (1991) Why Your Friends Have More Friends Than You Do. Am J Sociol 96:1464–1477
Goldberg A, Stein SK (2018) Beyond social contagion: associative diffusion and the emergence of cultural variation. Am Sociol Rev 83(5):897–932
Golub B, Jackson MO (2010) Naïve learning in social networks and the wisdom of crowds. Am Econ J Microecon 2(1):112–149
Holman B, Bruner J (2017) Experimentation by industrial selection. Philosophy Sci 84:1008–1019
Hung AA, Plott CR (2001) Information cascades: replication and an extension to majority rule and conformity-rewarding institutions. Am Econ Rev 91(5):1508–1520
Kiesling E, Günther M, Stummer C, Wakolbinger LM (2012) Agent-based simulation of innovation diffusion: a review. CEJOR 20:183–230
Lerman K, Xiaoran Y, Xin-Zeng W (2016) The “majority illusion” in social networks. PLoS ONE 11(2):e0147617
List C, Pettit P (2004) An epistemic free-riding problem? In: Catton Philip, Macdonald Graham (eds) Karl popper: critical appraisals. Routledge, London, pp 128–158
Mayo-Wilson C (2014) Reliability of testimonial norms in scientific communities. Synthese 191:55–78
Mercier H, Sperber D (2017) The Enigma of Reason. Harvard University Press, Cambridge
Mohseni A, Williams CR (2019) Truth and conformity on networks. Erkenntnis. https://doi.org/10.1007/s10670-019-00167-6
Morin O (2016) How Traditions Live and Die. Oxford University Press, Oxford
Nguyen CT (2018) Echo chambers and epistemic bubbles. Episteme. https://doi.org/10.1017/epi.2018.32
O’Connor C, Weatherall JO (2019) The misinformation age: how false beliefs spread. Yale University Press, New Haven
O’Connor C, Weatherall JO (2020) Conformity in scientific networks. Synthese. https://doi.org/10.1007/s11229-019-02520-2
Sperber D (1997) Intuitive and reflective beliefs. Mind Language 12:67–83
Sperber D (2001) Conceptual tools for a natural science of society and culture. Proc British Acad. 111:297–317
Sperber D, Clément F, Heintz C, Mascaro O, Mercier H, Origgi G, Wilson D (2010) Epistemic vigilance. Mind Lang 25:359–393
Sterelny K (2001) Explaining Culture: A Naturalistic Approach, by Dan Sperber. Mind 110:845–854
Sterelny K (2017) Cultural evolution in California and Paris. Stud History Philos Biol 62:42–50
Sterelny K (2018) Why reason? Hugo Mercier’s and Dan Sperber’s The Enigma of Reason: A New Theory of Human Understanding. Mind Lan 33:502–512
Weisberg M (2013) Simulation and Similarity. Oxford University Press, Oxford
Zollman KJS (2010) The epistemic benefit of transient diversity. Erkenntnis 72:17–35
Funding was provided by Leverhulme Trust (Grant No. ECF-2018-005), and the Isaac Newton Trust (Grant No. G101655).
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Buskell, A. Evolution, Cultural Evolution, and Epistemic Optimism. Acta Biotheor (2020). https://doi.org/10.1007/s10441-020-09384-x