dc.contributor.author | Derex, M | |
dc.contributor.author | Bonnefon, J-F | |
dc.contributor.author | Boyd, R | |
dc.contributor.author | Mesoudi, AA | |
dc.date.accessioned | 2019-03-11T13:36:07Z | |
dc.date.issued | 2019-04-01 | |
dc.description.abstract | Highly-optimized tools are common in traditional populations. Bows and arrows, dogsleds, clothing, houses, and kayaks are just a few examples of the complex, exquisitely designed tools that humans produced and used to colonize new, demanding environments. Because there is much evidence that humans’ cognitive abilities are unparalleled, many believe that such technologies resulted from our superior causal reasoning abilities alone. However, others have stressed that the high dimensionality of human technologies make them very hard to understand causally. Instead, they argue that optimized technologies emerge through the selective retention of small improvements across generations without requiring explicit understanding of how these technologies work. Here, we find experimental support for the latter view by showing that a physical artifact becomes progressively optimized across generations of social learners in the absence of explicit causal understanding. Moreover, we show that the transmission of causal models across generations has no noticeable effect on the pace of cultural accumulation. The reason is that participants do not spontaneously create multidimensional causal theories but instead mainly produce simplistic models related to a specifically salient dimension. Finally, we show that the transmission of these inaccurate theories 1) constrains exploration in subsequent generations of learners and 2) has negative downstream effects on their understanding. These results indicate that highly optimized technologies need not result from enhanced causal reasoning but instead can emerge from the accumulation of many small improvements made across generations linked by cultural transmission, and demand a focus on the cultural dynamics underlying technological change as well as individual cognition. | en_GB |
dc.description.sponsorship | European Commission | en_GB |
dc.description.sponsorship | European Union’s Horizon 2020 research and innovation programme | en_GB |
dc.identifier.citation | Published online 01 April 2019. | en_GB |
dc.identifier.doi | 10.1038/s41562-019-0567-9 | |
dc.identifier.grantnumber | 748310 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/36386 | |
dc.language.iso | en | en_GB |
dc.publisher | Nature Research | en_GB |
dc.rights.embargoreason | Under embargo until 01 October 2019 in compliance with publisher policy. | |
dc.rights | © The Author(s), under exclusive licence to Springer Nature Limited 2019. | |
dc.subject | culturally evolving technology | en_GB |
dc.subject | Highly-optimized tools | en_GB |
dc.subject | human technologies | en_GB |
dc.title | Causal understanding is not necessary for the improvement of culturally evolving technology | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2019-03-11T13:36:07Z | |
dc.identifier.issn | 2397-3374 | |
dc.description | This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this record. | en_GB |
dc.identifier.journal | Nature Human Behaviour | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
dcterms.dateAccepted | 2019-02-25 | |
exeter.funder | ::European Commission | en_GB |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2019-02-25 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2019-03-10T04:18:57Z | |
refterms.versionFCD | AM | |
refterms.panel | A | en_GB |