AI can revolutionise education but technology is not enough: human development meets cultural evolution

Muthukrishna, Michael ORCID: 0000-0002-7079-5166, Dai, Jiner, Madrid, Diana Panizo, Sabherwal, Riya, Vanoppen, Karlijn and Yao, Hanying (2025) AI can revolutionise education but technology is not enough: human development meets cultural evolution. Journal of Human Development and Capabilities. ISSN 1945-2829

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Abstract

Artificial Intelligence could dramatically boost educational outcomes and close gaps – but only if policymakers take a human-centred, systems-level approach to AI integration. Cultural evolution, the science of how beliefs, values, norms, technologies and institutions evolve over time, offers a framework for understanding the promises and pitfalls of different approaches to AI in education policy. Using this perspective and drawing on comparative evidence from Estonia’s successful “Tiger Leap” initiative and the failed “One Laptop Per Child” (OLPC) programme, we identify three missteps that derail national strategies: (1) techno-fix thinking, (2) weak infrastructure and teacher support and (3) lack of local adaptation. Uruguay’s Plan Ceibal is a notable exception to OLPC’s general failures, revealing why technology alone is not enough. We map AI’s headline promises – personalised tutoring, higher teacher productivity, smaller equity gaps – onto the specific capabilities each can expand, and we highlight three systemic risks: digital exclusion, algorithmic bias and widening inequalities. Synthesising these lessons, we propose a practical roadmap. AI will revolutionise education and enhance human development only insofar as it is embedded in human centred systems that grow everyone’s capabilities and freedom to learn, create and participate in society.

Item Type:	Article
Additional Information:	© 2025 The Author(s)
Divisions:	Psychological and Behavioural Science
Subjects:	L Education > LB Theory and practice of education H Social Sciences > H Social Sciences (General) T Technology > T Technology (General)
Date Deposited:	24 Jun 2025 07:42
Last Modified:	24 Jun 2025 07:42
URI:	http://eprintstest.lse.ac.uk/id/eprint/128541

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