Social Dynamics of AI Adoption

Leonardo Bursztyn, Alex Imas, Rafael Jiménez-Durán, Aaron Leonard and Christopher Roth

No 34488, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Anxiety about falling behind can drive people to embrace emerging technologies with uncertain consequences. We study how social forces shape demand for AI-based learning tools early in the education pipeline. In incentivized experiments with parents—key gatekeepers for children’s AI adoption—we elicit their demand for unrestricted AI tools for teenagers’ education. Parental demand rises with the share of other teenagers using the technology, with social forces increasing willingness to pay for AI by more than 60%. Providing information about potentially adverse effects of unstructured AI use negatively shifts beliefs about the merits of AI, but does not change individual demand. Instead, this information increases parents’ preference for banning AI in schools. Follow-up experiments show that social information has little effect on beliefs about AI quality, perceived skill priorities, or support for bans, suggesting that effects operate through social pressure rather than social learning. Our evidence highlights social pressure driving individual technology adoption despite widespread support for restricting its use.

JEL-codes: D83 D91 I20 O33 (search for similar items in EconPapers)
Date: 2025-11
New Economics Papers: this item is included in nep-ain, nep-exp, nep-hrm, nep-soc and nep-tid
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