How Artificial Intelligence Constrains the Human Experience

Ana Valenzuela, Stefano Puntoni, Donna Hoffman, Noah Castelo, Julian De Freitas, Berkeley Dietvorst, Christian Hildebrand, Young Eun Huh, Robert Meyer, Miriam E. Sweeney, Sanaz Talaifar, Geoff Tomaino and Klaus Wertenbroch

Journal of the Association for Consumer Research, 2024, vol. 9, issue 3, 241 - 256

Abstract: Artificial intelligence (AI) and related technologies are transforming many consumption activities, powering breakthroughs that expand the human experience by enhancing human capabilities, performance, and creativity. While this explains the consumer enthusiasm and rapid adoption of these technologies, AI systems can also have the opposite effect: reducing and constraining the range of experiences that are available to consumers. This article examines the mechanisms through which AI can constrain the human experience, considering individual, interpersonal, and societal processes. Our analysis uncovers a complex interplay between the advantages of AI and its inadvertent negative repercussions, which potentially restrict human autonomy, self-identity, relational dynamics, and social behavior. In this article, we propose three different mechanisms at the core of these constraining forces: parametric reductionism, agency transference, and regulated expression. Our exploration of these mechanisms highlights the risks connected to system design and points to questions and implications for future researchers and policymakers.

Date: 2024
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://dx.doi.org/10.1086/730709 (application/pdf)
http://dx.doi.org/10.1086/730709 (text/html)
Access to the online full text or PDF requires a subscription.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ucp:jacres:doi:10.1086/730709

Access Statistics for this article

More articles in Journal of the Association for Consumer Research from University of Chicago Press
Bibliographic data for series maintained by Journals Division ().