The governance & behavioral challenges of generative artificial intelligence’s hypercustomization capabilities
Generative artificial intelligence (GenAI) is changing human–machine interactions and the broader information ecosystem. Much as social media algorithms personalize online experiences, GenAI applications can align with user preferences to customize the way individuals interact with information. However, through training, fine-tuning, and prompting, GenAI applications can introduce a new level of customization: hypercustomization. By dynamically tailoring responses to an individual’s explicit and implicit preferences, hypercustomization can reinforce biases, false beliefs, or misconceptions. As a result, it can heighten significant societal challenges, such as the spread of misinformation and political and social polarization. In this article, we explore the risks associated with hypercustomization and the governance and behavioral challenges that might impede effective risk mitigation. These challenges include a lack of transparency in GenAI applications, opacity of the nature of their interactions with users, users’ overreliance on these systems, and the inefficacy of warning messages. We also provide recommendations for overcoming these challenges.
Authors
- Stefan Michael Herzog (ORCID: https://orcid.org/0000-0003-2329-6433)
- Ezequiel Lopez-Lopez (ORCID: https://orcid.org/0000-0001-8709-8044)
- Stephan Lewandowsky (ORCID: https://orcid.org/0000-0003-1655-2013)
- Levin Brinkmann (ORCID: https://orcid.org/0000-0002-1642-8744)
- Jason W. Burton (ORCID: https://orcid.org/0000-0002-6797-2299)
- Dawn Liu Holford
- Christoph M. Abels (ORCID: https://orcid.org/0000-0003-2012-5372)
Institutions
- University of Potsdam (DE)
- Copenhagen Business School (DK)
- University of Bristol (GB)
- Max Planck Institute for Human Development (DE)
Publication Details
- Journal
- Behavioral Science & Policy
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1177/23794607251347020
- Citations
- 3
- Primary Topic
- Misinformation and Its Impacts
- Type
- article
- Field-Weighted Citation Impact
- 12.60
Funders
- European Commission
- Deutsche Forschungsgemeinschaft