An Ontology of Dark Patterns Knowledge: Foundations, Definitions, and a Pathway for Shared Knowledge-Building
Open accessAbstract
Deceptive and coercive design practices are increasingly used by companies to extract profit, harvest data, and limit consumer choice. Dark patterns represent the most common contemporary amalgamation of these problematic practices, connecting designers, technologists, scholars, regulators, and legal professionals in transdisciplinary dialogue. However, a lack of universally accepted definitions across the academic, legislative, practitioner, and regulatory space has likely limited the impact that scholarship on dark patterns might have in supporting sanctions and evolved design practices. In this paper, we seek to support the development of a shared language of dark patterns, harmonizing ten existing regulatory and academic taxonomies of dark patterns and proposing a three-level ontology with standardized definitions for 64 synthesized dark pattern types across low-, meso-, and high-level patterns. We illustrate how this ontology can support translational research and regulatory action, including transdisciplinary pathways to extend our initial types through new empirical work across application and technology domains.
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The dark pattern collections offer comprehensive coverage across multiple dark pattern categories corresponding to the ontology and practitioner-identified patterns from real design contexts seen on the web.
“We chose to leverage these works as they offer comprehensive coverage across multiple dark pattern categories that directly correspond to the ontology [31] presented in Section 2.2. Furthermore, they offer practitioner-identified patterns from real design contexts seen on the web.”
From Investigating the Impact of Dark Patterns on LLM-Based Web Agents (2026) · cites this paper as [31]
Dark patterns enable companies to exploit users for monetary gain, harvest personal data, and reduce consumer autonomy.
“Broadly, dark patterns enable companies to exploit users for monetary gain, harvest personal data, and reduce consumer autonomy [31].”
From Investigating the Impact of Dark Patterns on LLM-Based Web Agents (2026) · cites this paper as [31]
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When design deceives: consumer reactions to dark patterns in quick commerce
Agrawal, S., & Narayanan, S. (2026) · Journal of Indian Business Research · doi:10.1108/jibr-05-2025-0188 · Cited by 4 · see citing works
Hostile interaction design: AI, governance, and the quest for human oversight
Foth, M. (2026) · AI & SOCIETY · doi:10.1007/s00146-026-03065-y · Cited by 1 · see citing works
Investigating the Impact of Dark Patterns on LLM-Based Web Agents
Ersoy, D., Lee, B., Shreekumar, A., Arunasalam, A., Ibrahim, M., Bianchi, A., & Berkay Celik, Z. (2026) · 2026 IEEE Symposium on Security and Privacy (SP) · doi:10.1109/sp63933.2026.00042 · Cited by 1 · see citing works
“To address these challenges, researchers have developed automated detection methods and user-centered interventions to mitigate the negative effects of dark patterns [52], [60].”
- Authors
- Gray, C. M., Santos, C. T., Bielova, N., & Mildner, T.
- Affiliations
- Indiana University Bloomington (US)
- Utrecht University (NL)
- Institut national de recherche en sciences et technologies du numérique (FR)
- University of Bremen (DE)
- Venue
- Proceedings of the CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2024-05-11
- Volume
- 1
- Pages
- 1-22
- OpenAlex
- W4396832378
- Cited by
- 121
- References
- 1
- Citations by year
- 2026: 54 · 2025: 50 · 2024: 17
- FWCI
- 38.90
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- arXiv (Cornell University) (submittedVersion, cc-by-nc-sa)
- HAL (submittedVersion, cc-by)
- arXiv (Cornell University)
- Funders
- ANR (22-PECY-0002 IPOP (Interdisciplinary Project on Privacy) project of the Cybersecurity PEPR)
- National Science Foundation (1909714)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- dark patterns, design ethics, ontology (information science), definitions, consumer choice, data harvesting, regulation, transdisciplinary research, knowledge construction
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