# An Ontology of Dark Patterns Knowledge: Foundations, Definitions, and a Pathway for Shared Knowledge-Building

arXiv: https://arxiv.org/abs/2309.09640 · HTML: https://mlsanity.com/paper/2309.09640/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Sep 2023.

## Built on by (most cited first, 14 of 14)

- [Knowledge Mechanisms in Large Language Models: A Survey and Perspective](https://mlsanity.com/paper/2407.15017/) (2024)
- [Investigating the Impact of Dark Patterns on LLM-Based Web Agents](https://mlsanity.com/paper/2510.18113/) (2025)
- [Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight](https://mlsanity.com/paper/2509.10723/) (2025)
- [SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agents](https://mlsanity.com/paper/2510.11035/) (2025)
- [Comparing Human Oversight Strategies for Computer-Use Agents](https://mlsanity.com/paper/2604.04918/) (2026)
- [Designing AI Personalities: Enhancing Human-Agent Interaction Through Thoughtful Persona Design](https://mlsanity.com/paper/2410.22744/) (2024)
- [Personas Evolved: Designing Ethical LLM-Based Conversational Agent Personalities](https://mlsanity.com/paper/2502.20513/) (2025)
- [Imposing AI: Deceptive design patterns against sustainability](https://mlsanity.com/paper/2508.08672/) (2025)
- ["I Strongly Suspect This Website Is a Scam": Benchmarking PII Leakage and Detection without Defense in Autonomous Web Agents](https://mlsanity.com/paper/2606.00497/) (2026)
- [Deception at Scale: Deceptive Designs in 1K LLM-Generated Ecommerce Components](https://mlsanity.com/paper/2502.13499/) (2025)
- [The Global Landscape of Environmental AI Regulation: From the Cost of Reasoning to a Right to Green AI](https://mlsanity.com/paper/2603.00068/) (2026)
- [On the Suitability of LLM-Driven Agents for Dark Pattern Audits](https://mlsanity.com/paper/2603.03881/) (2026)
- [TourMart: A Parametric Audit Instrument for Commission Steering in LLM Travel Agents](https://mlsanity.com/paper/2605.10440/) (2026)
- [Learning to Detect UI Principle Violations via Reinforcement Learning](https://mlsanity.com/paper/2607.20690/) (2026)

## Abstract (arXiv)

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 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 65 synthesized dark patterns types across low-, meso-, and high-level patterns. We illustrate how this ontology can support translational research and regulatory action, including pathways to extend our initial types through new empirical work and map across application domains.