# What Makes a Dark Pattern... Dark? Design Attributes, Normative Considerations, and Measurement Methods

arXiv: https://arxiv.org/abs/2101.04843 · HTML: https://mlsanity.com/paper/2101.04843/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jan 2021.

## Built on by (most cited first, 15 of 15)

- [DarkBench: Benchmarking Dark Patterns in Large Language Models](https://mlsanity.com/paper/2503.10728/) (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)
- [LLM Whisperer: An Inconspicuous Attack to Bias LLM Responses](https://mlsanity.com/paper/2406.04755/) (2024)
- [Characterizing and modeling harms from interactions with design patterns in AI interfaces](https://mlsanity.com/paper/2404.11370/) (2024)
- [Beneficent Intelligence: A Capability Approach to Modeling Benefit, Assistance, and Associated Moral Failures through AI Systems](https://mlsanity.com/paper/2308.00868/) (2023)
- [SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agents](https://mlsanity.com/paper/2510.11035/) (2025)
- [Automated detection of dark patterns in cookie banners: how to do it poorly and why it is hard to do it any other way](https://mlsanity.com/paper/2204.11836/) (2022)
- [Dark patterns in e-commerce: a dataset and its baseline evaluations](https://mlsanity.com/paper/2211.06543/) (2022)
- [Affective Context Amplifies Sycophancy in LLM Responses](https://mlsanity.com/paper/2608.21242/) (2026)
- [Imposing AI: Deceptive design patterns against sustainability](https://mlsanity.com/paper/2508.08672/) (2025)
- [Against Algorithmic Exploitation of Human Vulnerabilities](https://mlsanity.com/paper/2301.04993/) (2023)
- [Why is the User Interface a Dark Pattern? : Explainable Auto-Detection and its Analysis](https://mlsanity.com/paper/2401.04119/) (2023)
- [Deception at Scale: Deceptive Designs in 1K LLM-Generated Ecommerce Components](https://mlsanity.com/paper/2502.13499/) (2025)
- [Playing Games with My Heart: An Evaluation of AI Companion Apps](https://mlsanity.com/paper/2605.08093/) (2026)
- [LLM-Based Intelligent Notification Composition: From Static Personalization to Context-Aware Persuasive Messaging](https://mlsanity.com/paper/2605.16264/) (2026)

## Abstract (arXiv)

There is a rapidly growing literature on dark patterns, user interface designs -- typically related to shopping or privacy -- that researchers deem problematic. Recent work has been predominantly descriptive, documenting and categorizing objectionable user interfaces. These contributions have been invaluable in highlighting specific designs for researchers and policymakers. But the current literature lacks a conceptual foundation: What makes a user interface a dark pattern? Why are certain designs problematic for users or society? We review recent work on dark patterns and demonstrate that the literature does not reflect a singular concern or consistent definition, but rather, a set of thematically related considerations. Drawing from scholarship in psychology, economics, ethics, philosophy, and law, we articulate a set of normative perspectives for analyzing dark patterns and their effects on individuals and society. We then show how future research on dark patterns can go beyond subjective criticism of user interface designs and apply empirical methods grounded in normative perspectives.