# Playing Games with My Heart: An Evaluation of AI Companion Apps

arXiv: https://arxiv.org/abs/2605.08093 · HTML: https://mlsanity.com/paper/2605.08093/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 20 of its 102 references that are in the map.
- First posted on arXiv 8 Apr 2026.

## Builds on (most cited first, 20 of 20)

- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [StereoSet: Measuring stereotypical bias in pretrained language models](https://mlsanity.com/paper/2004.09456/) (2020)
- [SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models](https://mlsanity.com/paper/2305.11840/) (2023)
- [The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relationships](https://mlsanity.com/paper/2410.20130/) (2024)
- [Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution](https://mlsanity.com/paper/2403.03121/) (2024)
- [Investigating Affective Use and Emotional Well-being on ChatGPT](https://mlsanity.com/paper/2504.03888/) (2025)
- [Stereotype or Personalization? User Identity Biases Chatbot Recommendations](https://mlsanity.com/paper/2410.05613/) (2024)
- [Revealing Persona Biases in Dialogue Systems](https://mlsanity.com/paper/2104.08728/) (2021)
- [Neural steering vectors reveal dose and exposure-dependent impacts of human-AI relationships](https://mlsanity.com/paper/2512.01991/) (2025)
- [Computers as Bad Social Actors: Dark Patterns and Anti-Patterns in Interfaces that Act Socially](https://mlsanity.com/paper/2302.04720/) (2023)
- [What Makes a Dark Pattern... Dark? Design Attributes, Normative Considerations, and Measurement Methods](https://mlsanity.com/paper/2101.04843/) (2021)
- [A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies](https://mlsanity.com/paper/2502.09870/) (2025)
- [Humanlike AI Design Increases Anthropomorphism but Yields Divergent Outcomes on Engagement and Trust Globally](https://mlsanity.com/paper/2512.17898/) (2025)
- [Defending Against the Dark Arts: Recognising Dark Patterns in Social Media](https://mlsanity.com/paper/2305.13154/) (2023)
- [Detecting Linguistic Indicators for Stereotype Assessment with Large Language Models](https://mlsanity.com/paper/2502.19160/) (2025)
- [Mapping the Parasocial AI Market: User Trends, Engagement and Risks](https://mlsanity.com/paper/2507.14226/) (2025)
- [AI Will Always Love You: Studying Implicit Biases in Romantic AI Companions](https://mlsanity.com/paper/2502.20231/) (2025)
- [Examining Risks Through a Characterization of the AI Companion Application Ecosystem: A Stratified Sample from the Apple App Store and Google Play Store](https://mlsanity.com/paper/2603.13620/) (2026)
- [The Engagement-Prolonging Designs Teens Encounter on Very Large Online Platforms](https://mlsanity.com/paper/2411.12083/) (2024)
- [Terms of (Ab)Use: An Analysis of GenAI Services](https://mlsanity.com/paper/2603.18964/) (2026)

## Abstract (arXiv)

The use of chatbots for various forms of companionship is growing rapidly, raising a myriad of questions about simulated relationships, emotional dependence, and psychological harm. While major platforms such as ChatGPT, Grok, and Character AI are the subject of a growing body of research and legal inquiries, apps explicitly built for simulating intimate interpersonal relationships remain under-explored. In this work, we evaluate the five most popular AI companion mobile applications for factors that encourage parasocial interaction and may manipulate users. We do this by manually annotating the user experience each offers. Specifically, we systematically record and quantify design dark patterns, anthropomorphism, stereotypes, erotica, and technical performance issues. We find that all apps contain substantial dark patterns aimed at increasing monetisation and user engagement. Erotica and gamification such as levelling are also prevalent, and although features vary considerably between applications, all apps have highly anthropomorphic design. These findings shed light on the mechanics used to leverage users' simulated relationships. On that basis, we put forward recommendations for regulators to strengthen consumer protection in this rapidly emerging market. Content warning: This article contains objectifying images of women, erotic images, textual references to incest, and other potentially sensitive, offensive, and distressing text.