# AI Companions Reduce Loneliness

arXiv: https://arxiv.org/abs/2407.19096 · HTML: https://mlsanity.com/paper/2407.19096/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 67 references that are in the map.
- First posted on arXiv 9 Jul 2024.

## Builds on (most cited first, 5 of 5)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [A Holistic Approach to Undesired Content Detection in the Real World](https://mlsanity.com/paper/2208.03274/) (2022)
- [Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasets](https://mlsanity.com/paper/2106.10328/) (2021)
- [How should my chatbot interact? A survey on human-chatbot interaction design](https://mlsanity.com/paper/1904.02743/) (2019)
- [Sentiment Analysis Based on Deep Learning: A Comparative Study](https://mlsanity.com/paper/2006.03541/) (2020)

## Built on by (most cited first, 28 of 28)

- [A Pragmatic View of AI Personhood](https://mlsanity.com/paper/2510.26396/) (2025)
- [Mental Health Impacts of AI Companions: Triangulating Social Media Quasi-Experiments, User Perspectives, and Relational Theory](https://mlsanity.com/paper/2509.22505/) (2025)
- [The Role of Governments in Increasing Interconnected Post-Deployment Monitoring of AI](https://mlsanity.com/paper/2410.04931/) (2024)
- [PTCBENCH: Benchmarking Contextual Stability of Personality Traits in LLM Systems](https://mlsanity.com/paper/2602.00016/) (2026)
- [Mental Models of Autonomy and Sentience Shape Reactions to AI](https://mlsanity.com/paper/2512.09085/) (2025)
- [Revisiting Trust in the Era of Generative AI: Factorial Structure and Latent Profiles](https://mlsanity.com/paper/2510.10199/) (2025)
- ["I am here for you": How relational conversational AI appeals to adolescents, especially those who are socially and emotionally vulnerable](https://mlsanity.com/paper/2512.15117/) (2025)
- [Privacy in Human-AI Romantic Relationships: Concerns, Boundaries, and Agency](https://mlsanity.com/paper/2601.16824/) (2026)
- [Regulating Artificial Intimacy: From Locks and Blocks to Relational Accountability](https://mlsanity.com/paper/2604.18893/) (2026)
- [Conceptualization, Operationalization, and Measurement of Machine Companionship: A Scoping Review](https://mlsanity.com/paper/2506.18119/) (2025)
- [The Adaptation Paradox: Agency vs. Mimicry in Companion Chatbots](https://mlsanity.com/paper/2509.12525/) (2025)
- [Making LLMs Reliable When It Matters Most: A Five-Layer Architecture for High-Stakes Decisions](https://mlsanity.com/paper/2511.07669/) (2025)
- [AI for Proactive Mental Health: A Multi-Institutional, Longitudinal, Randomized Controlled Trial](https://mlsanity.com/paper/2601.11530/) (2025)
- [Not a Silver Bullet for Loneliness: How Attachment and Age Shape Intimacy with AI Companions](https://mlsanity.com/paper/2602.12476/) (2026)
- [CharacterFlywheel: Scaling Iterative Improvement of Engaging and Steerable LLMs in Production](https://mlsanity.com/paper/2603.01973/) (2026)
- [Discourse Diversity in Multi-Turn Empathic Dialogue](https://mlsanity.com/paper/2604.11742/) (2026)
- [AICompanionBench: Benchmarking LLMs-as-Judges for AI Companion Safety](https://mlsanity.com/paper/2606.04867/) (2026)
- [Caring Without Feeling: Affective Dynamics as the Control Layer of Human-AI Agent Collaboration](https://mlsanity.com/paper/2606.18259/) (2026)
- [The Cost-Benefit of Interdisciplinarity in AI for Mental Health](https://mlsanity.com/paper/2510.18581/) (2025)
- [When Nobody Around Is Real: Exploring Public Opinions and User Experiences On the Multi-Agent AI Social Platform](https://mlsanity.com/paper/2601.18275/) (2026)
- [When Workout Buddies Are Virtual: AI Agents and Human Peers in a Longitudinal Physical Activity Study](https://mlsanity.com/paper/2602.01918/) (2026)
- [VET: A Framework for Analyzing AI Discourse](https://mlsanity.com/paper/2606.01929/) (2026)
- [Stumbling Into AI Emotional Dependence: How Routine AI Interactions Reshape Human Connection](https://mlsanity.com/paper/2606.04150/) (2026)
- [Aesthetic Perspectives in Information Systems Research: A Hermeneutic Analysis](https://mlsanity.com/paper/2606.09839/) (2026)
- [AI Companions as Hyper Attachment and Caregiving Targets](https://mlsanity.com/paper/2606.20589/) (2026)
- [Me and My Bot: What Users Talk About in AI Companion Communities on Reddit](https://mlsanity.com/paper/2608.00748/) (2026)
- [Disrupted Companionship: A Risk Assessment Framework and Cross-Platform Quantitative Analysis of Psychosocial Responses to AI Companion Disruptions](https://mlsanity.com/paper/2609.16907/) (2026)
- [AnthroDial: Benchmarking LLM Anthropomorphism in Autonomous Social Interaction](https://mlsanity.com/paper/2609.37853/) (2026)

## Abstract (arXiv)

Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications are effective at alleviating loneliness. We address this question by focusing on AI companions applications designed to provide consumers with synthetic interaction partners. Studies 1 and 2 find suggestive evidence that consumers use AI companions to alleviate loneliness, by employing a novel methodology for fine tuning large language models to detect loneliness in conversations and reviews. Study 3 finds that AI companions successfully alleviate loneliness on par only with interacting with another person, and more than other activities such watching YouTube videos. Moreover, consumers underestimate the degree to which AI companions improve their loneliness. Study 4 uses a longitudinal design and finds that an AI companion consistently reduces loneliness over the course of a week. Study 5 provides evidence that both the chatbots' performance and, especially, whether it makes users feel heard, explain reductions in loneliness. Study 6 provides an additional robustness check for the loneliness alleviating benefits of AI companions.