mlsanityData to 7 Oct 2026

Generative Confidants: How do People Experience Trust in Emotional Support from Generative AI?

arXiv 2601.16656 ↗First posted 23 Jan 2026cs.HC cs.AI cs.CYcited by 0

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Abstract (arXiv)

People are increasingly turning to generative AI (e.g., ChatGPT, Gemini, Copilot) for emotional support and companionship. While trust is likely to play a central role in enabling these informal and unsupervised interactions, we still lack an understanding of how people develop and experience it in this context. Seeking to fill this gap, we recruited 24 frequent users of generative AI for emotional support and conducted a qualitative study consisting of diary entries about interactions, transcripts of chats with AI, and in-depth interviews. Our results suggest important novel drivers of trust in this context: familiarity emerging from personalisation, nuanced mental models of generative AI, and awareness of people's control over conversations. Notably, generative AI's homogeneous use of personalised, positive, and persuasive language appears to promote some of these trust-building factors. However, this also seems to discourage other trust-related behaviours, such as remembering that generative AI is a machine trained to converse in human language. We present implications for future research that are likely to become critical as the use of generative AI for emotional support increasingly overlaps with therapeutic work.

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References · 18

  1. 2023Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignmentcited by 394
  2. 2024Foundational Challenges in Assuring Alignment and Safety of Large Language Modelscited by 193
  3. 2023Sociotechnical Safety Evaluation of Generative AI Systemscited by 154
  4. 2023Understanding the Benefits and Challenges of Using Large Language Model-based Conversational Agents for Mental Well-being Supportcited by 75
  5. 2025Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providerscited by 67
  6. 2025Investigating Affective Use and Emotional Well-being on ChatGPTcited by 36
  7. 2025Customizing Emotional Support: How Do Individuals Construct and Interact With LLM-Powered Chatbotscited by 25
  8. 2024The Typing Cure: Experiences with Large Language Model Chatbots for Mental Health Supportcited by 23
  9. 2024Evaluating the Experience of LGBTQ+ People Using Large Language Model Based Chatbots for Mental Health Supportcited by 14
  10. 2024Large Language Model for Mental Health: A Systematic Reviewcited by 14
  11. 2022Textwash -- automated open-source text anonymisationcited by 10
  12. 2021Exploring Interactions Between Trust, Anthropomorphism, and Relationship Development in Voice Assistantscited by 9
6 more
  1. 2023Truth Machines: Synthesizing Veracity in AI Language Modelscited by 8
  2. 2023Twenty-Four Years of Empirical Research on Trust in AI: A Bibliometric Review of Trends, Overlooked Issues, and Future Directionscited by 6
  3. 2024Healthcare Voice AI Assistants: Factors Influencing Trust and Intention to Usecited by 6
  4. 2024Language Models as Critical Thinking Tools: A Case Study of Philosopherscited by 6
  5. 2025Understanding Attitudes and Trust of Generative AI Chatbots for Social Anxiety Supportcited by 5
  6. 2025Why it is worth making an effort with GenAIcited by 2

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