Trust in Human-AI Interaction: Scoping Out Models, Measures, and Methods
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Abstract (arXiv)
Trust has emerged as a key factor in people's interactions with AI-infused systems. Yet, little is known about what models of trust have been used and for what systems: robots, virtual characters, smart vehicles, decision aids, or others. Moreover, there is yet no known standard approach to measuring trust in AI. This scoping review maps out the state of affairs on trust in human-AI interaction (HAII) from the perspectives of models, measures, and methods. Findings suggest that trust is an important and multi-faceted topic of study within HAII contexts. However, most work is under-theorized and under-reported, generally not using established trust models and missing details about methods, especially Wizard of Oz. We offer several targets for systematic review work as well as a research agenda for combining the strengths and addressing the weaknesses of the current literature.
Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 2 of its 61 references that are in the map. First posted on arXiv 30 Apr 2022.
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2 of 61 references.
References · 2
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Citing papers per year: 2023: 3; 2024: 6; 2025: 1; 2026: 3.
13 papers.
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- 2024"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trustcited by 67
- 2023Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Applicationcited by 14
- 2023"AI enhances our performance, I have no doubt this one will do the same": The Placebo effect is robust to negative descriptions of AIcited by 11
- 2024Don't be Fooled: The Misinformation Effect of Explanations in Human-AI Collaborationcited by 8
- 2024An Empirical Exploration of Trust Dynamics in LLM Supply Chainscited by 5
- 2024The Interaction Layer: An Exploration for Co-Designing User-LLM Interactions in Parental Wellbeing Support Systemscited by 3
- 2023Trust and Reliance in Consensus-Based Explanations from an Anti-Misinformation Agentcited by 2
- 2024Trusting Your AI Agent Emotionally and Cognitively: Development and Validation of a Semantic Differential Scale for AI Trustcited by 2
- 2024Qualitative Approaches to Voice UXcited by 1
- 2026What Are You Doing? Effects of Intermediate Feedback from Agentic LLM In-Car Assistants During Multi-Step Processingcited by 1
- 2025Developing and Integrating Trust Modeling into Multi-Objective Reinforcement Learning for Intelligent Agricultural Managementcited by 0
- 2026A Survey on Quantitative Modeling of Trust in Online Social Networkscited by 0
- 2026Checkpoints Are Not Enough: Trust Calibration in CoSLR, a Human-AI System for Systematic Literature Reviews5 Sep 2026
- 2026A Survey on Quantitative Modeling of Trust in Online Social Networks26 Feb 2026
- 2026What Are You Doing? Effects of Intermediate Feedback from Agentic LLM In-Car Assistants During Multi-Step Processing17 Feb 2026
- 2025Developing and Integrating Trust Modeling into Multi-Objective Reinforcement Learning for Intelligent Agricultural Management16 May 2025
- 2024The Interaction Layer: An Exploration for Co-Designing User-LLM Interactions in Parental Wellbeing Support Systems2 Nov 2024
- 2024Don't be Fooled: The Misinformation Effect of Explanations in Human-AI Collaboration19 Sep 2024
- 2024Trusting Your AI Agent Emotionally and Cognitively: Development and Validation of a Semantic Differential Scale for AI Trust25 Jul 2024
- 2024An Empirical Exploration of Trust Dynamics in LLM Supply Chains25 May 2024
- 2024"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust1 May 2024
- 2024Qualitative Approaches to Voice UX23 Apr 2024
- 2023"AI enhances our performance, I have no doubt this one will do the same": The Placebo effect is robust to negative descriptions of AI28 Sep 2023
- 2023Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Application15 May 2023
1 more
- 2024"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trustcited by 67
- 2023Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Applicationcited by 14
- 2023"AI enhances our performance, I have no doubt this one will do the same": The Placebo effect is robust to negative descriptions of AIcited by 11
- 2024Don't be Fooled: The Misinformation Effect of Explanations in Human-AI Collaborationcited by 8
- 2024An Empirical Exploration of Trust Dynamics in LLM Supply Chainscited by 5
- 2024The Interaction Layer: An Exploration for Co-Designing User-LLM Interactions in Parental Wellbeing Support Systemscited by 3
- 2023Trust and Reliance in Consensus-Based Explanations from an Anti-Misinformation Agentcited by 2
- 2024Qualitative Approaches to Voice UXcited by 1
- 2026A Survey on Quantitative Modeling of Trust in Online Social Networkscited by 0
- 2026Checkpoints Are Not Enough: Trust Calibration in CoSLR, a Human-AI System for Systematic Literature Reviewscited by 0
- 2026Checkpoints Are Not Enough: Trust Calibration in CoSLR, a Human-AI System for Systematic Literature Reviews5 Sep 2026
- 2026A Survey on Quantitative Modeling of Trust in Online Social Networks26 Feb 2026
- 2024The Interaction Layer: An Exploration for Co-Designing User-LLM Interactions in Parental Wellbeing Support Systems2 Nov 2024
- 2024Don't be Fooled: The Misinformation Effect of Explanations in Human-AI Collaboration19 Sep 2024
- 2024An Empirical Exploration of Trust Dynamics in LLM Supply Chains25 May 2024
- 2024"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust1 May 2024
- 2024Qualitative Approaches to Voice UX23 Apr 2024
- 2023"AI enhances our performance, I have no doubt this one will do the same": The Placebo effect is robust to negative descriptions of AI28 Sep 2023
- 2023Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Application15 May 2023
- 2023Trust and Reliance in Consensus-Based Explanations from an Anti-Misinformation Agent22 Apr 2023