Human Trust in Artificial Intelligence: Review of Empirical Research

By Ella Glikson, Anita Williams Woolley. The Academy of Management Annals, 2020

2,160 citations recorded by the source corpus.

Artificial intelligence (AI) characterizes a new generation of technologies capable of interacting with the environment and aiming to simulate human intelligence. The success of integrating AI into...

Subfields: Artificial Intelligence, Information Systems, Safety Research

View Paper: https://www.semanticscholar.org/paper/ef0c62ff070a476f216fe478cc190c773f12a1f6

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Citations in the corpus

A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective (2022, methodology): “…project a perception of physical and psychological closeness to the user (Glikson & Woolley, 2020), (3) social presence of the AI-enabled system (Glikson & Woolley, 2020; Morana et al., 2020; Weitz et al., 2021), (4) integrity of the AI-enabled system (i.e., repeatedly satisfactory task…”
A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective (2021, positive): “However, the latter type, which involves automatic processes and algorithms that can autonomously perform all tasks without human intervention, is still an area under development (Glikson & Woolley, 2020).”
Pandemics: Implications for research and practice in industrial and organizational psychology (2020, background): “In addition to the technical development, however, user experience and trust in such information systems are key for a successful and rapid integration (e.g., Glikson & Woolley, 2020; Thielsch, Meeßen, & Hertel, 2018), with concrete implication for a usercentric design.”
Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2020, background): “…humans and autonomous agents will need to interact in team- like structures to achieve objectives (e.g., Cooke et al., 2016; Cuevas et al., 2007; Glikson & Woolley, 2020; Larson & DeChurch, 2020; McNeese & McNeese, 2020; Myers et al., 2019; Seeber et al., 2020; Wynne & Lyons, 2018), and we…”
The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers (2025, positive): “We measure participants’ overall trust in GenAI, which has been shown to correlate with users’ attitudes and adoption of the use of the technologies [43, 76].”
AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap (2023, background): “This tendency to overtrust based on the LLM’s own explanations may be further amplified by the common anthropomorphization [62] and presentation of LLMs as “intelligent” systems.”
Artificial intelligence and innovation management: A review, framework, and research agenda✰ (2021, background): “Depending on the design of the AI system, humans can sometimes trust the technology either too much or too little, which creates friction in using the AI system (Glikson and Woolley, 2020).”
Trust in AI and Its Role in the Acceptance of AI Technologies (2022, background): “Glikson and Woolley (2020) identified factors that predict cognitive and emotional trust in AI.”
Mind the Gap! Choice Independence in Using Multilingual LLMs for Persuasive Co-Writing Tasks in Different Languages (2025, unknown): “First, human-AI interaction research highlights the critical role of first impressions and initial exposures for user behaviour and trust [38, 86, 103, 112].”