Trust in Automation
By Kevin A. Hoff, Masooda N. Bashir. 2015
2,121 citations recorded by the source corpus.
Subfields: Experimental and Cognitive Psychology, Information Systems and Management, Social Psychology, AI Ethics, Fairness & Society, Human-Computer Interaction
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Experimental and Cognitive Psychology
- James L. Szalma
- Peter A. Hancock
- Jessie Y.C. Chen
- Johannes Maria Kraus
- Wolfgang Minker
- C. Wickens
- Tyler H. Shaw
- Matthias Kraus
In Information Systems and Management
- Angelia L. Sebok
- Jessie Y.C. Chen
- Johannes Maria Kraus
- Wolfgang Minker
- C. Wickens
- Tyler H. Shaw
- Matthias Kraus
- Paul Rodway
In Social Psychology
- James L. Szalma
- Peter A. Hancock
- Tyler H. Shaw
- Richard Pak
- Jessie Y.C. Chen
- Angelia L. Sebok
- Michael J. Barnes
- Johannes Maria Kraus
In AI Ethics, Fairness & Society
- Jessie Y.C. Chen
- Johannes Maria Kraus
- Wolfgang Minker
- Tyler H. Shaw
- Matthias Kraus
- Paul Rodway
- Michael A. Nees
- Kristin E. Schaefer
In Human-Computer Interaction
- Jessie Y.C. Chen
- Johannes Maria Kraus
- Wolfgang Minker
- C. Wickens
- Tyler H. Shaw
- John R. Wilson
- Matthias Kraus
- Paul Rodway
Citations in the corpus
- Making deep neural networks right for the right scientific reasons by interacting with their explanations (2020, background): “Actually, trust lies at the foundation of major theories of interpersonal relationships in psychology [5, 6] and we argue that interaction and understandability are central to trust in learning machines.”
- Highly automated job interviews: Acceptance under the influence of stakes (2019, neutral): “More precisely, automated processes help to (a) acquire information, (b) analyze information, (c) select and decide about potential actions, and (d) implement these actions (Hoff & Bashir, 2015; Parasuraman et al., 2000).”
- Understanding Is Key: An Analysis of Factors Pertaining to Trust in a Real-World Automation System (2018, background): “Hoffman, Johnson, and Bradshaw (2013) highlight that much of the research into trust between humans and automation has involved small-world studies using simulation and college students as participants, and they caution that these results do not necessarily generalize.”
- Acceptance of Self-driving Cars (2016, background): “Trust in automation is influenced by expectations and attitudes that develop before a person uses a system (Hoff & Bashir, 2015), thus it will be important to understand acceptance before the arrival of self-driving cars on markets (see Payre et al., 2014).”
- The General Attitudes towards Artificial Intelligence Scale (GAAIS): Confirmatory Validation and Associations with Personality, Corporate Distrust, and General Trust (2022, background): “This aspect of trust has been researched for many years, not just in relation to AI, but also other types of automation (see e.g., Muir & Moray, 1996).”