The DOI matches its Crossref record; 183 of the 183 references it cites were found in a registry or an index.
We and It: An interdisciplinary review of the experimental evidence on how humans interact with machines
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“When interacting with a machine, people respond less emotionally, feeling less guilt about being ungenerous (52).”
From The impact of generative artificial intelligence on socioeconomic inequalities and policy making (2024) · cites this paper as [52]
Citations
Cites
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Trust in Automation: Designing for Appropriate Reliance
Lee, J. D., & See, K. A. (2004) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/hfes.46.1.50_30392 · Cited by 6,605
The Narrative Construction of Reality
Bruner, J. (1991) · Critical Inquiry · doi:10.1086/448619 · Cited by 5,728
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Research works printed but not linked: 5
- Feier, T., Gogoll, J., & Uhl, M. (2021). Hiding behind machines: When blame is shifted to artificial agents. arXiv preprint arXiv:2101.11465. · arXiv
- Lee, 2019, Procedural justice in algorithmic fairness: Leveraging transparency and outcome control for fair algorithmic mediation, Proceedings of the ACM on Human-Computer Interaction, 3, 1
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- Tan, S., Adebayo, J., Inkpen, K., & Kamar, E. (2018). Investigating human+ machine complementarity for recidivism predictions. arXiv preprint arXiv:1808.09123. · arXiv
Cited by
Sorted by citations
The impact of generative artificial intelligence on socioeconomic inequalities and policy making
Capraro, V., Lentsch, A., Acemoglu, D., Akgun, S., Akhmedova, A., Bilancini, E., Bonnefon, J.-F., Brañas-Garza, P., Butera, L., Douglas, K. M., et al. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae191 · Cited by 371
Three Challenges for AI-Assisted Decision-Making
Steyvers, M., & Kumar, A. (2024) · Perspectives on Psychological Science · doi:10.1177/17456916231181102 · Cited by 217
“However, many potential factors associated with this framework could affect the perceived control of the decision, which could in turn influence the human’s willingness to rely on the AI (Chugunova & Sele, 2022).”
Understanding Liability Risk from Using Health Care Artificial Intelligence Tools
Mello, M. M., & Guha, N. (2024) · New England Journal of Medicine · doi:10.1056/nejmhle2308901 · Cited by 155
Liu, F., & Lee, Y.-H. (2023) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2023.103685 · Cited by 105
A new sociology of humans and machines
Tsvetkova, M., Yasseri, T., Pescetelli, N., & Werner, T. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-02001-8 · Cited by 122
“From fake social media accounts and generative artificial intelligence chatbots to trading algorithms and self-driving vehicles, robots, bots and algorithms are proliferating and permeating our communication channels, social interactions, economic transactions and transportation arteries.”
Metadata
- Authors
- Chugunova, M., & Sele, D.
- Affiliations
- Max Planck Institute for Innovation and Competition (DE)
- ETH Zurich (CH)
- Corresponding author
- Chugunova, Marina
- Venue
- Journal of Behavioral and Experimental Economics
- Publisher
- Elsevier BV
- Published
- 2022-08
- Volume
- 99
- Pages
- 101897
- ISSN
- 2214-8043 (ISSN-L)
- OpenAlex
- W4281256336
- Cited by
- 118
- References
- 183
- Citations by year
- 2026: 21 · 2025: 45 · 2024: 27 · 2023: 24
- FWCI
- 22.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Behavioral and Experimental Economics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- human-automation interaction, automated agents, trust in automation, decision-making power, algorithmic decision support, task context, performance expectations
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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