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
The integrative review: updated methodology
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“Why Should I Trust You?”: Explaining the Predictions of Any Classifier
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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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Behavioral Study of obedience.
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Flagged first, then by citations
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
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Sorted by citations
Items 101–118 of 118
Information-signaling in pre-trial bargaining: An experiment
Guerra, A., Lavie, S., & Turrini, E. (2025) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2025.107343
The Guardian in the Machine:Designing Ethical Behavior in Cobotic ServicesPreprint
Mou, Y., Zhang, S., & Ding, Z. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6000583
Algorithm Perception When Using Threat Intelligence in Vulnerability Risk Assessment
van Gerwen, S., Papotti, A., Tuma, K., & Massacci, F. (2026) · Risk Analysis · doi:10.1111/risa.70178 · Cited by 1
“Research shows that workload, complexity of the decision, complexity of the decision domain, and cognitive strain influence the extent to which decision makers rely on automated advice (Chugunova and Sele 2022 , Kaufmann et al. 2023 ).”
Liu, H., Wang, Q.-H., & Wei, Z. (2026) · Current Psychology · doi:10.1007/s12144-026-09204-4
Engel, C., Grossmann, M. R. P., & Ockenfels, A. (2025) · Experimental Economics · doi:10.1017/eec.2025.10038
Jünke, A., & Möller, F. (2026) · Electronic Markets · doi:10.1007/s12525-026-00891-2
Cho, J., Han, E., & Spassova, G. (2026) · European Journal of Marketing · doi:10.1108/ejm-03-2024-0198
Teaming Up with Artificial Agents in Non-routine Analytical Tasks
Cominelli, L., Galatolo, F., Giannetti, C., Dell'orletta, F., Ciaccio, C., Chapkovski, P., & Venturi, G. (2026) · ACM Trans. Hum. Robot Interact. · doi:10.1145/3816428
“In particular, we use three different types of artificial agents (see Table 1 and Figure 2), each representing a different level of embodiment:”
Zhu, Y., & Zhou, R. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2687131
Exploiting the machine: Human cooperation with artificial agents in prisoner's dilemma
Barreda‐Tarrazona, I., Jaramillo-Gutiérrez, A., Pavan, M., & Sabater‐Grande, G. (2026) · Journal of Economic Psychology · doi:10.1016/j.joep.2026.102925
Bai, L., Han, D. Y., & Hennessy, S. (2026) · Research Square · doi:10.21203/rs.3.rs-10309041/v1
Kärgel, K. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1869979
“…the conditions under which ODR dynamics unfold: where surveillance is intensified and sanction risks are reshaped, the threshold at which organizational members consider experiences safe to articulate may shift accordingly (Anjelia et al., 2025; Chugunova and Sele, 2022; Xavier and Korunka, 2025).”
Zhang, Q., Ding, Y., & Hu, X. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.101290
Coordination and leadership: The impact of artificial intelligence
Bigoni, M., & Paoli, D. (2026) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2026.107767
Exploring trust in Artificial Intelligence (AI) systems: Insights from a repeated trust game
Jayasekara, D. N., Deng, R., Ho, J. Q., & Prissé, B. (2026) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2026.102658 · Cited by 2
Rethinking Cognitive Bias in Human–AI Cognitive Systems: A Structured Conceptual Mapping Review
Jacomuzzi, A. C., Alioto, B. P., & Magni, S. (2026) · Behavioral Sciences · doi:10.3390/bs16101829
“The interdisciplinary review by Chugunova and Sele (2022) is the only one reporting reduced emotional response, whereas the economic psychology review by Rodriguez-Fernandez (2025) is the only one reporting preference reshaping (together with “bias amplification”).”
InfluentialStudying trust in AI in sports: An interdisciplinary primer
Wunderlich, F., & Reis, M. (2026) · Psychology of sport and exercise · doi:10.1016/j.psychsport.2026.103274 · Cited by 1
A System Dynamics Approach to Modeling Trust Dynamics in Conversational AI
Berberena, T., Ðula, I., & Wirzberger, M. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-40108-3_9
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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