We and it: an interdisciplinary review of the experimental evidence on how humans interact with machines
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
When interacting with a machine, people respond less emotionally, feeling less guilt about being ungenerous.
“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]
Cites
The integrative review: updated methodology
Whittemore, R., & Knafl, K. (2005) · Journal of Advanced Nursing · doi:10.1111/j.1365-2648.2005.03621.x · Cited by 10,241 · see citing works
“Why Should I Trust You?”: Explaining the Predictions of Any Classifier
Ribeiro, M., Singh, S., & Guestrin, C. (2016) · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations · doi:10.18653/v1/n16-3020 · Cited by 6,682 · see citing works
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 · see citing works
The Narrative Construction of Reality
Bruner, J. (1991) · Critical Inquiry · doi:10.1086/448619 · Cited by 5,728 · see citing works
The mythos of model interpretability
Lipton, Z. C. (2018) · Communications of the ACM · doi:10.1145/3233231 · Cited by 5,427 · see citing works
Behavioral Study of obedience.
Milgram, S. (1963) · The Journal of Abnormal and Social Psychology · doi:10.1037/h0040525 · Cited by 4,918 · see citing works
(1997) · Choice Reviews Online · doi:10.5860/choice.34-3702 · Cited by 4,870 · see citing works
Humans and automation: Use, misuse, disuse, abuse
Parasuraman, R., & Riley, V. (1997) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872097778543886 · Cited by 4,554 · see citing works
Machines and Mindlessness: Social Responses to Computers
Nass, C., & Moon, Y. (2000) · Journal of Social Issues · doi:10.1111/0022-4537.00153 · Cited by 4,022 · see citing works
The neural basis of economic decision-making in the Ultimatum Game.
Sanfey, A. G., Rilling, J. K., Aronson, J. A., Nystrom, L. E., & Cohen, J. D. (2003) · Science · doi:10.1126/science.1082976 · Cited by 3,375 · see citing works
An Experimental Study of Apparent Behavior
Heider, F., & Simmel, M. (1944) · The American Journal of Psychology · doi:10.2307/1416950 · Cited by 3,340 · see citing works
Algorithm aversion: People erroneously avoid algorithms after seeing them err.
Dietvorst, B. J., Simmons, J. P., & Massey, C. (2015) · Journal of Experimental Psychology: General · doi:10.1037/xge0000033 · Cited by 3,232 · see citing works
Bystander intervention in emergencies: Diffusion of responsibility.
Darley, J. M., & Latane, B. (1968) · Journal of Personality and Social Psychology · doi:10.1037/h0025589 · Cited by 3,083 · see citing works
Human trust in artificial intelligence: Review of empirical research
Glikson, E., & Woolley, A. W. (2020) · Academy of Management Annals · doi:10.5465/annals.2018.0057 · Cited by 2,921 · see citing works
Gray, H. M., Gray, K., & Wegner, D. M. (2007) · Science · doi:10.1126/science.1134475 · Cited by 2,342 · see citing works
Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
Mark, G., Fussell, S. R., Lampe, C., Schraefel, M., Hourcade, J., Appert, C., & Wigdor, D. J. (2017) · International Conference on Human Factors in Computing Systems · doi:10.1145/3025453 · Cited by 2,222 · see citing works
Clinical versus statistical prediction: A theoretical analysis and a review of the evidence.
Meehl, P. E. (1954) · University of Minnesota Press eBooks · doi:10.1037/11281-000 · Cited by 2,187 · see citing works
Algorithm appreciation: People prefer algorithmic to human judgment
Logg, J. M., Minson, J. A., & Moore, D. A. (2019) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2018.12.005 · Cited by 2,061 · see citing works
Resistance to Medical Artificial Intelligence
Longoni, C., Bonezzi, A., & Morewedge, C. K. (2019) · Journal of Consumer Research · doi:10.1093/jcr/ucz013 · Cited by 2,015 · see citing works
The Neural Basis of Mentalizing
Frith, C. D., & Frith, U. (2006) · Neuron · doi:10.1016/j.neuron.2006.05.001 · Cited by 1,855 · see citing works
Complacency and Bias in Human Use of Automation: An Attentional Integration
Parasuraman, R., & Manzey, D. H. (2010) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720810376055 · Cited by 1,710 · see citing works
The mind in the machine: Anthropomorphism increases trust in an autonomous vehicle
Waytz, A., Heafner, J., & Epley, N. (2014) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2014.01.005 · Cited by 1,439 · see citing works
Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J.-F., Breazeal, C., Crandall, J. W., Christakis, N. A., Couzin, I. D., Jackson, M. O., et al. (2019) · Nature · doi:10.1038/s41586-019-1138-y · Cited by 1,364 · see citing works
Lee, M. K. (2018) · Big Data & Society · doi:10.1177/2053951718756684 · Cited by 1,338 · see citing works
Mas, A., & Moretti, E. (2009) · American Economic Review · doi:10.1257/aer.99.1.112 · Cited by 1,280 · see citing works
Dietvorst, B. J., Simmons, J. P., & Massey, C. (2018) · Management Science · doi:10.1287/mnsc.2016.2643 · Cited by 1,230 · see citing works
Mende, M., Scott, M. L., van Doorn, J., Grewal, D., & Shanks, I. (2019) · Journal of Marketing Research · doi:10.1177/0022243718822827 · Cited by 1,197 · see citing works
Automation bias: a systematic review of frequency, effect mediators, and mitigators
Goddard, K., Roudsari, A., & Wyatt, J. C. (2012) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000089 · Cited by 1,162 · see citing works
Testing for Altruism and Social Pressure in Charitable Giving
DellaVigna, S., List, J. A., & Malmendier, U. (2012) · The Quarterly Journal of Economics · doi:10.1093/qje/qjr050 · Cited by 1,080 · see citing works
Human Decisions and Machine Predictions
Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., & Mullainathan, S. (2018) · The Quarterly Journal of Economics · doi:10.1093/qje/qjx032 · Cited by 1,040 · see citing works
Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019) · Marketing Science · doi:10.1287/mksc.2019.1192 · Cited by 1,027 · see citing works
MUIR, B. M., & MORAY, N. (1996) · Ergonomics · doi:10.1080/00140139608964474 · Cited by 993 · see citing works
A functional imaging study of cooperation in two-person reciprocal exchange
McCabe, K., Houser, D., Ryan, L., Smith, V., & Trouard, T. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.211415698 · Cited by 984 · see citing works
It's only a computer: virtual humans increase willingness to disclose
Lucas, G. M., Gratch, J., King, A., & Morency, L.-P. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.04.043 · Cited by 977 · see citing works
Feeling robots and human zombies: Mind perception and the uncanny valley
Gray, K., & Wegner, D. M. (2012) · Cognition · doi:10.1016/j.cognition.2012.06.007 · Cited by 941 · see citing works
Performance Consequences of Automation-Induced 'Complacency'
Parasuraman, R., Molloy, R., & Singh, I. L. (1993) · The International Journal of Aviation Psychology · doi:10.1207/s15327108ijap0301_1 · Cited by 875 · see citing works
(2018) · AEA Papers and Proceedings · doi:10.1257/pandp · Cited by 852 · see citing works
Proceedings of the 18th European conference on information systems (ECIS2010)
Tervonen, T., Brock, D. B., Graeff, D. P., & Hillege, H. L. (2010) · Cited by 836 · see citing works
A systematic review of algorithm aversion in augmented decision making
Burton, J. W., Stein, M., & Jensen, T. B. (2020) · Journal of Behavioral Decision Making · doi:10.1002/bdm.2155 · Cited by 814 · see citing works
Matching robot appearance and behavior to tasks to improve human-robot cooperation
Goetz, J. L., Kiesler, S. B., & Powers, A. (2004) · doi:10.1109/roman.2003.1251796 · Cited by 785 · see citing works
People are averse to machines making moral decisions.
Bigman, Y. E., & Gray, K. (2018) · Cognition · doi:10.1016/j.cognition.2018.08.003 · Cited by 738 · see citing works
Does automation bias decision-making?
SKITKA, L. J., MOSIER, K. L., & BURDICK, M. (1999) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1999.0252 · Cited by 694 · see citing works
Are Machines Gender Neutral? Gender‐Stereotypic Responses to Computers With Voices
Nass, C., Moon, Y., & Green, N. (1997) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.1997.tb00275.x · Cited by 670 · see citing works
Nass, C., Fogg, B. J., & Moon, Y. (1996) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1996.0073 · Cited by 665 · see citing works
A Virtual Reprise of the Stanley Milgram Obedience Experiments
Slater, M., Antley, A., Davison, A. R., Swapp, D., Guger, C., Barker, C., Pistrang, N., & Sanchez-Vives, M. V. (2006) · PLoS ONE · doi:10.1371/journal.pone.0000039 · Cited by 632 · see citing works
How Much Information?: Effects of Transparency on Trust in an Algorithmic Interface
Kizilcec, R. F. (2016) · Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858402 · Cited by 615 · see citing works
Anthropomorphism: Opportunities and Challenges in Human–Robot Interaction
Złotowski, J. A., Proudfoot, D., Yogeeswaran, K., & Bartneck, C. (2014) · International Journal of Social Robotics · doi:10.1007/s12369-014-0267-6 · Cited by 603 · see citing works
(S)he's Got the Look: Gender Stereotyping of Robots 1
Eyssel, F., & Hegel, F. (2012) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.2012.00937.x · Cited by 556 · see citing works
Newman, D. T., Fast, N. J., & Harmon, D. J. (2020) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2020.03.008 · Cited by 550 · see citing works
Human Decisions and Machine Predictions
Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., & Mullainathan, S. (2017) · doi:10.3386/w23180 · Cited by 545 · see citing works
(2014) · Digital Commons at University of Maryland Carey Law (University of Maryland Francis King Carey School of Law) · Cited by 524 · see citing works
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
(2010) · PsycEXTRA Dataset · doi:10.1037/e578662012-001 · Cited by 522 · see citing works
Using psychophysiological techniques to measure user experience with entertainment technologies
Mandryk, R. L., Inkpen, K. M., & Calvert, T. W. (2006) · Behaviour and Information Technology · doi:10.1080/01449290500331156 · Cited by 516 · see citing works
Establishing the computer-patient working alliance in automated health behavior change interventions
Bickmore, T., Gruber, A., & Picard, R. (2005) · Patient Education and Counseling · doi:10.1016/j.pec.2004.09.008 · Cited by 494 · see citing works
Can Machines Think? Interaction and Perspective Taking with Robots Investigated via fMRI
Krach, S., Hegel, F., Wrede, B., Sagerer, G., Binkofski, F., & Kircher, T. T. J. (2008) · PLoS ONE · doi:10.1371/journal.pone.0002597 · Cited by 490 · see citing works
Tay, B., Jung, Y., & Park, T. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.05.014 · Cited by 490 · see citing works
Thompson, S. G., & Pocock, S. (1991) · The Lancet · doi:10.1016/0140-6736(91)91975-z · Cited by 489 · see citing works
Avoiding the Ask: A Field Experiment on Altruism, Empathy, and Charitable Giving
James Andreoni, A., Rao, J. M., & Trachtman, H. (2017) · Journal of Political Economy · doi:10.1086/691703 · Cited by 486 · see citing works
Whose Job Is It Anyway? A Study of Human-Robot Interaction in a Collaborative Task
HINDS, P. J., Roberts, T. L., & Jones, H. (2004) · Human-Computer Interaction · doi:10.1207/s15327051hci1901&2_7 · Cited by 474 · see citing works
A Right to Reasonable Inferences: Re-Thinking Data Protection Law in the Age of Big Data and AI
Wachter, S., & Mittelstadt, B. (2018) · doi:10.31228/osf.io/mu2kf · Cited by 463 · see citing works
Making sense of recommendations
Yeomans, M., Shah, A., Mullainathan, S., & Kleinberg, J. (2019) · Journal of Behavioral Decision Making · doi:10.1002/bdm.2118 · Cited by 459 · see citing works
Accountability of AI Under the Law: The Role of Explanation
Doshi-Velez, F., Kortz, M., Budish, R., Bavitz, C., Gershman, S. J., O'Brien, D., Scott, K., Shieber, S., Waldo, J., Weinberger, D., et al. (2017) · doi:10.2139/ssrn.3064761 · Cited by 457 · see citing works
Affective state and decision-making in the Ultimatum Game
Wout‐Frank, M. V. ‘., Kahn, R. S., Sanfey, A. G., & Aleman, A. (2006) · Experimental Brain Research · doi:10.1007/s00221-006-0346-5 · Cited by 449 · see citing works
Creating Rapport with Virtual Agents
Gratch, J., Wang, N., Gerten, J., Fast, E., & Duffy, R. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-74997-4_12 · Cited by 419 · see citing works
Köbis, N., & Mossink, L. D. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106553 · Cited by 406 · see citing works
“It doesn’t matter what you are!” Explaining social effects of agents and avatars
von der Pütten, A. M., Krämer, N. C., Gratch, J., & Kang, S.-H. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.06.012 · Cited by 389 · see citing works
The Perceived Utility of Human and Automated Aids in a Visual Detection Task
Dzindolet, M. T., Pierce, L. G., Beck, H. P., & Dawe, L. A. (2002) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/0018720024494856 · Cited by 386 · see citing works
Neural correlates of depth of strategic reasoning in medial prefrontal cortex
Coricelli, G., & Nagel, R. (2009) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.0807721106 · Cited by 385 · see citing works
Automation Bias: Decision Making and Performance in High-Tech Cockpits
Mosier, K. L., Skitka, L. J., Heers, S., & Burdick, M. (1998) · The International Journal of Aviation Psychology · doi:10.1207/s15327108ijap0801_3 · Cited by 353 · see citing works
The relative influence of advice from human experts and statistical methods on forecast adjustments
Önkal, D., Goodwin, P., Thomson, M. E., Gonul, M. S., & Pollock, A. C. (2009) · Journal of Behavioral Decision Making · doi:10.1002/bdm.637 · Cited by 331 · see citing works
Accountability and automation bias
SKITKA, L. J., MOSIER, K., & BURDICK, M. D. (2000) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1999.0349 · Cited by 324 · see citing works
When shall we use our heads instead of the formula?
Meehl, P. E. (1957) · Journal of Counseling Psychology · doi:10.1037/h0047554 · Cited by 310 · see citing works
An Experimental Study on Emotional Reactions Towards a Robot
Pütten, A. M. R.-V. D., Krämer, N. C., Hoffmann, L., Sobieraj, S., & Eimler, S. C. (2012) · International Journal of Social Robotics · doi:10.1007/s12369-012-0173-8 · Cited by 308 · see citing works
Understanding algorithm aversion: When is advice from automation discounted?
Prahl, A., & Van Swol, L. (2017) · Journal of Forecasting · doi:10.1002/for.2464 · Cited by 308 · see citing works
Effects of Imperfect Automation on Decision Making in a Simulated Command and Control Task
Rovira, E., McGarry, K., & Parasuraman, R. (2007) · Hum. Factors · doi:10.1518/001872007779598082 · Cited by 297 · see citing works
Manzey, D., Reichenbach, J., & Onnasch, L. (2012) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343411433844 · Cited by 277 · see citing works
Dietvorst, B. J., & Bharti, S. (2020) · Psychological Science · doi:10.1177/0956797620948841 · Cited by 275 · see citing works
Physical Human–Robot Interaction
Haddadin, S., & Croft, E. A. (2016) · Springer handbooks · doi:10.1007/978-3-319-32552-1_69 · Cited by 268 · see citing works
Decision-making authority, team efficiency and human worker satisfaction in mixed human–robot teams
Gombolay, M., Gutierrez, R. A., Clarke, S. G., Sturla, G. F., & Shah, J. (2015) · Autonomous Robots · doi:10.1007/s10514-015-9457-9 · Cited by 258 · see citing works
Hoffman, M., Kahn, L. B., & Li, D. (2018) · The Quarterly Journal of Economics · doi:10.1093/qje/qjx042 · Cited by 252 · see citing works
To err is robot: how humans assess and act toward an erroneous social robot
Mirnig, N., Stollnberger, G., Miksch, M., Stadler, S., Giuliani, M., & Tscheligi, M. (2017) · Frontiers in Robotics and AI · doi:10.3389/frobt.2017.00021 · Cited by 244 · see citing works
Promberger, M., & Baron, J. (2006) · Journal of Behavioral Decision Making · doi:10.1002/bdm.542 · Cited by 242 · see citing works
Crandall, J. W., Oudah, M., Tennom, Ishowo-Oloko, F., Abdallah, S., Bonnefon, J., Cebrián, M., Shariff, A., Goodrich, M. A., & Rahwan, I. (2018) · Nature Communications · doi:10.1038/s41467-017-02597-8 · Cited by 240 · see citing works
Social Robots on a Global Stage: Establishing a Role for Culture During Human–Robot Interaction
Lim, V., Rooksby, M., & Cross, E. S. (2020) · International Journal of Social Robotics · doi:10.1007/s12369-020-00710-4 · Cited by 228 · see citing works
Lim, S., & Reeves, B. (2010) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2009.09.008 · Cited by 226 · see citing works
Metzger, U., & Parasuraman, R. (2005) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/0018720053653802 · Cited by 217 · see citing works
Who should i blame? effects of autonomy and transparency on attributions in human-robot interaction
Kim, T., & Hinds, P. (2006) · ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication · doi:10.1109/roman.2006.314398 · Cited by 217 · see citing works
“Who’s Johnny?” Anthropomorphic Framing in Human–Robot Interaction, Integration, and Policy
Darling, K. (2017) · Oxford University Press eBooks · doi:10.1093/oso/9780190652951.003.0012 · Cited by 216 · see citing works
AI as a moral crumple zone: The effects of AI-mediated communication on attribution and trust
Hohenstein, J., & Jung, M. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2019.106190 · Cited by 212 · see citing works
Bad machines corrupt good morals
Köbis, N., Bonnefon, J., & Rahwan, I. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01128-2 · Cited by 209 · see citing works
Sarter, N. B., & Schroeder, B. (2001) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872001775870403 · Cited by 195 · see citing works
Assessing Risk Assessment in Action
Stevenson, M. T. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.3016088 · Cited by 195 · see citing works
No fair!! An interaction with a cheating robot
Short, E. S., Hart, J., Vu, M., & Scassellati, B. M. (2010) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1109/hri.2010.5453193 · Cited by 185 · see citing works
Behavioural evidence for a transparency–efficiency tradeoff in human–machine cooperation
Ishowo-Oloko, F., Bonnefon, J.-F., Soroye, Z., Crandall, J., Rahwan, I., & Rahwan, T. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0113-5 · Cited by 178 · see citing works
Waytz, A. G., & Norton, M. I. (2014) · Emotion · doi:10.1037/a0036054 · Cited by 177 · see citing works
Complacency and Automation Bias in the Use of Imperfect Automation
Wickens, C. D., Clegg, B. A., Vieane, A. Z., & Sebok, A. L. (2015) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815581940 · Cited by 176 · see citing works
Jago, A. S. (2017) · Academy of Management Discoveries · doi:10.5465/amd.2017.0002 · Cited by 172 · see citing works
Don't Blame the Computer: When Self-Disclosure Moderates the Self-Serving Bias
Moon, Y. (2003) · Journal of Consumer Psychology · doi:10.1207/153276603768344843 · Cited by 163 · see citing works
Autonomy and Common Ground in Human-Robot Interaction: A Field Study
Stubbs, K. N., HINDS, P. J., & Wettergreen, D. S. (2007) · IEEE Intelligent Systems · doi:10.1109/mis.2007.21 · Cited by 162 · see citing works
Computer Decision Support as a Source of Interpretation Error: The Case of Electrocardiograms
Tsai, T. L., Fridsma, D. B., & Gatti, G. (2003) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m1279 · Cited by 161 · see citing works
Persuasiveness of expert systems
Dijkstra, J. J., Liebrand, W. B. G., & Timminga, E. (1998) · Behaviour & Information Technology · doi:10.1080/014492998119526 · Cited by 161 · see citing works
Why are we averse towards Algorithms? A comprehensive literature Review on Algorithm aversionPreprint
Jussupow, E., Benbasat, I., & Heinzl, A. (2020) · RePEc: Research Papers in Economics · Cited by 157 · see citing works
Vulnerable robots positively shape human conversational dynamics in a human–robot team
Traeger, M. L., Strohkorb Sebo, S., Jung, M., Scassellati, B., & Christakis, N. A. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1910402117 · Cited by 140 · see citing works
Are computers scapegoats? Attributions of responsibility in human–computer interaction
Moon, Y., & Nass, C. (1998) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.1998.0199 · Cited by 129 · see citing works
Automation Bias and Errors: Are Crews Better Than Individuals?
Skitka, L. J., Mosier, K. L., Burdick, M., & Rosenblatt, B. (2000) · The International Journal of Aviation Psychology · doi:10.1207/s15327108ijap1001_5 · Cited by 127 · see citing works
Economics, Fairness and Algorithmic BiasPreprint
Cowgill, B., & Tucker, C. E. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3361280 · Cited by 126 · see citing works
User agreement with incorrect expert system advice
Dijkstra, J. J. (1999) · Behaviour and Information Technology · doi:10.1080/014492999118832 · Cited by 124 · see citing works
Effects of incorrect computer-aided detection (CAD) output on human decision-making in mammography
Alberdi, E., Povyakalo, A., Strigini, L., & Ayton, P. (2004) · Academic Radiology · doi:10.1016/j.acra.2004.05.012 · Cited by 124 · see citing works
How do we think machines think? An fMRI study of alleged competition with an artificial intelligence
Chaminade, T., Rosset, D. B., Fonséca, D. D., Nazarian, B., Lutscher, E., Cheng, G., & Deruelle, C. (2012) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2012.00103 · Cited by 119 · see citing works
Bartneck, C., Yogeeswaran, K., Ser, Q. M., Woodward, G., Sparrow, R., Wang, S., & Eyssel, F. (2018) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3171221.3171260 · Cited by 118 · see citing works
Why do patients derogate physicians who use a computer-based diagnostic support system?
Shaffer, V. A., Probst, C. A., Merkle, E. C., Arkes, H. R., & Medow, M. A. (2013) · Medical Decision Making · doi:10.1177/0272989x12453501 · Cited by 115 · see citing works
Shank, D. B., DeSanti, A., & Maninger, T. (2019) · Information Communication & Society · doi:10.1080/1369118x.2019.1568515 · Cited by 114 · see citing works
Driver Acceptance of Unreliable Traffic Information in Familiar and Unfamiliar Settings
Kantowitz, B. H., Hanowski, R. J., & Kantowitz, S. C. (1997) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872097778543831 · Cited by 113 · see citing works
Rage against the machine: Automation in the moral domain
Gogoll, J., & Uhl, M. (2018) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2018.04.003 · Cited by 110 · see citing works
Patients Derogate Physicians Who Use a Computer-Assisted Diagnostic Aid
Arkes, H. R., Shaffer, V. A., & Medow, M. A. (2007) · Medical Decision Making · doi:10.1177/0272989x06297391 · Cited by 103 · see citing works
Adam, M. T. P., Krämer, J., & Muller, M. (2015) · Journal of Retailing · doi:10.1016/j.jretai.2015.01.003 · Cited by 99 · see citing works
Computer-Assisted Screening for Intimate Partner Violence and Control
Ahmad, F., Hogg‐Johnson, S., Stewart, D. E., Skinner, H. A., Glazier, R. H., & Levinson, W. S. (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-151-2-200907210-00124 · Cited by 99 · see citing works
Slow response times undermine trust in algorithmic (but not human) predictions
Efendić, E., de Calseyde, P. P. F. M. V., & Evans, A. M. (2020) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2020.01.008 · Cited by 99 · see citing works
Bai, B., Dai, H., Zhang, D., Zhang, F., & Hu, H. (2020) · Manufacturing & Service Operations Management · doi:10.1287/msom.2022.1120 · Cited by 98 · see citing works
Does spell-checking software need a warning label?
Galletta, D. F., Durcikova, A., Everard, A., & Jones, B. (2005) · Communications of the ACM · doi:10.1145/1070838.1070841 · Cited by 93 · see citing works
Group-based Emotions in Teams of Humans and Robots
Correia, F., Mascarenhas, S., Prada, R., Melo, F. S., & Paiva, A. (2018) · IEEE/ACM International Conference on Human-Robot Interaction · doi:10.1145/3171221.3171252 · Cited by 91 · see citing works
Promises and trust in human–robot interaction
Cominelli, L., Feri, F., Garofalo, R., Giannetti, C., Meléndez-Jímenez, M. A., Greco, A., Nardelli, M., Scilingo, E. P., & Kirchkamp, O. (2021) · Scientific Reports · doi:10.1038/s41598-021-88622-9 · Cited by 90 · see citing works
Trust in humans and robots: Economically similar but emotionally different
Schniter, E., Shields, T. W., & Sznycer, D. (2020) · Journal of Economic Psychology · doi:10.1016/j.joep.2020.102253 · Cited by 89 · see citing works
Service robot feature design effects on user perceptions and emotional responses
Zhang, T., KABER, D. B., Zhu, B., Neubert, M. S., Mosaly, P. R., & Hodge, L. (2010) · Intelligent Service Robotics · doi:10.1007/s11370-010-0060-9 · Cited by 88 · see citing works
Reducing algorithm aversion through experience
Filiz, I., Judek, J. R., Lorenz, M., & Spiwoks, M. (2021) · Journal of Behavioral and Experimental Finance · doi:10.1016/j.jbef.2021.100524 · Cited by 88 · see citing works
Automated underwriting in mortgage lending: Good news for the underserved?
Gates, S., Perry, V. G., & Zorn, P. M. (2002) · Housing Policy Debate · doi:10.1080/10511482.2002.9521447 · Cited by 87 · see citing works
Briggs, G., & Scheutz, M. J. (2014) · International Journal of Social Robotics · doi:10.1007/s12369-014-0235-1 · Cited by 86 · see citing works
Galster, S. M., Duley, J. A., Masalonis, A. J., & Parasuraman, R. (2001) · International Journal of Aviation Psychology · doi:10.1207/s15327108ijap1101_5 · Cited by 86 · see citing works
Teubner, T., Adam, M. T. P., & Riordan, R. (2015) · Journal of the Association for Information Systems · doi:10.17705/1jais.00412 · Cited by 77 · see citing works
Lee, E. (2010) · Communication Research · doi:10.1177/0093650209356389 · Cited by 72 · see citing works
Humphreys, J. C., Tsoh, J. Y., Kohn, M. A., & Gerbert, B. (2010) · Women s Health Issues · doi:10.1016/j.whi.2010.09.006 · Cited by 68 · see citing works
Gaming and strategic opacity in incentive provision
Ederer, F. P., Holden, R. T., & Meyer, M. (2018) · The RAND Journal of Economics · doi:10.1111/1756-2171.12253 · Cited by 68 · see citing works
Good advice is beyond all price, but what if it comes from a machine?
Hertz, N., & Wiese, E. (2019) · Journal of Experimental Psychology Applied · doi:10.1037/xap0000205 · Cited by 67 · see citing works
Blame Attribution Asymmetry in Human–Automation Cooperation
Liu, P., & Du, Y. L. (2021) · Risk Analysis · doi:10.1111/risa.13674 · Cited by 65 · see citing works
Electronic Checklists: Implications for Decision Making
Mosier, K. L., Palmer, E. A., & Degani, A. (1992) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193129203600104 · Cited by 63 · see citing works
Aircrews and automation bias: the advantages of teamwork?
Mosier, K. L., Skitka, L. J., Dunbar, M., & McDonnell, L. (2001) · The International Journal of Aviation Psychology · doi:10.1207/s15327108ijap1101_1 · Cited by 62 · see citing works
People Do Not Feel Guilty About Exploiting Machines
Melo, C. D., Marsella, S., & Gratch, J. S. (2016) · ACM Transactions on Computer-Human Interaction · doi:10.1145/2890495 · Cited by 59 · see citing works
Robot moderation of a collaborative game: Towards socially assistive robotics in group interactions
Short, E. S., & Matarić, M. J. (2017) · IEEE RO-MAN · doi:10.1109/roman.2017.8172331 · Cited by 53 · see citing works
Robot abuse - a limitation of the media equation
Bartneck, C. (2018) · TU/e Research Portal · doi:10.17605/osf.io/4fxq6 · Cited by 51 · see citing works
Hiring algorithms : An ethnography of fairness in practice
van den Broek, E., Sergeeva, A., & Huysman, M. (2019) · Data Archiving and Networked Services (DANS) · Cited by 50 · see citing works
Tay, B. T. C., Park, T., Jung, Y., Tan, Y. K., & Wong, A. H. Y. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39360-0_29 · Cited by 50 · see citing works
Improving human-human collaboration between children with a social robot
Sebo, S. S., Fukuto, E., Warren, N., Taylor, C., Berry, B., & Scassellati, B. M. (2016) · IEEE RO-MAN · doi:10.1109/roman.2016.7745172 · Cited by 50 · see citing works
Impact of Algorithmic Decision Making on Human Behavior: Evidence from Ultimatum Bargaining
Erlei, A., Nekdem, F., Meub, L., Anand, A., & Gadiraju, U. (2020) · Proceedings of the AAAI Conference on Human Computation and Crowdsourcing · doi:10.1609/hcomp.v8i1.7462 · Cited by 50 · see citing works
Social reactions toward people vs. computers: How mere lables shape interactions
Aharoni, E., & Fridlund, A. J. (2006) · Computers in Human Behavior · doi:10.1016/j.chb.2006.02.019 · Cited by 45 · see citing works
Bubbles in hybrid markets: How expectations about algorithmic trading affect human trading
Farjam, M., & Kirchkamp, O. (2017) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2017.11.011 · Cited by 44 · see citing works
Consumer reactions to professionals who use decision aids
Palmeira, M. M., & Spassova, G. (2015) · European Journal of Marketing · doi:10.1108/ejm-07-2013-0390 · Cited by 43 · see citing works
Sharing responsibility with a machine
Kirchkamp, O., & Strobel, C. (2019) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2019.02.010 · Cited by 42 · see citing works
The Incentive Effect of Scores: Randomized Evidence from Credit Committees
Paravisini, D., & Antoinette Schoar, B. (2013) · National Bureau of Economic Research · doi:10.3386/w19303 · Cited by 41 · see citing works
Bahner, J. E., Elepfandt, M. F., & Manzey, D. (2008) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120805201906 · Cited by 35 · see citing works
Bai, B., Dai, H., Zhang, D., et al. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3550887 · Cited by 34 · see citing works
Naquin, C. E., & Kurtzberg, T. R. (2003) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2003.12.001 · Cited by 33 · see citing works
Pezzo, M. V., & Pezzo, S. P. (2006) · Medical Decision Making · doi:10.1177/0272989x05282644 · Cited by 33 · see citing works
Blurring the Line Between Human and Machine: Marketing Artificial Intelligence
Castelo, N. (2019) · doi:10.7916/d8-k7vk-0s40 · Cited by 30 · see citing works
International Conference on Human-Agent Interaction
(2023) · doi:10.1145/3623809 · Cited by 30 · see citing works
Why Are People’s Decisions Sometimes Worse with Computer Support?
Alberdi, E., Strigini, L., Povyakalo, A. A., & Ayton, P. (2009) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-04468-7_3 · Cited by 29 · see citing works
Alberdi, E., Povyakalo, A. A., Strigini, L., Ayton, P., & Given-Wilson, R. (2008) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-008-0213-x · Cited by 28 · see citing works
How Humans Judge MachinesPreprint
Hidalgo, C. A., Orghian, D., Albó-Canals, J., de Almeida, F., & Martin, N. (2021) · CrimRxiv · doi:10.21428/cb6ab371.a6bc9cb4 · Cited by 24 · see citing works
How do Humans Interact with Algorithms? Experimental Evidence from Health Insurance
Bundorf, M. K., Polyakova, M., & Tai‐Seale, M. (2019) · National Bureau of Economic Research · doi:10.3386/w25976 · Cited by 23 · see citing works
Adam, M. T. P., Teubner, T., & Gimpel, H. (2018) · Group Decision and Negotiation · doi:10.1007/s10726-018-9579-5 · Cited by 22 · see citing works
The Managerial Effects of Algorithmic Fairness Activism
Cowgill, B., Dell’Acqua, F., & Matz, S. (2020) · AEA Papers and Proceedings · doi:10.1257/pandp.20201035 · Cited by 22 · see citing works
Nitsch, V., & Glassen, T. (2015) · IEEE RO-MAN · doi:10.1109/roman.2015.7333560 · Cited by 22 · see citing works
CHI '97 Extended Abstracts on Human Factors in Computing Systems
Edwards, A., Association for Computing Machinery-Digital Library, ACM Special Interest Group on Computer-Human Interaction, & SIGs, A. (1997) · Cited by 21 · see citing works
The Behavioral Economics of Artificial Intelligence: Lessons from Experiments with Computer PlayersPreprint
March, C. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3485475 · Cited by 21 · see citing works
The electronic mirror: Human-computer interaction and change in self-appraisals
Laere, K. H. D., Lundgren, D. C., & Howe, S. R. (1998) · Computers in Human Behavior · doi:10.1016/s0747-5632(97)00031-9 · Cited by 20 · see citing works
Tazelaar, F., & Snijders, C. C. P. (2004) · Journal of Purchasing and Supply Management · doi:10.1016/j.pursup.2004.11.004 · Cited by 17 · see citing works
Intelligent machines as social catalysts
Rahwan, I., Crandall, J. W., & Bonnefon, J. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2002744117 · Cited by 15 · see citing works
The Chinese Approach to Artificial Intelligence: An Analysis of Policy and RegulationPreprint
Roberts, H., Cowls, J., Morley, J., Taddeo, M., Wang, V., & Floridi, L. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3469783 · Cited by 15 · see citing works
Me, You or AI? How do we Feel about Delegation.
Leyer, M., & Schneider, S. (2019) · Journal of the Association for Information Systems · Cited by 15 · see citing works
Metzger, U., Duley, J. A., Abbas, R., & Parasuraman, R. (2000) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120004401104 · Cited by 13 · see citing works
Dell'Acqua, F., Kogut, B., & Perkowski, P. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3746564 · Cited by 5 · see citing works
The Economics of Babysitting a RobotPreprint
Alekseev, A. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3656684 · Cited by 4 · see citing works
Europe plans to strictly regulate high-risk AI technology
(2020) · AAAS Articles DO Group · doi:10.1126/science.abb3741 · Cited by 3 · see citing works
Rac(g)e Against the Machine? Social Incentives When Humans Meet RobotsPreprint
Corgnet, B., Hérnan-Gonzalez, R., & Mateo, R. (2019) · RePEc: Research Papers in Economics · Cited by 3 · see citing works
The Hidden Costs of Automation:
Hubbard, A., & Submission, H. C. F. (1987) · Medical Reference Services Quarterly · doi:10.1300/j115v06n01_07 · Cited by 2 · see citing works
Essays on Social and Behavioral Aspects of Apparel Supply Chains
Cuenca, A. S. D. T. (2019) · Cited by 1 · see citing works
Flagged first, then by citations
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 · see citing works
Three Challenges for AI-Assisted Decision-Making
Steyvers, M., & Kumar, A. (2024) · Perspectives on Psychological Science · doi:10.1177/17456916231181102 · Cited by 217 · see citing works
“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 · see citing works
Liu, F., & Lee, Y.-H. (2023) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2023.103685 · Cited by 105 · see citing works
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 98 · see citing works
“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.”
van Doorn, J., Smailhodžić, E., Puntoni, S., Li, J., Schumann, J. H., & Holthöwer, J. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.114000 · Cited by 55 · see citing works
Do people trust humans more than ChatGPT?
Buchanan, J. A., & Hickman, W. (2024) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2024.102239 · Cited by 41 · see citing works
Multi-agent, human–agent and beyond: A survey on cooperation in social dilemmas
Mu, C., Guo, H., Chen, Y., Shen, C., Hu, D., Hu, S., & Wang, Z. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128514 · Cited by 33 · see citing works
Regulating Government AI and the Challenge of Sociotechnical Design
Engstrom, D. F., & Haim, A. (2023) · Annual Review of Law and Social Science · doi:10.1146/annurev-lawsocsci-120522-091626 · Cited by 35 · see citing works
The cold-start problem in nascent AI strategy: Kickstarting data network effects
Vomberg, A., Wiegand, N., Krakowski, S. M., Bogusz, C. I., Gijsenberg, M. J., & Bleier, A. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.114236 · Cited by 30 · see citing works
“However, studies have also identified aversion even if no algorithmic error occurs (for an overview, see Chugunova & Sele, 2022).”
Putting a human in the loop: Increasing uptake, but decreasing accuracy of automated decision-making
Sele, D., & Chugunova, M. (2024) · PLoS ONE · doi:10.1371/journal.pone.0298037 · Cited by 30 · see citing works
Self-citationNavigating AI Convergence in Human–Artificial Intelligence Teams: A Signaling Theory Approach
Smith, A., Wagoner, H. P. V., Keplinger, K., & Çelebi, C. (2025) · Journal of Organizational Behavior · doi:10.1002/job.2856 · Cited by 36 · see citing works
“Previous research on human–AI teaming in organizational settings suggests that the distribution of agency is a pivotal factor that significantly impacts AI convergence in the work-place (Agrawal, Gans, and Goldfarb 2019; Chugunova and Sele 2022; Gagné et al. 2022; Grundke 2024).”
InfluentialYou, Me, and the AI: The Role of Third‐Party Human Teammates for Trust Formation Toward AI Teammates
Erengin, T., Briker, R., & de Jong, S. B. (2025) · Journal of Organizational Behavior · doi:10.1002/job.2857 · Cited by 27 · see citing works
The impact of generative artificial intelligence on socioeconomic inequalities and policy makingPreprint
Capraro, V., Lentsch, A., Acemoğlu, D., Akgün, S., Akhmedova, A., Bilancini, E., Bonnefon, J., Brañas‐Garza, P., Butera, L., Douglas, K. M., et al. (2023) · doi:10.31234/osf.io/6fd2y · Cited by 36 · see citing works
Maggioni, M. A., & Rossignoli, D. (2023) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2023.102011 · Cited by 21 · see citing works
Grundke, A. (2023) · Behaviour and Information Technology · doi:10.1080/0144929x.2023.2210688 · Cited by 20 · see citing works
“The critical question is, up to which point this discomfort is accepted and at which point too much aversion arises and thus the rise of the uncanny valley of mind outweighs the potential advantages of the use of machines with human-like mental capabilities (Chugunova and Sele 2022).”
BackgroundLi, K.-J., Shan, T., Wu, H.-J., Zou, Z., Huang, R.-P., Chang, R., & Shrestha, A. (2024) · Engineering applications of artificial intelligence · doi:10.1016/j.engappai.2024.109401 · Cited by 20 · see citing works
Digital knowledge engineering for strategy development
Vomberg, A., de Haan, E., Fabian, N. E., & Broekhuizen, T. (2024) · Journal of Business Research · doi:10.1016/j.jbusres.2024.114632 · Cited by 24 · see citing works
Nord-Bronzyk, A., Savulescu, J., Ballantyne, A., Braunack‐Mayer, A., Krishnaswamy, P., Lysaght, T., Ong, M. E. H., Liu, N., Menikoff, J., Mertens, M., et al. (2025) · Asian Bioethics Review · doi:10.1007/s41649-024-00348-8 · Cited by 18 · see citing works
Countering AI-generated misinformation with pre-emptive source discreditation and debunking
Spearing, E. R., Gile, C. I., Fogwill, A. L., Prike, T., Swire‐Thompson, B., Lewandowsky, S., & Ecker, U. K. H. (2025) · Royal Society Open Science · doi:10.1098/rsos.242148 · Cited by 27 · see citing works
In bot we trust? Personality traits and reciprocity in human-bot trust games
Upadhyaya, N., & Galizzi, M. M. (2023) · Frontiers in Behavioral Economics · doi:10.3389/frbhe.2023.1164259 · Cited by 18 · see citing works
“, 2018), an entire field now exists to investigate the behavioural and logistical factors which affect human-bot cooperation (Rahwan et al., 2019; Chugunova and Sele, 2022).”
BackgroundResultInfluentialLammert, O., Richter, B., Schütze, C., Thommes, K., & Wrede, B. (2024) · Frontiers in Behavioral Economics · doi:10.3389/frbhe.2024.1377075 · Cited by 18 · see citing works
Lai, X., & Rau, P. P. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2365029 · Cited by 28 · see citing works
“As the capabilities and autonomy of artificial intelligence (AI) have increased, the role of AI-infused robots or intelligent agents in the workplace has expanded from subordinate tools to collaborative teammates and, in some cases, even managers or leaders (Chugunova & Sele, 2022).”
Social interactions between automated vehicles and human drivers: a narrative review
Liu, P. (2024) · Ergonomics · doi:10.1080/00140139.2024.2435038 · Cited by 13 · see citing works
“Its approach resembles previous reviews (Chugunova and Sele 2022; Patterson 2018).”
The Emotional Dilemma: Influence of a Human-like Robot on Trust and Cooperation
Becker, D., Rueda, D., Beese, F., Torres, B. S. G., Lafdili, M., Ahrens, K., Fu, D., Strahl, E., Weber, T., & Wermter, S. (2023) · IEEE RO-MAN · doi:10.1109/ro-man57019.2023.10309321 · Cited by 13 · see citing works
“Research on social dilemmas suggests that humans act more selfishly and less emotional when interacting with artificial agents and robots [34], [35], [36].”
BackgroundThe Impact of Generative Artificial Intelligence on Socioeconomic Inequalities and Policy MakingPreprint
Capraro, V., Lentsch, A., Acemoğlu, D., Akgün, S., Akhmedova, A., Bilancini, E., Bonnefon, J., Brañas‐Garza, P., Butera, L., Douglas, K. M., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4666103 · Cited by 13 · see citing works
Machines meet humans on the social road: Risk implications
Liu, P. (2023) · Risk Analysis · doi:10.1111/risa.14255 · Cited by 12 · see citing works
“Research on other machines (Chugunova & Sele, 2022) suggests that AV exploitation may also stem from certain affective and moral components (see also Liu et al., 2022).”
Biswas, S., Erlei, A., & Gadiraju, U. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713201 · Cited by 12 · see citing works
Artificial influence: how AI and influencers shape choices in tourism and hospitality
Mesquita, E., Herrero, E., Lopes, E. L., Ribeiro, T. D. L. S., & Scrivano, P. (2025) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-12-2024-1898 · Cited by 10 · see citing works
Ruled by robots: preference for algorithmic decision makers and perceptions of their choices
Chugunova, M., & Luhan, W. J. (2024) · Public Choice · doi:10.1007/s11127-024-01178-w · Cited by 12 · see citing works
“Importantly, our results only indirectly speak to the discussion of whether people are generally averse to algorithms (Dietvorst et al., 2015), appreciate them (Logg et al., 2019), or even over-rely on them (for the overview of the literature see, Chugunova & Sele, 2022).”
Self-citationAdverse reactions to the use of large language models in social interactions
Dvorak, F., Stumpf, R., Fehrler, S., & Fischbacher, U. (2025) · PNAS Nexus · doi:10.1093/pnasnexus/pgaf112 · Cited by 10 · see citing works
“…– algorithm interaction has shown that, depending on the design of the algorithm, humans often act more rationally and selfish than in human – human interactions, and seem less prone to emotional and social responses ( 18 – 20 ) but are nevertheless willing to delegate decisions to algorithms (21).”
Understanding consumer responses to robot roles in human-robot service collaboration
Li, Y., Chang, Y., Yang, T., & Li, Y. (2025) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2025.104407 · Cited by 10 · see citing works
Improving Human Deception Detection Using Algorithmic Feedback
Serra-García, M., & Uri Gneezy, B. (2025) · Management Science · doi:10.1287/mnsc.2023.02792 · Cited by 11 · see citing works
Roser, D., Meinikheim, M., Muzalyova, A., Mendel, R., Palm, C., Probst, A., Nagl, S., Scheppach, M. W., Römmele, C., Schnoy, E., et al. (2025) · DEN Open · doi:10.1002/deo2.70150 · Cited by 9 · see citing works
“As recently summarized [18–20], we need to account for numerous possible pitfalls and cognitive biases in the interaction between endoscopists/human examiners and the mechanical AI system, as shown in Figure 4.”
Are artificial agents perceived similarly to humans? Knowns, unknowns and the road ahead
Rubo, M., & Neumann, I. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1565170 · Cited by 9 · see citing works
Ferraz, V., Houf, L., Pitz, T., Schwieren, C., & Sickmann, J. (2024) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2024.100578 · Cited by 9 · see citing works
“Studies have found differing levels of human interaction with automated agents based on factors such as task context, performance expectations, and agent roles [8].”
Moral judgements of errors by AI systems and humans in civil and criminal law
Parlangeli, O., Currò, F., Palmitesta, P., & Guidi, S. (2023) · Behaviour and Information Technology · doi:10.1080/0144929x.2023.2283622 · Cited by 7 · see citing works
“As suggested by Chugunova and Sele (2022), such con fl icting fi ndings can be reconciled with a general willingness to include intelligent systems in decision-making processes, even to an excessive degree, though not allocating them to the decision (Chugunova and Sele 2022).”
Li, Y., Chang, Y., & Li, Y. (2025) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2025.102937 · Cited by 6 · see citing works
Seven Challenges for the Science of Animal Minds
Dacey, M. (2025) · doi:10.1093/9780198928102.001.0001 · Cited by 6 · see citing works
Parlangeli, O., Currò, F., Palmitesta, P., & Guidi, S. (2023) · European Conference on Cognitive Ergonomics · doi:10.1145/3605655.3605676 · Cited by 6 · see citing works
Context-dependent preferences for a decision support system's level of automation
Schilling, T., Müller, R., Ellwart, T., & Antoni, C. H. (2023) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2023.100350 · Cited by 6 · see citing works
Measuring preferences for algorithms — How willing are people to cede control to algorithms?
Ivanova‐Stenzel, R., & Tolksdorf, M. (2024) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2024.102270 · Cited by 5 · see citing works
Kotsios, H. C., Asteriou, P. M. M. P., & Wintersberger, P. (2024) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3640792.3675738 · Cited by 5 · see citing works
Increasing Accountability and Compliance with Robot Advice
Holthöwer, J., van Doorn, J., & Noble, S. M. (2025) · Journal of Marketing · doi:10.1177/00222429251370268 · Cited by 4 · see citing works
Schaap, G., Bosse, T., & Vettehen, P. H. (2025) · Cyberpsychology Journal of Psychosocial Research on Cyberspace · doi:10.5817/cp2025-5-8 · Cited by 4 · see citing works
Flösch, K., Flaisch, T., Imhof, M. A., & Schupp, H. T. (2023) · Psychophysiology · doi:10.1111/psyp.14433 · Cited by 4 · see citing works
From challenges to opportunities: navigating the human response to automated agents in the workplace
Ðula, I., Berberena, T., Keplinger, K., & Wirzberger, M. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03962-x · Cited by 4 · see citing works
“…other hand, in situations where increased emotions and social interactions are detrimental, the reduced emotional and social response has been shown to increase the rationality of human-AI interactions and improve performance (Chugunova and Sele, 2022), as shown in the balancing feedback loop B3.”
Humans program artificial delegates to accurately solve collective-risk dilemmas but lack precision
Terrucha, I., Domingos, E. F., Suchon, R., Santos, F. C., Simoens, P., & Lenaerts, T. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2319942121 · Cited by 4 · see citing works
The mind online: Can digital technologies affect how we think?
Ρούσσος, Π. (2023) · Psychology the Journal of the Hellenic Psychological Society · doi:10.12681/psy_hps.36226 · Cited by 6 · see citing works
Algorithmic trading, what if it is just an illusion? Evidence from experimental asset markets
Leal, S. J., & Hanaki, N. (2024) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2024.102240 · Cited by 4 · see citing works
Szukits, Á., Sztrida, L., & Szabó, I. A. (2024) · Vezetéstudomány / Budapest Management Review · doi:10.14267/veztud.2024.06.03 · Cited by 4 · see citing works
Human mediation leads to higher compliance in digital mental health: field evidence from India
Chatterjee, C., Chugunova, M., Ghosh, M., Singhal, A., & Wang, L. X. (2023) · Frontiers in Behavioral Economics · doi:10.3389/frbhe.2023.1232462 · Cited by 4 · see citing works
“Users also tend to incorporate recommendations from an algorithm more than those from other humans (Logg et al., 2019; Sele and Chugunova, 2022).”
Self-citationThe impact of process automation on performance
Strobel, C. (2025) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2025.102377 · Cited by 4 · see citing works
The Economics of Babysitting a RobotPreprint
Alekseev, A. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3656684 · Cited by 4 · see citing works
Future Perspective of Artificial Intelligence Diagnostics for Early Barrett’s Neoplasia
Roser, D. A., & Ebigbo, A. (2025) · Digestion · doi:10.1159/000547635 · Cited by 3 · see citing works
Trusting machines with morality — Delegating moral decisions to AI
Hüholt, N., & Szech, N. (2026) · European Economic Review · doi:10.1016/j.euroecorev.2025.105255 · Cited by 5 · see citing works
Gorny, P. M., Renner, B., & Schäfer, L. (2023) · Frontiers in Behavioral Economics · doi:10.3389/frbhe.2023.1220563 · Cited by 4 · see citing works
Ultimatum bargaining: Algorithms vs. Humans
Özkes, A., Hanaki, N., Vanderelst, D. F., & Willems, J. (2024) · Economics Letters · doi:10.1016/j.econlet.2024.111979 · Cited by 3 · see citing works
Chen, H., Wang, Z., & Ren, M. (2025) · Data and Information Management · doi:10.1016/j.dim.2025.100107 · Cited by 3 · see citing works
Hooked on artificial agents: a systems thinking perspective
Ðula, I., Berberena, T., Keplinger, K., & Wirzberger, M. (2023) · Frontiers in Behavioral Economics · doi:10.3389/frbhe.2023.1223281 · Cited by 3 · see citing works
From Adam Smith to artificial intelligence: an experimental exploration of emotion in humanomics
Qin, X., Wang, S., Wu, M. Z., & Feng, X. (2024) · Public Choice · doi:10.1007/s11127-024-01227-4 · Cited by 3 · see citing works
“Chugunova and Sele (2022) reviewed 138 experimental studies examining how humans interact with automated agents.”
Strebinger, A., & Treiblmaier, H. (2025) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2025.102939 · Cited by 3 · see citing works
Bureaucratic accountability: enabler or barrier for algorithm use?
Weerheijm, B., Galdames, M., & Giest, S. N. (2025) · Policy Design and Practice · doi:10.1080/25741292.2025.2578064 · Cited by 5 · see citing works
Alekseev, A. O., & Strobel, C. (2026) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2026.102525 · Cited by 2 · see citing works
Mutzner, N., Oberhauser, V., Winter, F., & Rauhut, H. (2023) · Frontiers in Behavioral Economics · doi:10.3389/frbhe.2023.1227166 · Cited by 2 · see citing works
Ferraz, V., Houf, L., Pitz, T., Schwieren, C., & Sickmann, J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4891768 · Cited by 2 · see citing works
Additive vs. subtractive earning in shared human-robot work environments
Dreyfuss, B., Heffetz, O., Hoffman, G., Ishai, G., & Kshirsagar, A. (2023) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2023.11.024 · Cited by 1 · see citing works
Introduction to human-machine interaction
Ahmed, S. S., Nisar, H., & Lo, P. K. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-29150-0.00008-1 · Cited by 1 · see citing works
Remote Control and Automation of UR3 Robot with IoT and Vision Algorithms
Contreras-Torres, J., Robles, H. D. L. T., Gutiérrez-Castro, S., Díaz-Martínez, J.-G., FLORES-ERAÑA, G., & Gutiérrez-Carmona, I. (2024) · IEEE International Conference on Engineering Veracruz (ICEV) · doi:10.1109/icev63254.2024.10766003 · Cited by 1 · see citing works
“Universal Robots presents the UR3e as a medium-sized arm with a 3 kg payload and an action radius of 500 mm, positioning it as one of the most suitable robots for automating tasks requiring lifting low weights [1].”
Yapay Zekâ ve İnsan İş birliği: Çatışma mı, İş birliği mi?
Gezgin, A. Y. (2025) · Özgür Yayınları eBooks · doi:10.58830/ozgur.pub686.c2892 · Cited by 1 · see citing works
Saumer, M., Neureiter, A., Varga, E., Gataric, V., Liu, C., & Matthes, J. (2025) · Cyberpsychology: Journal of Psychosocial Research on Cyberspace · doi:10.5817/cp2025-2-3 · Cited by 1 · see citing works
“AI is viewed as less intentional, self-interested, and biased, having a narrower emotional range with reduced gratitude, anger, and fairness responses (Chugunova & Sele, 2022), thus, possibly not as authentic as humans.”
Comparing the audience effect of anthropomorphic robots and humans in economic games
Stinkeste, C., Dreber, A., Olofsson, J., & Skantze, G. (2025) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2025.100215 · Cited by 1 · see citing works
When Robots Think and Feel, Will Trust Disappear? Evidence from an Online Experiment
Pan, Y., Gómez‐González, C., Clochard, G.-J., & Dietl, H. (2026) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2026.102563 · Cited by 1 · see citing works
Jian, Y., Xi, J., & Huang, Y. (2026) · International Journal of Advertising · doi:10.1080/02650487.2026.2660003 · Cited by 1 · see citing works
Dacey, M. (2025) · Oxford University Press eBooks · doi:10.1093/9780198928102.003.0008 · Cited by 1 · see citing works
Sample Size and Generalizability
Dacey, M. (2025) · Oxford University Press eBooks · doi:10.1093/9780198928102.003.0007 · Cited by 1 · see citing works
Do you trust your boss, who relies on AI? New evidence for algorithm aversionPreprint
Taguchi, S., Tanaka, K., Tsuruta, M., Nagata, D., & Isokawa, K. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4495860 · Cited by 1 · see citing works
Algorithmic trading, what if it is just an illusion? Evidence from experimental asset marketsPreprint
Leal, S. J., & Hanaki, N. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4620189
Bai, L., Wei, L., & Xue, L. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4636843
Chen, H., Wang, Z., & Ren, M. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4895723
Human and Algorithmic Cooperation: Parameters Matter!Preprint
von Schenk, A., Blonski, M., Klockmann, V., Eibelshäuser, S., & Hegemann, H. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4955708
Ðula, I., Berberena, T., Keplinger, K., & Wirzberger, M. (2024) · Lecture notes in information systems and organisation · doi:10.1007/978-3-031-76970-2_15
Dacey, M. (2025) · Oxford University Press eBooks · doi:10.1093/9780198928102.003.0001
Conclusion: Of a Different Mind
Dacey, M. (2025) · Oxford University Press eBooks · doi:10.1093/9780198928102.003.0009
Dacey, M. (2025) · Oxford University Press eBooks · doi:10.1093/9780198928102.003.0002
Dacey, M. (2025) · Oxford University Press eBooks · doi:10.1093/9780198928102.003.0004
Dacey, M. (2025) · Oxford University Press eBooks · doi:10.1093/9780198928102.003.0003
Dacey, M. (2025) · Oxford University Press eBooks · doi:10.1093/9780198928102.003.0006
Dacey, M. (2025) · Oxford University Press eBooks · doi:10.1093/9780198928102.003.0005
Dacey, M. (2025) · Oxford University Press eBooks · doi:10.1093/9780198928102.002.0006
Information-Signaling in Pre-Trial Bargaining: An ExperimentPreprint
Turrini, E., Guerra, A., & Lavie, S. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5219401
Lie against AI: Revealing private information through AI in an economic experiment
Bershadskyy, D., Dinges, L., Fiedler, M.-A., Greif, J., Al-Hamadi, A. K., Ostermaier, N., & Weimann, J. (2026) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2026.107547
A Taxonomy of AI ExperimentsPreprint
Alekseev, A., & Strobel, C. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5291490
Artificial intelligence, distributional fairness, and pivotality
Klockmann, V., von Schenk, A., & Villeval, M. C. (2025) · European Economic Review · doi:10.1016/j.euroecorev.2025.105098 · Cited by 1 · see citing works
Between AI, You, and Me: Is Algorithm Aversion Just About Control?Preprint
Ivanova‐Stenzel, R., & Tolksdorf, M. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5362996
Human vs. algorithmic auditors: the impact of entity type and ambiguity on human dishonesty
Protte, M., & Djawadi, B. M. (2025) · Frontiers in Behavioral Economics · doi:10.3389/frbhe.2025.1645749
Building Trust with a Teachable Artificial Intelligence: The Case of Repeated Trust Games *Preprint
Prissé, B., Jayasekara, D. N., Deng, R., & Ho, J. Q. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5527939
Beyond Performance: Exploring trade-offs in the design of financial algorithms
Gaudeul, A., & Giannetti, C. (2025) · Journal of Behavioral and Experimental Finance · doi:10.1016/j.jbef.2025.101119 · Cited by 3 · see citing works
Weerheijm, B., Giest, S. N., & Klievink, B. (2025) · Government Information Quarterly · doi:10.1016/j.giq.2025.102088 · Cited by 1 · see citing works
Playing Prisoner's Dilemma Games with a Large Language ModelPreprint
Orland, A., Takemoto, K., & Külpmann, P. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5716903
- 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 · 2020: 1
- 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 › Psychology › Social Psychology › 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
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
