The ethical use of artificial intelligence in human resource management: a decision-making framework
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?
Bankins (2021) proposes that organizations must align actual AI use with its intended use by instructing employees on how to interact and rely on AI.
“Bankins (2021) in her ethical framework for AI in human resource management proposes that organizations must align actual AI use with its intended use by instructing employees on how to interact and rely on AI.”
From Check the box! How to deal with automation bias in AI-based personnel selection (2023) · cites this paper as Bankins (2021)
Cites
The global landscape of AI ethics guidelines
Jobin, A., Ienca, M., & Vayena, E. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0088-2 · Cited by 6,220 · see citing works
Task-Technology Fit and Individual Performance
Goodhue, D. L., & Thompson, R. L. (1995) · MIS Quarterly · doi:10.2307/249689 · Cited by 6,006 · see citing works
boyd, D., & Crawford, K. (2012) · Information, Communication & Society · doi:10.1080/1369118x.2012.678878 · Cited by 5,479 · see citing works
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., et al. (2018) · Minds and Machines · doi:10.1007/s11023-018-9482-5 · Cited by 4,774 · cited 7× · see citing works
“The field generally adopts a socio-technical stance (i.e., that social and technological contexts must be examined in tandem, Selbst et al., 2019) and takes the view that AI should be developed and applied by, with, and for people to aid the betterment of humans (e.g., Floridi et al., 2018).”
BackgroundInfluentialAlgorithm 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
Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making
Jarrahi, M. H. (2018) · Business Horizons · doi:10.1016/j.bushor.2018.03.007 · Cited by 2,772 · see citing works
Algorithms at Work: The New Contested Terrain of Control
Kellogg, K. C., Valentine, M. A., & Christin, A. (2020) · Academy of Management Annals · doi:10.5465/annals.2018.0174 · Cited by 2,732 · see citing works
The Ethics of AI Ethics: An Evaluation of Guidelines
Hagendorff, T. (2020) · Minds and Machines · doi:10.1007/s11023-020-09517-8 · Cited by 1,911 · cited 1× · see citing works
“Recent reviews (e.g., Floridi & Cowls, 2019; Hagendorff, 2020; Jobin et al., 2019) suggest a significant overlap exists across these approaches that supports an emerging global consensus on such ethical principles.”
BackgroundA Unified Framework of Five Principles for AI in Society
Floridi, L., & Cowls, J. (2019) · Harvard Data Science Review · doi:10.1162/99608f92.8cd550d1 · Cited by 1,631 · cited 1× · see citing works
“Recent reviews (e.g., Floridi & Cowls, 2019; Hagendorff, 2020; Jobin et al., 2019) suggest a significant overlap exists across these approaches that supports an emerging global consensus on such ethical principles.”
BackgroundFairness and Abstraction in Sociotechnical Systems
Selbst, A. D., Boyd, D., Friedler, S. A., Venkatasubramanian, S., & Vertesi, J. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency · doi:10.1145/3287560.3287598 · Cited by 1,631 · see citing works
Artificial Intelligence in Human Resources Management: Challenges and a Path Forward
Tambe, P., Cappelli, P., & Yakubovich, V. (2019) · California Management Review · doi:10.1177/0008125619867910 · Cited by 1,609 · see citing works
Lee, M. K. (2018) · Big Data & Society · doi:10.1177/2053951718756684 · Cited by 1,338 · see citing works
Amazon Scraps Secret AI Recruiting Tool that Showed Bias against Women *
Dastin, J. (2022) · Ethics of Data and Analytics · doi:10.1201/9781003278290-44 · Cited by 1,165 · see citing works
Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World
Parker, S. K., & Grote, G. (2022) · Applied Psychology · doi:10.1111/apps.12241 · Cited by 960 · see citing works
Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers
Lee, M. K., Kusbit, D., Metsky, E., & Dabbish, L. (2015) · Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702548 · Cited by 823 · see citing works
Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need?
Holstein, K., Wortman Vaughan, J., Daumé, H., Dudik, M., & Wallach, H. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300830 · Cited by 777 · see citing works
'It's Reducing a Human Being to a Percentage': Perceptions of Justice in Algorithmic Decisions
Binns, R., Van Kleek, M., Veale, M., Lyngs, U., Zhao, J., & Shadbolt, N. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173951 · Cited by 691 · cited 1× · see citing works
“…denial of human interaction can degrade individuals’ justice perceptions, or the perceived fairness of a decision, generating feelings of impersonal treatment, devaluation, and dehumanization (such as “being reduced to a percentage”) (Binns et al., 2018, p. 1; Lee et al., 2019, p. 16; Lee, 2018).”
BackgroundToo much sitting – A health hazard
Dunstan, D. W., Howard, B., Healy, G. N., & Owen, N. G. (2012) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2012.05.020 · Cited by 583 · see citing works
Meaningful Human Control over Autonomous Systems: A Philosophical Account
Santoni de Sio, F., & van den Hoven, J. (2018) · Frontiers in Robotics and AI · doi:10.3389/frobt.2018.00015 · Cited by 566 · see citing works
Society-in-the-loop: programming the algorithmic social contract
Rahwan, I. (2018) · Ethics and Information Technology · doi:10.1007/s10676-017-9430-8 · Cited by 553 · see citing works
Human + Machine : Reimagining Work in the Age of AI
Daugherty, P. R. (2021) · Cited by 511 · see citing works
Artificial Intelligence in Society
OECD (2019) · doi:10.1787/eedfee77-en · Cited by 487 · see citing works
Algorithmic Bias in Autonomous Systems
Danks, D., & London, A. J. (2017) · Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2017/654 · Cited by 472 · 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 · cited 1× · see citing works
“…governing principles for AI development (Floridi et al., 2018), examining the legal and accountability implications of AI decision making (Doshi-Velez et al., 2017), the ethical implications of social robot use (Stahl & Coeckelbergh, 2016), and the efficacy of granting moral rights to AI…”
BackgroundPerformance Management: A Model and Research Agenda
Hartog, D. N. D., Boselie, P., & Paauwe, J. (2004) · Applied Psychology · doi:10.1111/j.1464-0597.2004.00188.x · Cited by 434 · see citing works
The Ethics of AI Ethics: An Evaluation of Guidelines
Hagendorff, T. (2020) · PhilPapers (PhilPapers Foundation) · Cited by 394 · see citing works
Braddock, J. H., & McPartland, J. M. (1987) · Journal of Social Issues · doi:10.1111/j.1540-4560.1987.tb02329.x · Cited by 373 · 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 · cited 2× · see citing works
“While many individual characteristics are relevant to understanding technology ‘utilization’, I focus here on two human biases that could particularly undermine the ethical use of AI: algorithm aversion and automation bias (Bahner et al., 2008; Prahl & Van Swol, 2017).”
Background(2016) · CERN Document Server (European Organization for Nuclear Research) · Cited by 293 · see citing works
Bahner, J. E., Hüper, A.-D., & Manzey, D. (2008) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2008.06.001 · Cited by 279 · see citing works
Designing fair AI for managing employees in organizations: a review, critique, and design agenda
Robert, L. P., Pierce, C., Marquis, L., Kim, S., & Alahmad, R. (2020) · Human–Computer Interaction · doi:10.1080/07370024.2020.1735391 · Cited by 268 · see citing works
AI in talent acquisition: a review of AI-applications used in recruitment and selection
Albert, E. T. (2019) · Strategic HR Review · doi:10.1108/shr-04-2019-0024 · Cited by 243 · see citing works
Procedural Justice in Algorithmic Fairness
Lee, M. K., Jain, A., Jin, H., Ojha, S., & Kusbit, D. (2019) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3359284 · Cited by 236 · see citing works
Ethics of healthcare robotics: Towards responsible research and innovation
Stahl, B. C., & Coeckelbergh, M. (2016) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2016.08.018 · Cited by 235 · see citing works
A Framework for Understanding Unintended Consequences of Machine Learning
Suresh, H., & Guttag, J. V. (2019) · Cited by 229 · see citing works
Artificial Intelligence Techniques in Human Resource Management—A Conceptual Exploration
Strohmeier, S., & Piazza, F. (2015) · Intelligent Systems Reference Library · doi:10.1007/978-3-319-17906-3_7 · Cited by 224 · see citing works
Designing for human rights in AI
Aizenberg, E., & van den Hoven, J. (2020) · Big Data & Society · doi:10.1177/2053951720949566 · Cited by 220 · see citing works
Black-box artificial intelligence: an epistemological and critical analysis
Carabantes, M. (2019) · AI & Society · doi:10.1007/s00146-019-00888-w · Cited by 180 · see citing works
Andrews, L. (2019) · Public Administration · doi:10.1111/padm.12534 · Cited by 172 · see citing works
Human Judgment in algorithmic loops: Individual justice and automated <scp>decision‐making</scp>
Binns, R. (2022) · Regulation & Governance · doi:10.1111/rego.12358 · Cited by 134 · cited 2× · see citing works
“As noted earlier, this may occur when the individual merits of a case must be assessed and human value judgments must be made that can’t easily be specified through AI modelling (see Binns, 2020; Colson, 2019).”
BackgroundA Scoping Review of the Application of the Task-Technology Fit Theory
Spies, R., Grobbelaar, S. S. S., & Botha, A. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-44999-5_33 · Cited by 131 · see citing works
(2018) · Journal of the Association for Information Systems · Cited by 129 · see citing works
Pizer, J. C., Sears, B., & Mallory, C. (2012) · bepress Legal Repository · Cited by 125 · see citing works
Crawford, K. (2013) · Harvard business review · Cited by 102 · see citing works
Autonomy in surgical robots and its meaningful human control
Ficuciello, F., Tamburrini, G., Arezzo, A., Villani, L., & Siciliano, B. (2019) · Paladyn, Journal of Behavioral Robotics · doi:10.1515/pjbr-2019-0002 · Cited by 92 · see citing works
Langlois, R. N. (2003) · Journal of Economic Psychology · doi:10.1016/s0167-4870(02)00201-5 · Cited by 81 · see citing works
Beyond the bubble that is Robodebt: How governments that lose integrity threaten democracy
Braithwaite, V. A. (2020) · Australian Journal of Social Issues · doi:10.1002/ajs4.122 · Cited by 71 · see citing works
Making moral machines: why we need artificial moral agents
Formosa, P., & Ryan, M. (2020) · AI & Society · doi:10.1007/s00146-020-01089-6 · Cited by 71 · see citing works
The Principlism Debate: A Critical Overview
Davis, R. B. (1995) · Journal of Medicine and Philosophy · doi:10.1093/jmp/20.1.85 · Cited by 57 · cited 1× · see citing works
“Similarly, ethical assessments must also balance the trade-offs in meeting different ethical principles (Davis, 1995).”
BackgroundHow is new technology changing job design?
Gibbs, M., & Bazylik, S. (2017) · IZA World of Labor · doi:10.15185/izawol.344 · Cited by 57 · see citing works
Measuring leadership effectiveness in complex socio- technical systems
Hazy, J. K. (2006) · Cited by 56 · see citing works
Ajunwa, I., Crawford, K., & Ford, J. (2016) · The Journal of Law Medicine & Ethics · doi:10.1177/1073110516667943 · Cited by 56 · see citing works
Ethnic and gender discrimination in recruitment: Experimental evidence from Finland
Liebkind, K., Larja, L., & Brylka, A. (2016) · Journal of Social and Political Psychology · doi:10.5964/jspp.v4i1.433 · Cited by 56 · see citing works
Heikoop, D. D., Hagenzieker, M., Mecacci, G., Calvert, S. C., de Sio, F. S., & van Arem, B. (2019) · Theoretical Issues in Ergonomics Science · doi:10.1080/1463922x.2019.1574931 · Cited by 41 · see citing works
The Business Case for AI in HR: With Insights and Tips on Getting Started
Guenole, N., & Feinzig, S. L. (2018) · Goldsmiths (University of London) · Cited by 20 · see citing works
Bankins, S., & Formosa, P. (2021) · Redefining the Psychological Contract in the Digital Era · doi:10.1007/978-3-030-63864-1_4 · Cited by 19 · see citing works
Self-citationSturm, T., & Peters, F. (2020) · TUbilio (Technical University of Darmstadt) · Cited by 12 · see citing works
Lohn, A. J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2009.00802 · Cited by 11 · see citing works
Big data and human resource management
Scholz, T. M. (2019) · Edward Elgar Publishing eBooks · doi:10.4337/9781788112352.00008 · Cited by 8 · see citing works
On Meaningful Human Control in High-Stakes Machine-Human Partnerships
McCoy, L. G., Burkell, J., Card, D., Davis, B., Gichoya, J. W., Lepage, S., & Madras, D. (2019) · eScholarship (California Digital Library) · Cited by 3 · see citing works
Flagged first, then by citations
2 of the 63 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
The Ethical Implications of Artificial Intelligence (AI) For Meaningful Work
Bankins, S., & Formosa, P. (2023) · Journal of Business Ethics · doi:10.1007/s10551-023-05339-7 · Cited by 554 · see citing works
Self-citationREVIEWING THE ETHICAL IMPLICATIONS OF AI IN DECISION MAKING PROCESSES
Osasona, F., Amoo, O. O., Atadoga, A., Abrahams, T. O., Farayola, O. A., & Ayinla, B. S. (2024) · International Journal of Management & Entrepreneurship Research · doi:10.51594/ijmer.v6i2.773 · Cited by 188 · see citing works
Generative Artificial Intelligence in Education: Advancing Adaptive and Personalized Learning
Guettala, M., Bourekkache, S., Kazar, O., & Harous, S. (2024) · Acta Informatica Pragensia · doi:10.18267/j.aip.235 · Cited by 190 · see citing works
Does AI Debias Recruitment? Race, Gender, and AI’s “Eradication of Difference”
Drage, E., & Mackereth, K. (2022) · Philosophy & Technology · doi:10.1007/s13347-022-00543-1 · Cited by 132 · see citing works
Bujold, A., Roberge‐Maltais, I., Parent‐Rocheleau, X., Boasen, J., Sénécal, S., & Léger, P. (2023) · AI and Ethics · doi:10.1007/s43681-023-00325-1 · Cited by 183 · see citing works
Transformative AI in human resource management: enhancing workforce planning with topic modeling
Venugopalan, M., Madhavan, V., Prasad, R., & Raghu Raman, R. (2024) · Cogent Business & Management · doi:10.1080/23311975.2024.2432550 · Cited by 166 · see citing works
Ethical issues in the development of artificial intelligence: recognizing the risks
Kamila, M. K., & Jasrotia, S. S. (2023) · International Journal of Ethics and Systems · doi:10.1108/ijoes-05-2023-0107 · Cited by 105 · see citing works
Exploring how AI adoption in the workplace affects employees: a bibliometric and systematic review
Soulami, M., Benchekroun, S., & Galiulina, A. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1473872 · Cited by 101 · see citing works
Mori, M., Sassetti, S., Cavaliere, V. F., & Bonti, M. (2024) · Personnel Review · doi:10.1108/pr-03-2023-0257 · Cited by 119 · see citing works
Fenwick, A., Molnár, G., & Frangos, P. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1272823 · Cited by 124 · see citing works
Xiao, Q., Yan, J.-Q., & Bamber, G. J. (2023) · Person-centered review · doi:10.1108/pr-03-2023-0198 · Cited by 51 · see citing works
Tusquellas, N., Palau, R., & Santiago, R. (2024) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2024.100288 · Cited by 88 · see citing works
Shahzad, M. F., Xu, S., Naveed, W., Nusrat, S., & Zahid, I. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e21818 · Cited by 77 · see citing works
AI for the people? Embedding AI ethics in HR and people analytics projects
Bar-Gil, O., Ron, T., & Czerniak, O. (2024) · Technology in Society · doi:10.1016/j.techsoc.2024.102527 · Cited by 75 · see citing works
Check the box! How to deal with automation bias in AI-based personnel selection
Kupfer, C., Prassl, R., Fleiß, J., Malin, C., Thalmann, S., & Kubicek, B. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1118723 · Cited by 59 · see citing works
“Bankins (2021) in her ethical framework for AI in human resource management proposes that organizations must align actual AI use with its intended use by instructing employees on how to interact and rely on AI.”
BackgroundAI-Based Human Resource Management Tools and Techniques; A Systematic Literature Review
Madanchian, M., Taherdoost, H., & Mohamed, N. A. (2023) · Procedia Computer Science · doi:10.1016/j.procs.2023.12.039 · Cited by 89 · see citing works
Mahade, A., Elmahi, A., Alomari, K. M., & Abdalla, A. A. (2025) · Discover Sustainability · doi:10.1007/s43621-025-01114-y · Cited by 82 · see citing works
Olaniyan, O. P., Elufioye, O. A., Okonkwo, F. C., Udeh, C. A., Eleogu, T., & Olatoye, F. O. (2023) · International Journal of Management & Entrepreneurship Research · doi:10.51594/ijmer.v4i12.674 · Cited by 43 · see citing works
Revisiting the bullwhip effect: how can AI smoothen the bullwhip phenomenon?
Weisz, E., Herold, D. M., & Kummer, S. (2022) · The International Journal of Logistics Management · doi:10.1108/ijlm-02-2022-0078 · Cited by 48 · see citing works
Algorithmic Management: Its Implications for Information Systems Research
Cameron, L., Lamers, L., Leicht‐Deobald, U., Lutz, C., Meijerink, J., & Möhlmann, M. (2023) · Communications of the Association for Information Systems · doi:10.17705/1cais.05221 · Cited by 42 · see citing works
Politics by Automatic Means? A Critique of Artificial Intelligence Ethics at Work
Cole, M., Cant, C., Ustek-Spilda, F., & Graham, M. (2022) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2022.869114 · Cited by 30 · see citing works
Promoting Ethical Use of Generative AI in Education
Deng, X. (., & Joshi, K. D. (2024) · ACM SIGMIS Database: the DATABASE for Advances in Information Systems · doi:10.1145/3685235.3685237 · Cited by 34 · see citing works
Ethical aspects of AI use in the circular economy
Bashynska, I. (2025) · AI & Society · doi:10.1007/s00146-025-02436-1 · Cited by 48 · see citing works
A Bibliometric Analysis of Artificial Intelligence and Human Resource Management Studies
Morshidi, A. B., Satar, N. S. M., Azizan, A. A. D. A., Idris, R. Z., Idris, R., Radzi, M. S. M., Yusoff, S. M., & Sarjono, F. (2023) · Advances in human resources management and organizational development book series · doi:10.4018/979-8-3693-0039-8.ch006 · Cited by 24 · see citing works
Khan, M. I., Parahyanti, E., & Hussain, S. M. A. M. (2024) · Asian Journal of Logistics Management · doi:10.14710/ajlm.2024.24671 · Cited by 23 · see citing works
Ethical decision-making in IT governance: A review of models and frameworks
Farayola, O. A., & Olorunfemi, O. L. (2023) · International Journal of Science and Research Archive · doi:10.30574/ijsra.2024.11.2.0373 · Cited by 23 · see citing works
Employee involvement in AI-driven HR decision-making: A systematic review
Taslim, W. S., Rosnani, T., & Fauzan, R. (2025) · SA Journal of Human Resource Management · doi:10.4102/sajhrm.v23i0.2856 · Cited by 30 · see citing works
Dignity and use of algorithm in performance evaluation
Zhang, L., & Amos, C. (2023) · Behaviour and Information Technology · doi:10.1080/0144929x.2022.2164214 · Cited by 24 · see citing works
Benabou, A., & Touhami, F. (2025) · International journal of production management and engineering · doi:10.4995/ijpme.2025.21900 · Cited by 33 · see citing works
Tuffaha, M. (2023) · European Journal of Business and Innovation Research · doi:10.37745/ejbir.2013/vol11n43558 · Cited by 24 · see citing works
AI and HRM in Tourism and Hospitality in Egypt: Inevitability, Impact, and Future
Al‐Romeedy, B. S. (2024) · Springer eBooks · doi:10.1007/978-3-031-62369-1_13 · Cited by 21 · see citing works
Forecasting HR expenses: A review of predictive analytics in financial planning for HR
Nwaimo, C. S., Adegbola, A. E., Adegbola, M. D., & Adeusi, K. B. (2024) · International Journal of Management & Entrepreneurship Research · doi:10.51594/ijmer.v6i6.1169 · Cited by 19 · see citing works
Malik, A., Lirio, P., Budhwar, P. S., Nguyen, M., & Fauzi, M. A. (2025) · Personnel Review · doi:10.1108/pr-12-2024-1061 · Cited by 19 · see citing works
Exploring Opportunities for Artificial Intelligence in Organization Development
Park, S., Chai, D. S., Park, J. J., & Oh, J. (2024) · Human Resource Development Review · doi:10.1177/15344843241273231 · Cited by 18 · see citing works
Guggemos, J. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100260 · Cited by 22 · see citing works
Ethical AI in HR: A Case Study of Tech Hiring
Rao, S., & Zhao, T. (2025) · Journal of Computer Information Systems · doi:10.1080/08874417.2024.2446954 · Cited by 19 · see citing works
Yu, J. H., Ma, Z., & Zhu, L. (2023) · Information Technology and People · doi:10.1108/itp-04-2022-0271 · Cited by 17 · see citing works
Aldighrir, W. M. (2024) · Current Psychology · doi:10.1007/s12144-024-06862-0 · Cited by 15 · see citing works
Artificial Intelligence in Human Resource Management: A PRISMA-based Systematic Review
Benabou, A., & Touhami, F. (2025) · Acta Informatica Pragensia · doi:10.18267/j.aip.264 · Cited by 21 · see citing works
The impact of artificial intelligence on human resource management practices: An investigation
Ncube, T. R., Sishi, K. K., & Skinner, J. (2025) · SA Journal of Human Resource Management · doi:10.4102/sajhrm.v23i0.2960 · Cited by 14 · see citing works
Optimization of the environmental protection tax system design based on artificial intelligence
Zhang, J. (2023) · Frontiers in Environmental Science · doi:10.3389/fenvs.2022.1076158 · Cited by 15 · see citing works
AI-Driven Job Displacement and Economic Impacts
Ramarajan, M., Dinesh, A., Muthuraman, C., Rajini, J., Anand, T., & Segar, B. (2024) · Advances in business information systems and analytics book series · doi:10.4018/979-8-3693-2643-5.ch013 · Cited by 13 · see citing works
Impact of Artificial Intelligence (AI) on Human Resource Management (HRM)
-, R. G. (2024) · International Journal For Multidisciplinary Research · doi:10.36948/ijfmr.2024.v06i03.21444 · Cited by 12 · see citing works
Sustainable Supply Chain Management and Industry 5.0
Fatorachian, H. (2024) · Advances in logistics, operations, and management science book series · doi:10.4018/979-8-3693-2219-2.ch009 · Cited by 12 · see citing works
The Digital Age: Exploring the Intersection of AI/CI and Human Cognition and Social Interactions
Usmani, U. A., Happonen, A., & Watada, J. (2024) · Procedia Computer Science · doi:10.1016/j.procs.2024.06.268 · Cited by 11 · see citing works
Joshi, A., Singh, R., & Rani, S. (2024) · The International Journal of Education Management and Sociology · doi:10.58818/ijems.v3i3.133 · Cited by 13 · see citing works
Algorithmic ethics in AI-enabled workplace systems for food delivery employees
Zhao, H., Yuan, B., Wen, M., & Zhang, T. (2025) · Service Industries Journal · doi:10.1080/02642069.2025.2538071 · Cited by 11 · see citing works
The Ethics of Machine Learning in Human Resources: Navigating Fairness and Efficiency
Raja, L., & Manoharan, G. (2024) · International Conference on Contemporary Computing and Informatics (IC3I) · doi:10.1109/ic3i61595.2024.10828730 · Cited by 9 · see citing works
AI-Driven Human Resource Management: Enhancing Transparency and Security with Machine Learning
Sareddy, M. R., & Khan, S. (2025) · Journal of Artificial Intelligence and Capsule Networks · doi:10.36548/jaicn.2024.4.009 · Cited by 9 · see citing works
Molina, C. M., Pérez-Macías, N., Rey-Tienda, S., & López-Sanz, M. E. (2025) · Sustainable Technology and Entrepreneurship · doi:10.1016/j.stae.2025.100108 · Cited by 8 · see citing works
Peng, Y., & Krutasaen, W. (2022) · Wireless Communications and Mobile Computing · doi:10.1155/2022/8805010 · Cited by 8 · see citing works
RetractedAutomated Scoring of Asynchronous Interview Videos Based on Multi-Modal Window-Consistency Fusion
Lv, J., Chen, C., & Liang, Z. (2023) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2023.3294335 · Cited by 9 · see citing works
Impact of artificial intelligence on Human Resource Management
Lahoti, P. D. Y. (2023) · Journal for ReAttach Therapy and Developmental Diversities · doi:10.53555/jrtdd.v6i1.2839 · Cited by 8 · see citing works
The Use of Artificial Intelligence in International Decision-Making Processes in Project ManagementPreprint
Tubman, A. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4121200 · Cited by 8 · see citing works
Fioravante, R., & Vaccaro, A. (2024) · Humanistic Management Journal · doi:10.1007/s41463-024-00193-9 · Cited by 7 · see citing works
Herold, M., & Roedenbeck, M. (2025) · SAGE Open · doi:10.1177/21582440251361746 · Cited by 7 · see citing works
Managing Transparency Fairness Accountability in AI for Sustainable Human Resource Management
Setiawati, R., Kusmara, A., & Kuusk, T. (2025) · International Conference on Creative Communication and Innovative Technology (ICCIT) · doi:10.1109/iccit65724.2025.11166968 · Cited by 8 · see citing works
Criteria for AI Adoption in HR: Efficiency vs. Ethics
Madanchian, M., & Taherdoost, H. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.04.261 · Cited by 5 · see citing works
Nunes, J. R., Rita, P., Pinto, D. C., González‐Jiménez, H., Akdim, K., & Wagner, R. L. (2025) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2025.102940 · Cited by 6 · see citing works
Fifth industrial revolution and the future of education and employment
Dhakal, S. P. (2025) · Quality & Quantity · doi:10.1007/s11135-025-02345-x · Cited by 6 · see citing works
İnsan kaynakları yönetiminde yapay zekâ teknolojisinin benimsenmesi üzerine güç alanı analizi
Kişi, N., & Özer, M. A. (2024) · Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi · doi:10.33707/akuiibfd.1406096 · Cited by 6 · see citing works
Chmielewska-Muciek, D., Marzec, P., Jakubczak, J. K., & Futa, B. (2024) · Sustainability · doi:10.3390/su16166865 · Cited by 6 · see citing works
Optimizing Digital Market Decision-Making Through Artificial Intelligence Platforms
Chen, R., & Chen, Y. (2024) · Journal of Global Information Management · doi:10.4018/jgim.365908 · Cited by 11 · see citing works
O'Callaghan, M. (2023) · Cogent Psychology · doi:10.1080/23311908.2023.2258475 · Cited by 9 · see citing works
Wang, Z., & Wu, H. (2024) · Journal of the Knowledge Economy · doi:10.1007/s13132-024-02287-z · Cited by 5 · see citing works
Responsible Artificial Intelligence (AI) Governance
Kaur, J. (2024) · Advances in business strategy and competitive advantage book series · doi:10.4018/979-8-3693-3948-0.ch014 · Cited by 5 · see citing works
Arnestad, M. N., Bigman, Y., Solberg, E. A., & Gray, K. J. (2025) · International Journal of Selection and Assessment · doi:10.1111/ijsa.70028 · Cited by 8 · see citing works
Examining trends in AI ethics across countries and institutions via quantitative discourse analysis
Bar-Gil, O. (2025) · AI & Society · doi:10.1007/s00146-025-02673-4 · Cited by 5 · see citing works
Chandana, C. S., Sarkar, A., Deshmukh, K., Kulkarni, P., Acharjee, P. B., & Lourens, M. (2024) · International Conference on Innovative Practices in Technology and Management (ICIPTM) · doi:10.1109/iciptm59628.2024.10563736 · Cited by 5 · see citing works
Navigating the Ethical Frontier-Human Oversight in AI-Driven Decision-Making System
Tariq, M. U. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-6230-3.ch013 · Cited by 5 · see citing works
The Impact of Artificial Intelligence on Human Resource Management
Maota, T., & Naidoo, V. (2025) · IGI Global eBooks · doi:10.4018/979-8-3693-8679-8.ch016 · Cited by 5 · see citing works
Beyond aversion – principles of appropriate algorithmic decision-making in human resource management
Strohmeier, S., Becker, M., & Scheer-Weller, E. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128954 · Cited by 9 · see citing works
Artificial Intelligence and Emerging Risks in Occupational Safety and Health
Baraza, X., & Torrent‐Sellens, J. (2026) · Encyclopedia · doi:10.3390/encyclopedia6010025 · Cited by 5 · see citing works
Sustainable HRM in the age of analytics: capabilities, risks and a path forward
Yin, J. (2025) · Employee Relations · doi:10.1108/er-12-2024-0786 · Cited by 4 · see citing works
Blockchain and Ai-Based Smart Hr Management System for Secure and Transparent Employee Records
Singh, R., Neha, N., Singh, R. K., Bhatnagar, P., Kaushik, D., & Chauhan, R. (2025) · International Conference on Data Intelligence and Cognitive Informatics (ICDICI) · doi:10.1109/icdici66477.2025.11135283 · Cited by 4 · see citing works
Examining the Challenges of Adopting Modern Technologies in Public Sector Human Resource Management
Sani, S., & Mandina, S. P. (2024) · Advances in human resources management and organizational development book series · doi:10.4018/979-8-3693-2889-7.ch004 · Cited by 4 · see citing works
Design and Analysis of Human Resources Using Artificial Intelligence
Syed, S. M., Subbalakshmi, A. V. V. S., Singh, D. R., Emani, S., & Basava, R. K. (2023) · Journal of Law and Sustainable Development · doi:10.55908/sdgs.v11i9.829 · Cited by 4 · see citing works
CSA-DE-LR: enhancing cardiovascular disease diagnosis with a novel hybrid machine learning approach
Dedetürk, B. A., Dedetürk, B. K., & Bakır-Güngör, B. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2197 · Cited by 4 · see citing works
AI and Human Resources: Ethical Concerns and Potential Spots of Biases
Jalan, S., & Jena, L. K. (2025) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-83662-982-520251003 · Cited by 3 · see citing works
Beyond algorithms: Artificial intelligence driven talent identification with human insight
França, T. J. F., Mamede, H. S., Barroso, J., & Santos, V. (2025) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2025.200604 · Cited by 3 · see citing works
Kim, S. (2026) · Translational systems sciences · doi:10.1007/978-981-95-0622-4_6 · Cited by 4 · see citing works
Ethical Implications of AI-driven Digital Twin in Human Resources Management
Bhattacharjee, R. K., Chanda, S., & Mazumder, Z. (2026) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-83708-112-720261004 · Cited by 3 · see citing works
Srivastava, P., Mamodiya, U., Pandey, V., & Dutta, P. K. (2026) · Springer eBooks · doi:10.1007/978-3-032-08828-4_1 · Cited by 3 · see citing works
AI ethics strategies and practices in organizations: a scoping review
Marcoux, A. M. (2025) · International Journal of Ethics and Systems · doi:10.1108/ijoes-02-2024-0060 · Cited by 2 · see citing works
Electronic Digital Twin in Industry 5.0
Massaro, A. S. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-7994-3.ch005 · Cited by 3 · see citing works
Ethical Considerations in the Use of Deep Learning for HR Decision-Making
Singh, B. P., Neti, M., & Choudhury, S. (2024) · IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT) · doi:10.1109/ic2pct60090.2024.10486757 · Cited by 3 · see citing works
Inteligência artificial e tomada de decisão ética no setor público
Bergue, S. T. (2024) · Gestão org · doi:10.51359/1679-1827.2024.262501 · Cited by 3 · see citing works
Human Resource Management in the Digital Era
Bahri, M. I., Agustina, T. S., & Ridha, A. E. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-1005-3.ch003 · Cited by 3 · see citing works
Perceptual interventions ameliorate statistical discrimination in learning agents
Duéñez‐Guzmán, E. A., Comanescu, R., Mao, Y., McKee, K. R., Coppin, B., Sadedin, S., Chiappa, S., Vezhnevets, A. S., Bakker, M. A., Bachrach, Y., et al. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2319933121 · Cited by 2 · see citing works
Pan, S. (2025) · Information Technology and People · doi:10.1108/itp-05-2024-0708 · Cited by 2 · see citing works
Nogues, A. R. (2025) · AI & Society · doi:10.1007/s00146-025-02581-7 · Cited by 3 · see citing works
AI in human resources: efficiency, ethics, and emerging challenges
Majumder, S., Salman, S., & Dey, N. (2025) · AI and Ethics · doi:10.1007/s43681-025-00862-x · Cited by 2 · see citing works
Dark Side of Artificial Intelligence: A Meta‐Analytic Review
Rohit, K., & Shankar, A. (2026) · Journal of Consumer Behaviour · doi:10.1002/cb.70144 · Cited by 3 · see citing works
Integrating socio-technical perspectives in digital transformations in sales: a research agenda
Sathiskumar, N. N., Andersen, P. H., Rangarajan, D., & Bekamiri, H. (2026) · The Journal of Marketing Theory and Practice · doi:10.1080/10696679.2026.2681530 · Cited by 2 · see citing works
Universal design in psychometric testing
Doyle, N. (2023) · Assessment and Development Matters · doi:10.53841/bpsadm.2023.15.2.4 · Cited by 2 · see citing works
Artificial Intelligence is a Blessing or Curse for The Future Human Resource: A Conceptual Analysis
Muhammad, J., Jaweria, & Sikandar, P. (2023) · Pakistan Social Sciences Review · doi:10.35484/pssr.2023(7-iv)27 · Cited by 2 · see citing works
The transformative role of artificial intelligence in human resources
Žibret, K. (2024) · Mednarodno inovativno poslovanje = Journal of Innovative Business and Management · doi:10.32015/jibm.2024.16.1.5 · Cited by 2 · see citing works
Socially Responsible Application of Artificial Intelligence in Human Resources Management
Gričnik, A. M., Mulej, M., & Žižek, S. Š. (2024) · Advances in human and social aspects of technology book series · doi:10.4018/979-8-3693-3334-1.ch004 · Cited by 5 · see citing works
Governing Technology: A MacIntyrean Approach to the Ethics of Artificial Intelligence
Ruiz, P. G. (2024) · Ethical economy · doi:10.1007/978-3-031-78888-8_9 · Cited by 2 · see citing works
AI Integration in Public Administration
Asrifan, A., Akbar, A., Nur, M., Amu, R. W., & Pajarianto, H. (2025) · Advances in public policy and administration (APPA) book series · doi:10.4018/979-8-3373-2272-8.ch003 · Cited by 2 · see citing works
- Authors
- Bankins, S.
- Affiliations
- Macquarie University (AU)
- Corresponding author
- Bankins, Sarah
- ORCID
- Bankins, Sarah
- Venue
- Ethics and Information Technology
- Published
- 2021-11-25
- Volume
- 23
- Issue
- 4
- Pages
- 841-854
- ISSN
- 1388-1957 (ISSN-L)
- 1572-8439
- OpenAlex
- W3216241100
- Cited by
- 181
- References
- 63
- Citations by year
- 2026: 50 · 2025: 56 · 2024: 43 · 2023: 24 · 2022: 8
- FWCI
- 18.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Ethics and Information Technology (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Keywords
- artificial intelligence, human resource management, ethical AI, decision-making framework, task-technology fit, human-AI collaboration, recruitment and selection, staff allocation, career coaching
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
