From AI ethics principles to data science practice: A reflection and a gap analysis based on recent frameworks and practical experience
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?
Organizations establish ethical guidelines for AI usage through a multifaceted process involving identification of core ethical principles, development of practical frameworks, and implementation of governance models.
“Organizations establish ethical guidelines for AI usage by engaging in a multifaceted process that involves the identification of core ethical principles, the development of practical frameworks, and the implementation of governance models that ensure adherence to these guidelines throughout the AI system's lifecycle [18,19].”
From AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities (2024) · cites this paper as [19]
Cites
Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., et al. (2020) · Information Fusion · doi:10.1016/j.inffus.2019.12.012 · Cited by 10,423 · 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 1× · see citing works
“Their process is based on the AI for social good (AI4SG) values [23], which relate to the ethical principles in the Ethical Guidelines for Trustworthy AI [1].”
MethodPrinciples alone cannot guarantee ethical AI
Mittelstadt, B. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0114-4 · Cited by 1,886 · cited 4× · see citing works
“Yet, to confuse a priori consensus with a meaningful consensus [43] is a fallacy that would not help ethics achieve their ends as a vital part of the deliberative process.”
BackgroundInfluentialThe Handbook of science and technology studies
(2008) · Choice Reviews Online · doi:10.5860/choice.45-5536 · Cited by 1,769 · see citing works
Mikalef, P., & Gupta, M. (2021) · Information & Management · doi:10.1016/j.im.2021.103434 · Cited by 1,700 · see citing works
The Brussels Effect: How the European Union Rules the World
Bradford, A. (2020) · doi:10.1093/oso/9780190088583.001.0001 · Cited by 1,349 · see citing works
Investigating Information Systems with Action Research
Baskerville, R. (1999) · Communications of the Association for Information Systems · doi:10.17705/1cais.00219 · Cited by 1,123 · see citing works
Artificial Intelligence and Business Value: a Literature Review
Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022) · Information Systems Frontiers · doi:10.1007/s10796-021-10186-w · Cited by 1,046 · cited 1× · see citing works
“Such studies document further the challenge in integrating AI systems within existing organizational structures, and show that not every AI-facilitated solution brings about the expected added (business) value [20].”
BackgroundFjeld, J., Achten, N., Hilligoss, H., Nagy, A., & Srikumar, M. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3518482 · Cited by 998 · see citing works
Artificial Intelligence, Values, and Alignment
Gabriel, I. (2020) · Minds and Machines · doi:10.1007/s11023-020-09539-2 · Cited by 896 · cited 2× · see citing works
“1 The third wave of scholarship on ethical AI, which builds on the first two by exploring how to turn AI principles into actionable data science practice and governance (see for instance [10, 12, 24, 29, 62]), examines as such the spectrum of applicability of AI ethics in real-world cases [45], highlights issues of st…”
BackgroundMorley, J., Floridi, L., Kinsey, L., & Elhalal, A. (2020) · Science and Engineering Ethics · doi:10.1007/s11948-019-00165-5 · Cited by 882 · cited 6× · see citing works
“The HLEG requirements for trustworthy AI are mapped onto the general AI-lifecycle stages, for which we use the AI-lifecycle typology of Morley [45] that guides machine learning (ML)—a specific type of AI—developers through the phases of algorithmic development.”
BackgroundMethodInfluentialMittelstadt, B., Russell, C., & Wachter, S. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency · doi:10.1145/3287560.3287574 · Cited by 794 · 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
Shneiderman, B. (2020) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3419764 · Cited by 768 · see citing works
Greene, D., Hoffmann, A. L., & Stark, L. (2019) · Proceedings of the Annual Hawaii International Conference on System Sciences · doi:10.24251/hicss.2019.258 · Cited by 386 · see citing works
Handbook of Ethics, Values, and Technological Design
van den Hoven, J., Vermaas, P. E., & van de Poel, I. (2015) · Springer eBooks · doi:10.1007/978-94-007-6970-0 · Cited by 314 · see citing works
Ryan, M., & Stahl, B. C. (2021) · Journal of Information, Communication and Ethics in Society · doi:10.1108/jices-12-2019-0138 · Cited by 310 · cited 1× · see citing works
“The latter have resulted in the abundance of ethical frameworks for the development of socially beneficial or human-centred AI and its deployment (what we call the first wave of literature on ethical AI), as well as in efforts to assess the potential normative consensus and convergence [22, 45, 55] of these frameworks…”
BackgroundOwning Ethics: Corporate Logics, Silicon Valley, and the Institutionalization of Ethics
Metcalf, J., Moss, E., & boyd, D. (2019) · Social research · doi:10.1353/sor.2019.0022 · Cited by 280 · see citing works
Translating Values into Design Requirements
van de Poel, I. (2013) · Philosophy of Engineering and Technology · doi:10.1007/978-94-007-7762-0_20 · Cited by 273 · see citing works
Strengthening legal protection against discrimination by algorithms and artificial intelligence
Zuiderveen Borgesius, F. J. (2020) · The International Journal of Human Rights · doi:10.1080/13642987.2020.1743976 · Cited by 267 · see citing works
Mapping value sensitive design onto AI for social good principles
Umbrello, S., & van de Poel, I. (2021) · AI and Ethics · doi:10.1007/s43681-021-00038-3 · Cited by 251 · see citing works
Beyond the promise: implementing ethical AI
Eitel-Porter, R. (2021) · AI and Ethics · doi:10.1007/s43681-020-00011-6 · Cited by 245 · cited 1× · see citing works
“As a result, there are many barriers for scaling AI deployments [19], and especially so for considering ethical principles such as fairness [31].”
BackgroundRequirements Engineering for Machine Learning: Perspectives from Data Scientists
Vogelsang, A., & Borg, M. (2019) · IEEE International Requirements Engineering Conference Workshops (REW) · doi:10.1109/rew.2019.00050 · Cited by 238 · see citing works
ETHICS AS AN ESCAPE FROM REGULATION.: FROM “ETHICS-WASHING” TO ETHICS-SHOPPING?
WAGNER, B. (2018) · BEING PROFILED · doi:10.2307/j.ctvhrd092.18 · Cited by 228 · see citing works
On Technological Determinism: A Typology, Scope Conditions, and a Mechanism
Dafoe, A. (2015) · Science, Technology, & Human Values · doi:10.1177/0162243915579283 · Cited by 221 · 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
AI ethics should not remain toothless! A call to bring back the teeth of ethics
Rességuier, A., & Rodrigues, R. (2020) · Big Data & Society · doi:10.1177/2053951720942541 · Cited by 214 · see citing works
Don’t ask if artificial intelligence is good or fair, ask how it shifts power
Kalluri, P. (2020) · Nature · doi:10.1038/d41586-020-02003-2 · Cited by 213 · see citing works
Responsible AI for Digital Health: a Synthesis and a Research Agenda
Trocin, C., Mikalef, P., Papamitsiou, Z., & Conboy, K. (2023) · Information Systems Frontiers · doi:10.1007/s10796-021-10146-4 · Cited by 205 · see citing works
The algorithm audit: Scoring the algorithms that score us
Brown, S., Davidovic, J., & Hasan, A. (2021) · Big Data & Society · doi:10.1177/2053951720983865 · Cited by 204 · see citing works
Organisational responses to the ethical issues of artificial intelligence
Stahl, B. C., Antoniou, J., Ryan, M., Macnish, K., & Jiya, T. (2021) · AI & Society · doi:10.1007/s00146-021-01148-6 · Cited by 194 · see citing works
Lessons learned from AI ethics principles for future actions
Hickok, M. (2021) · AI and Ethics · doi:10.1007/s43681-020-00008-1 · Cited by 168 · cited 3× · see citing works
“1 The third wave of scholarship on ethical AI, which builds on the first two by exploring how to turn AI principles into actionable data science practice and governance (see for instance [10, 12, 24, 29, 62]), examines as such the spectrum of applicability of AI ethics in real-world cases [45], highlights issues of st…”
BackgroundAttributions of ethical responsibility by Artificial Intelligence practitioners
Orr, W., & Davis, J. L. (2020) · Information Communication & Society · doi:10.1080/1369118x.2020.1713842 · Cited by 163 · see citing works
Data Science as Political Action: Grounding Data Science in a Politics of Justice
Green, B. (2020) · Journal of Social Computing · doi:10.23919/jsc.2021.0029 · Cited by 157 · see citing works
On the Governance of Artificial Intelligence through Ethics Guidelines
LARSSON, S. (2020) · Asian Journal of Law and Society · doi:10.1017/als.2020.19 · Cited by 156 · see citing works
Hickman, E., & Petrin, M. (2020) · European Business Organization Law Review · doi:10.1007/s40804-021-00224-0 · Cited by 155 · see citing works
AI WATCH. Defining Artificial Intelligence
Samoili, S., Montserrat, L. C., Emilia, G. G., Giuditta, D. P., Martínez‐Plumed, F., & Blagoj, D. (2020) · Joint Research Centre (European Commission) · doi:10.2760/382730 · Cited by 154 · see citing works
Brun, Y., & Meliou, A. (2018) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3236024.3264838 · Cited by 138 · see citing works
Actionable Principles for Artificial Intelligence Policy: Three Pathways
Stix, C. (2021) · Science and Engineering Ethics · doi:10.1007/s11948-020-00277-3 · Cited by 129 · see citing works
Beyond checklists: toward an ethical-constructive technology assessment
Kiran, A. H., Oudshoorn, N., & Verbeek, P.-P. (2015) · Journal of Responsible Innovation · doi:10.1080/23299460.2014.992769 · Cited by 124 · see citing works
Artificial intelligence: From ethics to law
Robles-Carrillo, M. (2020) · Telecommunications Policy · doi:10.1016/j.telpol.2020.101937 · Cited by 108 · see citing works
Hagendorff, T. (2021) · AI and Ethics · doi:10.1007/s43681-021-00122-8 · Cited by 105 · see citing works
Veale, M. (2020) · European Journal of Risk Regulation · doi:10.1017/err.2019.65 · Cited by 85 · see citing works
Operationalizing AI ethics principles
Canca, C. (2020) · Communications of the ACM · doi:10.1145/3430368 · Cited by 79 · see citing works
Operationalizing human values in software: a research roadmap
Mougouei, D., Perera, H., Hussain, W., Shams, R. A., & Whittle, J. (2018) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3236024.3264843 · Cited by 78 · see citing works
A roadmap for ethics-aware software engineering
Aydemir, F. B., & Dalpiaz, F. (2018) · doi:10.1145/3194770.3194778 · Cited by 76 · see citing works
Beyond mystery: Putting algorithmic accountability in context
Reddy, E. A., Cakici, B., & Ballestero, A. (2019) · Big Data & Society · doi:10.1177/2053951719826856 · Cited by 60 · see citing works
Facebook’s ethical failures are not accidental; they are part of the business model
Lauer, D. (2021) · AI and Ethics · doi:10.1007/s43681-021-00068-x · Cited by 58 · see citing works
Making Values Explicit During the Design Process
Steen, M., & van de Poel, I. (2012) · IEEE Technology and Society Magazine · doi:10.1109/mts.2012.2225671 · Cited by 26 · see citing works
Survey of EU ethical guidelines for commercial AI: case studies in financial services
Huang, J. Y., Gupta, A., & Youn, M. (2021) · AI and Ethics · doi:10.1007/s43681-021-00048-1 · Cited by 18 · see citing works
Trustworthy AI for the People?
Figueras, C., Verhagen, H., & Pargman, T. C. (2021) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3461702.3462470 · Cited by 8 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Defining organizational AI governance
Mäntymäki, M., Minkkinen, M., Birkstedt, T., & Viljanen, M. (2022) · AI and Ethics · doi:10.1007/s43681-022-00143-x · Cited by 378 · see citing works
“Georgieva and her colleagues [8] call this the “third wave of scholarship on ethical AI,” which focuses on turning AI principles into actionable practice and governance.”
BackgroundWhat is Human-Centered about Human-Centered AI? A Map of the Research Landscape
Capel, T., & Brereton, M. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580959 · Cited by 228 · see citing works
Artificial Intelligence for Surface‐Enhanced Raman Spectroscopy
Bi, X., Lin, L. L., Chen, Z., & Ye, J. (2023) · Small Methods · doi:10.1002/smtd.202301243 · Cited by 152 · see citing works
AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities
Wu, C., Zhang, H., & Carroll, J. M. (2024) · Future Internet · doi:10.3390/fi16100354 · Cited by 99 · see citing works
“Organizations establish ethical guidelines for AI usage by engaging in a multifaceted process that involves the identification of core ethical principles, the development of practical frameworks, and the implementation of governance models that ensure adherence to these guidelines throughout the AI…”
Lin, X., Wang, Z., Zhou, W., Luo, G., Hwang, G., Zhou, Y., Wang, J., Hu, Q., Li, W., & Liang, Z. (2023) · Computers & Education · doi:10.1016/j.compedu.2023.104813 · Cited by 64 · see citing works
Ethical AI in practice: Balancing technological advancements with human values
Ayinla, B. S., Amoo, O. O., Atadoga, A., Abrahams, T. O., Osasona, F., & Farayola, O. A. (2024) · International Journal of Science and Research Archive · doi:10.30574/ijsra.2024.11.1.0218 · Cited by 62 · see citing works
Maiti, M., Kayal, P., & Vujko, A. (2025) · Future Business Journal · doi:10.1186/s43093-025-00462-5 · Cited by 94 · see citing works
Olateju, O. O., Okon, S. U., Olaniyi, O. O., Samuel-Okon, A. D., & Asonze, C. U. (2024) · Journal of Engineering Research and Reports · doi:10.9734/jerr/2024/v26i71206 · Cited by 52 · see citing works
Blanchard, A., Thomas, C., & Taddeo, M. (2024) · Ai & Society · doi:10.1007/s00146-024-01866-7 · Cited by 18 · see citing works
“…for the specification of AI ethics guidelines (Alshammari and Simpson 2017; Gasser and Almeida 2017; Butcher and Beridze 2019; Jobin et al. 2019; Leslie 2019; Krafft et al. 2020; Hickok 2021; Metcalf et al. 2021; Seppälä et al. 2021; Stix 2021; Ayling and Chapman 2022; Georgieva et al. 2022).”
Taddeo, M., Blanchard, A., & Thomas, C. (2024) · Philosophy & Technology · doi:10.1007/s13347-024-00710-6 · Cited by 22 · see citing works
“This has motivated a shift from the what to the how in AI ethics research (Floridi, 2019, 185), referred to as the “third wave of scholarship on ethical AI” (Georgieva et al., 2022).”
Banala, S., & Whig, P. (2024) · Advances in human and social aspects of technology book series · doi:10.4018/979-8-3693-4147-6.ch001 · Cited by 33 · see citing works
A five-layer framework for AI governance: integrating regulation, standards, and certification
Agarwal, A., & Nene, M. J. (2025) · Transforming Government People Process and Policy · doi:10.1108/tg-03-2025-0065 · Cited by 56 · see citing works
Kong, S. C., & Zhu, J. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100447 · Cited by 47 · see citing works
The Ethics of Artificial Intelligence in Defence
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.001.0001 · Cited by 16 · see citing works
Hohma, E., & Lütge, C. (2023) · AI · doi:10.3390/ai4040046 · Cited by 28 · see citing works
Crossing the principle–practice gap in AI ethics with ethical problem-solving
Corrêa, N. K., Santos, J. W., Galvão, C., Pasetti, M., Schiavon, D. E. B., Naqvi, F., Hossain, R., & Oliveira, N. F. D. (2024) · AI and Ethics · doi:10.1007/s43681-024-00469-8 · Cited by 21 · see citing works
“The scarcity of practical tools to address ethical matters within AI is a significant and concerning gap in AI ethics [3, 32, 111, 112].”
Operationalizing Explainable Artificial Intelligence in the European Union Regulatory Ecosystem
Nannini, L., Alonso, J. M., Catalá, A., Lama, M., & Barro, S. (2024) · IEEE Intelligent Systems · doi:10.1109/mis.2024.3383155 · Cited by 30 · see citing works
Evaluation of AI-Based Digital Assistants in Smart Manufacturing
Bousdekis, A., Mentzas, G. N., Apostolou, D., & Wellsandt, S. (2022) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-16411-8_58 · Cited by 19 · see citing works
Harle, S. M., Bhagat, A. P., Ingole, R., & Zanjad, N. S. (2025) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-025-10276-x · Cited by 19 · see citing works
Chan, A., Rahimi‐Ardabili, H., Rogers, W., & Coiera, E. W. (2025) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaf167 · Cited by 17 · see citing works
Herzog, C., & Blank, S. (2024) · Journal of Responsible Innovation · doi:10.1080/23299460.2024.2431350 · Cited by 17 · see citing works
Ethical AI in Social Sciences Research: Are We Gatekeepers or Revolutionaries?
Runcan, R., Hațegan, V.-P., Toderici, O. F., Croitoru, G., Gavrilă-Ardelean, M., Cuc, L. D., Rad, D., Costin, A., & Dughi, T. S. (2025) · Societies · doi:10.3390/soc15030062 · Cited by 15 · see citing works
Enacting Responsible AI: A Configurational Analysis of AI Principles in Practice
Akbarighatar, P., Pappas, I. O., Purao, S., & Vassilakopoulou, P. (2025) · Information Systems Frontiers · doi:10.1007/s10796-025-10618-x · Cited by 13 · see citing works
“Specifically, there is research conceptualising prescriptive frameworks aiming to establish normative guidance for organizations (Georgieva et al., 2022; Mäntymäki et al., 2022; Papagiannidis et al., 2025).”
Skeja, A., & Sadiku-Dushi, N. (2025) · Leadership & Organization Development Journal · doi:10.1108/lodj-06-2025-0530 · Cited by 17 · see citing works
The ethical implications of Chatbot developments for conservation expertise
Sworna, Z. T., Urzedo, D., Hoskins, A. J., & Robinson, C. (2024) · AI and Ethics · doi:10.1007/s43681-024-00460-3 · Cited by 17 · see citing works
“Implementing transparent and inclusive methodologies by developers and users [44] that actively seek out and incorporate various voices will help mitigate the risk of unintentional over-sight associated with the application of chatbot-generated information in expert elicitation processes [45].”
TACKLING ECONOMIC INEQUALITIES THROUGH BUSINESS ANALYTICS: A LITERATURE REVIEW
Adaga, E. M., Egieya, Z. E., Ewuga, S. K., Abdul, A. A., & Abrahams, T. O. (2024) · Computer Science & IT Research Journal · doi:10.51594/csitrj.v5i1.702 · Cited by 11 · see citing works
Multidimensional Perspective to Data Preprocessing for Model Cognition Verity
Ajakwe, S. O., Deji-Oloruntoba, O. O., Olatunbosun, S. O., Duorinaah, F. X., & Bayode, I. A. (2024) · Advances in systems analysis, software engineering, and high performance computing book series · doi:10.4018/979-8-3693-3609-0.ch002 · Cited by 11 · see citing works
Buijsman, S., Klenk, M., & van den Hoven, J. (2025) · Cambridge University Press eBooks · doi:10.1017/9781009367783.005 · Cited by 11 · see citing works
Distribution of Forward-Looking Responsibility in the EU Process on AI Regulation
Hedlund, M. (2022) · Frontiers in Human Dynamics · doi:10.3389/fhumd.2022.703510 · Cited by 11 · see citing works
Wang, T., & Long, Y. (2025) · Acta Psychologica · doi:10.1016/j.actpsy.2025.105904 · Cited by 11 · see citing works
Jin, D. (2023) · International Hospitality Review · doi:10.1108/ihr-06-2023-0033 · Cited by 10 · see citing works
Nemat, A., Becker, S. J., Lucas, S., Thomas, S. C., Gadea, I., & Charton, J. (2023) · Minds and Machines · doi:10.1007/s11023-023-09654-w · Cited by 5 · see citing works
“…will have to be multifaceted, selecting and combining different tools and approaches to suit the specific situation as well as the organisation and its component bodies, teams and other structural and procedural specificities (Mökander et al., 2021; Morley et al., 2021a; Georgieva et al., 2022).”
Vindigni, G. (2024) · European Journal of Contemporary Education and E-Learning · doi:10.59324/ejceel.2024.2(4).10 · Cited by 15 · see citing works
“Such biases have the potential to undermine the validity of scientific results and could further exacerbate existing social disparities (Georgieva et al., 2022; Cabitza et al., 2020).”
BackgroundVicnesh, J., Salvi, M., Hagiwara, Y., Yee, H. Y., Mir, H., Barua, P. D., Chakraborty, S., Molinari, F., & Acharya, U. R. (2024) · IEEE Access · doi:10.1109/access.2024.3522251 · Cited by 9 · see citing works
“Additionally, Georgieva et al. [58] concur on the need for clear governance models that underscore responsibility and influence the implementation of ethical practices in data science.”
Relational Ethics and Structural Epistemic Injustice of AI in Medicine
Herzog, C., & Branford, J. (2025) · Philosophy & Technology · doi:10.1007/s13347-025-00987-1 · Cited by 11 · see citing works
“Accordingly, there is a need to face and bridge the so-called principles-to-practice gap (e.g., Georgieva et al., 2022) of translating ethical reflection into effective operationalization 2 .”
A Conceptual Framework for AI Governance in Public Administration – A Smart Governance Perspective
Rajagopal, M., Ramkumar, S., Ramar, G., Mansurali, A., & Karuppasamy, S. K. (2023) · International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) · doi:10.1109/i-smac58438.2023.10290366 · Cited by 10 · see citing works
“However, this also raises ethical concerns about the use of AI technology in the public sector as humans may be replaced [18-19].”
BackgroundData Ethics Emergency Drill: A Toolbox for Discussing Responsible AI for Industry Teams
Hanschke, V. A., Rees, D., Alanyali, M., Hopkinson, D., & Marshall, P. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642402 · Cited by 7 · see citing works
Developing a framework for addressing ethical challenges in generative AI
Lucas, S., Heinitz, R. M., Becker, S. J., & Charton, J. E. (2025) · Journal of Information Technology Case and Application Research · doi:10.1080/15228053.2025.2558443 · Cited by 7 · see citing works
“…the ethical discourse of GAI or AI more broadly (Al-Kfairy et al., 2024; Ferrara, 2024; Floridi, 2012; Floridi & Taddeo, 2016) yet increasingly concentrates on bridging the “principles to practice gap” (Corr ê a et al., 2024; Georgieva et al., 2022; Mittelstadt, 2019; Morley et al., 2020).”
Artificial Intelligence for Social Good
Oyenuga, M. O. (2025) · African Journal of Economics and Sustainable Development · doi:10.52589/ajesd-0j428jii · Cited by 5 · see citing works
McGrath, Q. P., Hevner, A. R., & de Vreede, G. (2025) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2025.3565221 · Cited by 8 · see citing works
“First, the “principles-to-practice” gap is a recognized problem, and while many researchers have proposed solutions that include frameworks, toolkits, and guidelines [6], [7], [56], [57], [61], their lack of organizational adoption persists [41], [62], [63], [64].”
Intervenability as a Design Requirement for Autonomy and Oversight within Human-Centered AI
Herrmann, T. A. (2025) · Progress in IS · doi:10.1007/978-3-031-83512-4_9 · Cited by 5 · see citing works
“Georgieva et al. [6, p. 706] provide an overview of 13 categories of oversight; it includes, for example, a stop button that can be used to cancel a process.”
Comparing Socio-technical Design Principles with Guidelines for Human-Centered AI
Herrmann, T. A. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-60611-3_5 · Cited by 5 · see citing works
The problem of fairness in tools for algorithmic fairness
Sun, X.-Y., Ye, B., & Xia, B.-H. (2024) · AI and Ethics · doi:10.1007/s43681-024-00533-3 · Cited by 4 · see citing works
“…relying solely on these “static” ethical principles is insufficient to ensure the ethical commitment of artificial intelligence technologies and call for fundamental changes in the regulatory framework, as well as the operationalization of ethical principles through technical practices [22, 52].”
Operationalising digital ethics: establishment of an ethics evaluation tool for data analytics
Charton, J., Lucas, S., Vogd, W., Halter, W., & Becker, S. J. (2025) · Ai & Society · doi:10.1007/s00146-025-02621-2 · Cited by 3 · see citing works
“…codes and guidelines intended to navigate these challenges and bridge what has become known as the “principles to practice gap” (Corrêa et al. 2024; Georgieva et al. 2022; Mökander et al. 2023; Morley et al. 2020; Mittelstadt 2019), it has become apparent that these measures are not universally…”
We need better images of AI and better conversations about AI
Steen, M., Timan, T., van Diggelen, J., & Vethman, S. (2024) · AI & Society · doi:10.1007/s00146-024-02101-z · Cited by 4 · see citing works
“It will be interesting to see which person can take the initiatives and at what level of responsibility (Georgieva et al. 2022), and whether there is sufficient room and agency for project team members to question and critique, e.g., the Error Matrix.”
Self-citationEthical Considerations in Data Mining and Analytics
Kaushik, P., Sharma, K., Mahawar, M. K., Wasim, J., Dey, G., & Nibiya, S. A. (2024) · International Conference on Advances in Computing, Communication and Networking (ICAC2N) · doi:10.1109/icac2n63387.2024.10895012 · Cited by 4 · see citing works
“Georgieva et al. (2022) analyze the gap between AI ethics principles & data science practices, providing a reflection on how ethical frameworks are applied & the challenges faced in real-world implementations [6].”
Katirai, A., & Nagato, Y. (2024) · AI and Ethics · doi:10.1007/s43681-024-00477-8 · Cited by 5 · see citing works
“A focus on human-centricity can be seen to be an alternative to this, though the extent to which humans should be involved throughout ‘the loop’ remains an open question [35].”
Taddeo, M., & Floridi, L. (2025) · doi:10.1002/9781394240821.ch1 · Cited by 4 · see citing works
Design Principles for Human-Centred Explainable AI: A Scoping Review
Hughes, N. G. J., Jia, Y., Sujan, M. A., Lawton, T., Habli, I., & McDermid, J. A. (2025) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3771720 · Cited by 3 · see citing works
Wang, D., Zhang, Q., & Zhang, Y. (2024) · International Conference on Computer Science and Technologies in Education (CSTE) · doi:10.1109/cste62025.2024.00007 · Cited by 3 · see citing works
“The ethical literacy of human beings, as the subject of technology use, is a moral guarantee for the rational use of AI technology [2].”
BackgroundAI Regulation in the EU: The Future Interplay Between Frameworks
Schütte, B. (2023) · YSEC yearbook of socio-economic constitutions · doi:10.1007/16495_2023_64 · Cited by 3 · see citing works
Langlois, L., Dilhac, M.-A., Dratwa, J., Ménissier, T., Ganascia, J., Weinstock, D., Bégin, L., & Marchildon, A. (2023) · doi:10.61737/mdhp6080 · Cited by 3 · see citing works
Ethical Pluralism in AI Policy: A Framework for Islamic Integration into Global AI Governance
Muchtasor, N. S. (2025) · Sinergi International Journal of Islamic Studies · doi:10.61194/ijis.v3i3.897 · Cited by 2 · see citing works
Chauhan, M., Whale, J. J., & Rahimi, R. (2026) · Strategy and Leadership · doi:10.1108/sl-09-2025-0331 · Cited by 2 · see citing works
Explainability in Process Mining: A Framework for Improved Decision-Making
Nannini, L. (2023) · AAAI/ACM Conference on AI, Ethics, and Society · doi:10.1145/3600211.3604729 · Cited by 3 · see citing works
“Yet, this so-called “first wave” of AI ethics publications often offered ambiguous if not conflictual terminology, lacking empirical benchmarks [1, 10]: this calls for the current advancements of a “second wave” of AI ethics to focus on empirical and comprehensive experimentations for the AI systems’ lifecycle [13, 17…”
BackgroundJust War Theory and the Permissibility of Autonomous Weapons Systems
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.003.0008 · Cited by 1 · see citing works
Smuha, N. A. (2025) · Cambridge University Press eBooks · doi:10.1017/9781009367783.002 · Cited by 1 · see citing works
Reinhart, W. F., Williams, R., Solnosky, R. L., & Napolitano, K. (2025) · doi:10.18260/3-1-1153-36075 · Cited by 1 · see citing works
Darwich, K. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-0129-7.ch005 · Cited by 1 · see citing works
AI Ethicist in Action: Strategies for Operationalising AI Ethics
Carnevale, A. (2025) · Springer eBooks · doi:10.1007/978-3-032-05526-2_4 · Cited by 1 · see citing works
Learning Analytics, Artificial Intelligence, and the Future of Democratic Curricular Governance
Carrión, J., Jaramillo, C., & Villarreal, S. N. C. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-4480-5.ch015 · Cited by 1 · see citing works
Jha, A. K., & Leahy, E. (2023) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-50188-3_2 · Cited by 1 · see citing works
van den Berg, M., Gerlings, J., & Kim, J. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-50485-3_9 · Cited by 1 · see citing works
Martins, R., de Sousa, L. C., Fadel, A. S., da Silva, C. L., Bubniak, M. J., Travagin, I. C., Silva, V. A. F., Maiola, G. G. D. C., Mulinari, B. M., da Costa, C. H., et al. (2024) · Brazilian Archives of Biology and Technology · doi:10.1590/1678-4324-2024231238 · Cited by 1 · see citing works
Bousdekis, A., Mentzas, G. N., Apostolou, D., & Wellsandt, S. (2024) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-65894-5_16 · Cited by 1 · see citing works
The Groundwork for an Ethics of Artificial Intelligence in Defence
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.003.0001 · Cited by 1 · see citing works
Musasa, T. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-1414-3.ch013 · Cited by 1 · see citing works
Managing Ethical Risks of Artificial Intelligence in Business ApplicationsPreprint
McGrath, Q. P., Hevner, A. R., & de Vreede, G. (2024) · doi:10.36227/techrxiv.170905835.50964792/v1 · Cited by 1 · see citing works
Liu, B. (2023) · IEEE International Conference on Communication Systems and Network Technologies (CSNT) · doi:10.1109/csnt57126.2023.10134703
“This platform allows tourists to consume online within the specified time, so the data can be directly sent back to the background database [11-12].”
BackgroundBuilding Smart Systems to Satisfice User Intention in Situ: A Look Back to the Future*
Liu, L., Xie, H., Yang, J., & Li, Y. (2023) · IEEE International Conference on Software Services Engineering (SSE) · doi:10.1109/sse60056.2023.00042
Employee and Client Analytical Tool
Gupta, M., Rastogi, S., Sharma, P. K., & Arora, D. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-97-1724-8_3
The Future of Ethical AI in Large Language Models
Gupta, B. B., Gaurav, A., Chui, K. T., & Psannis, K. E. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-3860-5.ch013
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.002.0008
Taking a Moral Gambit: Accepting Moral Responsibility for the Actions of Autonomous Weapons Systems
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.003.0007
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.002.0007
Adversarial and Non-kinetic Uses of AI: Conceptual and Ethical Challenges
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.003.0004
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.002.0003
Adversarial and Kinetic Uses of AI: The Definition of Autonomous Weapon Systems
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.003.0006
Adversarial and Non-kinetic Uses: The Case of Artificial Intelligence for Cyber Deterrence
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.003.0005
Sustainment and Support Uses of AI in Defence: The Case of AI-Augmented Intelligence Analysis
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.003.0003
Ethical Principles for AI in Defence
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.003.0002
Taddeo, M. (2024) · Oxford University Press eBooks · doi:10.1093/oso/9780197745441.002.0005
Taddeo, M., Blanchard, A., & Thomas, C. (2025) · De Gruyter eBooks · doi:10.1515/9783111346632-024
Xiong, M., Wang, Y., & Olya, H. (2025) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-80262-963-720251009
Review of Policies for the Use of Generative Artificial Intelligence in Leading Foreign Universities
Gorlacheva, E. N., Леонидович, О. П., & Андреевна, П. Е. (2026) · University Management Practice and Analysis · doi:10.15826/umpa.2025.04.028
Ethical AI Integration in Digital Marketing for Sustainable Public Health Development in Africa
Takawira, B., Sibiya, A., Chadyiwa, M., & Pooe, D. R. I. (2026) · Springer eBooks · doi:10.1007/978-3-031-97088-7_3
Transparent and Trustworthy Data Practices for Talking Head Generation
Rakesh, V. K., Mazumdar, S., Samanta, T., Pal, S., & Das, A. K. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-1433-2.ch007
Constituting AI-Enabling Organizations: Legitimation Through AI Principles
Huhta, M., Sivunen, A. E., & van Zoonen, W. (2026) · International Journal of Business Communication · doi:10.1177/23294884261465791
What Do We Know about Implementing Ethical Principles in the Context of Artificial Intelligence
Rossi, J., Canedo, E. D., & Mendes, F. F. (2026) · ACM Computing Surveys · doi:10.1145/3860997
- Authors
- Georgieva, I., Lazo, C., Timan, T., & van Veenstra, A. F.
- Affiliations
- Netherlands Organisation for Applied Scientific Research (NL)
- Corresponding author
- Georgieva, Ilina
- Venue
- AI and Ethics
- Published
- 2022-01-12
- Volume
- 2
- Issue
- 4
- Pages
- 697-711
- ISSN
- 2730-5953 (ISSN-L)
- 2730-5961
- OpenAlex
- W4205433436
- Semantic Scholar
- 61b09551d1976151380e4df9a12103b513dd6a4e
- Cited by
- 89
- References
- 50
- Citations by year
- 2026: 7 · 2025: 26 · 2024: 40 · 2023: 13 · 2022: 3
- FWCI
- 23.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- AI and Ethics (publishedVersion)
- TNO Repository (submittedVersion)
- Funders
- TNO - Program 'Accelerating Trustworthy AI'
- Dutch AI Coalition
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Keywords
- AI ethics, ethical principles, data science practice, AI governance, AI lifecycle, ethical frameworks, digital services
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
