mlsanityData to 14 Oct 2026

Artificial Intelligence: the global landscape of ethics guidelines

arXiv 1906.11668 ↗First posted 24 Jun 2019cs.CY cs.AIcited by 107

Not on the map. Why?

Abstract (arXiv)

In the last five years, private companies, research institutions as well as public sector organisations have issued principles and guidelines for ethical AI, yet there is debate about both what constitutes "ethical AI" and which ethical requirements, technical standards and best practices are needed for its realization. To investigate whether a global agreement on these questions is emerging, we mapped and analyzed the current corpus of principles and guidelines on ethical AI. Our results reveal a global convergence emerging around five ethical principles (transparency, justice and fairness, non-maleficence, responsibility and privacy), with substantive divergence in relation to how these principles are interpreted; why they are deemed important; what issue, domain or actors they pertain to; and how they should be implemented. Our findings highlight the importance of integrating guideline-development efforts with substantive ethical analysis and adequate implementation strategies.

Key facts. Cited by 107 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Jun 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 19; 2022: 19; 2023: 31; 2024: 18; 2025: 12; 2026: 8.

107 papers.

Sort:

By area:

  1. 2021Trustworthy AI: From Principles to Practicescited by 207
  2. 2022The Fallacy of AI Functionalitycited by 88
  3. 2021Incorporating Domain Knowledge into Deep Neural Networkscited by 56
  4. 2023ChatGPT and a New Academic Reality: Artificial Intelligence-Written Research Papers and the Ethics of the Large Language Models in Scholarly Publishingcited by 52
  5. 2022How Different Groups Prioritize Ethical Values for Responsible AIcited by 49
  6. 2023GenAI Against Humanity: Nefarious Applications of Generative Artificial Intelligence and Large Language Modelscited by 42
  7. 2024Generative Artificial Intelligence: A Systematic Review and Applicationscited by 37
  8. 2023AI Alignment and Social Choice: Fundamental Limitations and Policy Implicationscited by 36
  9. 2024Trust in AI: Progress, Challenges, and Future Directionscited by 35
  10. 2023A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspectivecited by 33
  11. 2022On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbationscited by 32
  12. 2023Fairness and Bias in Algorithmic Hiring: a Multidisciplinary Surveycited by 30
38 more
  1. 2022Trust in AI and Its Role in the Acceptance of AI Technologiescited by 29
  2. 2022Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desideratacited by 28
  3. 2022Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governancecited by 28
  4. 2021Fairness Perceptions of Algorithmic Decision-Making: A Systematic Review of the Empirical Literaturecited by 27
  5. 2022From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible MLcited by 27
  6. 2021Automated scholarly paper review: Concepts, technologies, and challengescited by 21
  7. 2022Responsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and Engineeringcited by 20
  8. 2021Conformity Assessments and Post-market Monitoring: A Guide to the Role of Auditing in the Proposed European AI Regulationcited by 19
  9. 2024Mapping the Ethics of Generative AI: A Comprehensive Scoping Reviewcited by 19
  10. 2021Ethics of AI: A Systematic Literature Review of Principles and Challengescited by 18
  11. 2021Meaningful human control: actionable properties for AI system developmentcited by 18
  12. 2023Improving Recommendation Fairness via Data Augmentationcited by 18
  13. 2023`It is currently hodgepodge'': Examining AI/ML Practitioners' Challenges during Co-production of Responsible AI Valuescited by 18
  14. 2021Architectural Patterns for the Design of Federated Learning Systemscited by 17
  15. 2023Out of Context: Investigating the Bias and Fairness Concerns of "Artificial Intelligence as a Service"cited by 15
  16. 2023Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practicecited by 15
  17. 2021Filling gaps in trustworthy development of AIcited by 14
  18. 2022The Conflict Between Explainable and Accountable Decision-Making Algorithmscited by 13
  19. 2023Designing Interpretable ML System to Enhance Trust in Healthcare: A Systematic Review to Proposed Responsible Clinician-AI-Collaboration Frameworkcited by 11
  20. 2024Towards More Trustworthy and Interpretable LLMs for Code through Syntax-Grounded Explanationscited by 11
  21. 2024Generative AI for Requirements Engineering: A Systematic Literature Reviewcited by 11
  22. 2023fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Taskscited by 10
  23. 2024Auditing of AI: Legal, Ethical and Technical Approachescited by 10
  24. 2021FLRA: A Reference Architecture for Federated Learning Systemscited by 9
  25. 2021Software Engineering for Responsible AI: An Empirical Study and Operationalised Patternscited by 9
  26. 2022Algorithmic audits of algorithms, and the lawcited by 9
  27. 2022Towards a Roadmap on Software Engineering for Responsible AIcited by 9
  28. 2023Human-Centred Learning Analytics and AI in Education: a Systematic Literature Reviewcited by 9
  29. 2024FAIR Enough: How Can We Develop and Assess a FAIR-Compliant Dataset for Large Language Models' Training?cited by 9
  30. 2023Human-Centered Responsible Artificial Intelligence: Current & Future Trendscited by 8
  31. 2022Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliancecited by 7
  32. 2024Beyond principlism: Practical strategies for ethical AI use in research practicescited by 7
  33. 2024The Ethics of AI in Educationcited by 7
  34. 2022Moral Dilemmas for Moral Machinescited by 6
  35. 2022A Principles-based Ethics Assurance Argument Pattern for AI and Autonomous Systemscited by 6
  36. 2022Responsible Artificial Intelligence -- from Principles to Practicecited by 6
  37. 2022Persona-Based Conversational AI: State of the Art and Challengescited by 6
  38. 2023Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspectscited by 6

50 most cited of 107 All 107 (JSON)