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AI and Ethics—Operationalizing Responsible AI
8 references·4 citing·37 second hop
AI and Ethics—Operationalizing Responsible AI (2021)AI and Ethics—Operationalizing Responsibl…Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure (2021)Towards Accountability for Ma…How Humans Judge Machines (2021)How Humans Judge MachinesPrincipled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI (2020)Principled Artificial Intelli…Bridging the Gap Between Ethics and Practice (2020)Bridging the Gap Between Ethi…The global landscape of AI ethics guidelines (2019)The global landscape of AI et…Responsible Artificial Intelligence (2019)Responsible Artificial Intell…Principles alone cannot guarantee ethical AI (2019)Principles alone cannot guara…International Organization for Standardization (2011)International Organization fo…Integrating ESG and AI: a comprehensive responsible AI assessment framework (2025)Integrating ESG and AI: a com…The Convergence of Artificial Intelligence and Privacy: Navigating Innovation with Ethical Considerations (2024)The Convergence of Artificial…Developing Responsible Chatbots for Financial Services: A Pattern-Oriented Responsible Artificial Intelligence Engineering Approach (2023)Developing Responsible Chatbo…On the violation of honesty in mobile apps (2022)On the violation of honesty i…Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (2009)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. (2009)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)Ethics of AI in Education: Towards a Community-Wide Framework (2021)Ethical Decision Making by Individuals in Organizations: An Issue-Contingent Model (1991)AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations (2018)Artificial Intelligence, Values, and Alignment (2020)Ethics of AI-Enabled Recruiting and Selection: A Review and Research Agenda (2022)Research in Organizational Behavior. (1986)European Union Regulations on Algorithmic Decision Making and a “Right to Explanation” (2017)Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy (2020)Trustworthy AI: From Principles to Practices (2022)Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges (2023)Dilemmas in a general theory of planning (1973)Science in action : how to follow scientists and engineers through society (1987)Science in Action: How to Follow Scientists and Engineers through Society (1988)Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development (2021)On the genealogy of machine learning datasets: A critical history of ImageNet (2021)Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI (2022)The ethics of algorithms: Mapping the debate (2016)Navigating the Dual Nature of Deepfakes: Ethical, Legal, and Technological Perspectives on Generative Artificial Intelligence AI) Technology (2024)Likert Scale: Explored and Explained (2015)Purposive sampling: complex or simple? Research case examples (2020)The role of artificial intelligence in achieving the Sustainable Development Goals (2020)Algorithmic HRM as a regime of control: surveillance, legitimacy and worker resistance (2026)An examination of corporate reporting, environmental management practices and firm performance (2006)How Do Employees Perceive Corporate Responsibility? Development and Validation of a Multidimensional Corporate Stakeholder Responsibility Scale (2015)Green human resource management research in emergence: A review and future directions (2017)Artificial intelligence, systemic risks, and sustainability (2021)Responsible artificial intelligence governance: A review and research framework (2025)Trust repair in human-agent teams: the effectiveness of explanations and expressing regret (2021)Prompting meaning: a hermeneutic approach to optimising prompt engineering with ChatGPT (2023)Quantifying the use and potential benefits of artificial intelligence in scientific research (2024)An Overview of Artificial Intelligence Ethics (2022)Thinking responsibly about responsible AI and ‘the dark side’ of AI (2022)Transparency and accountability in AI systems: safeguarding wellbeing in the age of algorithmic decision-making (2024)
this work references cited by second hop

References

  • 2011International Organization for Standardization12,534 cited
  • 2019The global landscape of AI ethics guidelines6,172 cited
  • 2019Principles alone cannot guarantee ethical AI1,869 cited
  • 2019Responsible Artificial Intelligence1,064 cited
  • 2020Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI998 cited
  • 2020Bridging the Gap Between Ethics and Practice747 cited
  • 2021Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure279 cited
  • 2021How Humans Judge Machines113 cited

Cited by

  • 2025Integrating ESG and AI: a comprehensive responsible AI assessment framework42 cited
  • 2024The Convergence of Artificial Intelligence and Privacy: Navigating Innovation with Ethical Considerations27 cited
  • 2023Developing Responsible Chatbots for Financial Services: A Pattern-Oriented Responsible Artificial Intelligence Engineering Approach19 cited
  • 2022On the violation of honesty in mobile apps18 cited

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