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An evidence-based methodology for human rights impact assessment (HRIA) in the development of AI data-intensive systems
2 references·10 citing·43 second hop
An evidence-based methodology for human rights impact assessment (HRIA) in the development of AI data-intensive systems (2021)An evidence-based methodology for human r…The regulation of civilian drones' impacts on behavioural privacy (2014)The regulation of civilian dr…The Filter Bubble: What the Internet Is Hiding from You (2011)The Filter Bubble: What the I…Ethical theories, governance models, and strategic frameworks for responsible AI adoption and organizational success (2025)Ethical theories, governance …What ethics can say on artificial intelligence: Insights from a systematic literature review (2024)What ethics can say on artifi…Normative Challenges of Risk Regulation of Artificial Intelligence (2024)Normative Challenges of Risk …My Future with My Chatbot: A Scenario-Driven, User-Centric Approach to Anticipating AI Impacts (2024)My Future with My Chatbot: A …Developing an Ethical Regulatory Framework for Artificial Intelligence: Integrating Systematic Review, Thematic Analysis, and Multidisciplinary Theories (2024)Developing an Ethical Regulat…Legal Aspects of the Use Artificial Intelligence in Telemedicine (2023)Legal Aspects of the Use Arti…Exploring ethics and human rights in artificial intelligence – A Delphi study (2023)Exploring ethics and human ri…Questioning the EU proposal for an Artificial Intelligence Act: The need for prohibitions and a stricter approach to biometric surveillance1 (2022)Questioning the EU proposal f…FMEA-AI: AI fairness impact assessment using failure mode and effects analysis (2022)FMEA-AI: AI fairness impact a…Beyond Data (2022)Beyond Data11. The Right to Privacy (1890)Discipline and Punish: The Birth of the Prison. (1978)Privacy, data protection and ethics for civil drone practice: A survey of industry, regulators and civil society organisations (2016)A Survey of Behavioral Models for Social Robots (2019)Regulatory alternatives for AI (2019)Discipline and Punish: The Birth of the Prison (2020)Certifying and Removing Disparate Impact (2015)The social dilemma of autonomous vehicles (2016)Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2017)A step toward building a unified framework for managing AI bias (2023)Towards Concrete and Connected AI Risk Assessment (C2AIRA): A Systematic Mapping Study (2023)A literature review of risk assessment approaches in failure mode and effects analysis (2025)Group Privacy (2016)Emotional AI, soft biometrics and the surveillance of emotional life: An unusual consensus on privacy (2020)Demystifying the Draft EU Artificial Intelligence Act — Analysing the good, the bad, and the unclear elements of the proposed approach (2021)Analyzing AI regulation through literature and current trends (2025)Computer-vision research powers surveillance technology (2025)Public Opinion and the Rise of Digital Minds: Perceived Risk, Trust, and Regulation Support (2025)Risk Society: Towards a New Modernity (1993)Pandora's Hope: Essays on the Reality of Science Studies (2000)The global landscape of AI ethics guidelines (2019)Enhancing AI fairness through impact assessment in the European Union: a legal and computer science perspective (2023)On the Development of AI Governance Frameworks (2023)The promises and challenges of addressing artificial intelligence with human rights (2023)Stanford Encyclopedia of Philosophy (2015)An Introduction to the Principles of Morals and Legislation (2017)Impact of AI-focussed technologies on social and technical competencies for HR managers – A systematic review and research agenda (2024)Integrating artificial intelligence and human resource management: a review and future research agenda (2024)The relationship between digital technologies and innovation: A review, critique, and research agenda (2024)The responsibility gap: Ascribing responsibility for the actions of learning automata (2004)Legal and human rights issues of AI: Gaps, challenges and vulnerabilities (2020)There Is No Techno-Responsibility Gap (2020)Technology Parks in High Tech Sphere: New Legislation Analysis (2023)Digital Twins in Healthcare System: Communication between Society and Law (2024)Implications of Artificial Intelligence for the Labour Market (2026)The Fourth Industrial Revolution (2017)Content Analysis: An Introduction to Its Methodology (2019)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)A Survey on Bias and Fairness in Machine Learning (2021)Ethical Decision Making by Individuals in Organizations: An Issue-Contingent Model (1991)Exposure to ideologically diverse news and opinion on Facebook (2015)Filter Bubbles, Echo Chambers, and Online News Consumption (2016)Beyond misinformation: Understanding and coping with the “post-truth” era. (2017)
this work references cited by second hop

References

  • 2011The Filter Bubble: What the Internet Is Hiding from You4,429 cited
  • 2014The regulation of civilian drones' impacts on behavioural privacy112 cited

Cited by

  • 2023Exploring ethics and human rights in artificial intelligence – A Delphi study94 cited
  • 2022Beyond Data66 cited
  • 2025Ethical theories, governance models, and strategic frameworks for responsible AI adoption and organizational success64 cited
  • 2024What ethics can say on artificial intelligence: Insights from a systematic literature review40 cited
  • 2023Legal Aspects of the Use Artificial Intelligence in Telemedicine38 cited
  • 2024Normative Challenges of Risk Regulation of Artificial Intelligence36 cited
  • 2022Questioning the EU proposal for an Artificial Intelligence Act: The need for prohibitions and a stricter approach to biometric surveillance127 cited
  • 2022FMEA-AI: AI fairness impact assessment using failure mode and effects analysis26 cited
  • 2024Developing an Ethical Regulatory Framework for Artificial Intelligence: Integrating Systematic Review, Thematic Analysis, and Multidisciplinary Theories19 cited
  • 2024My Future with My Chatbot: A Scenario-Driven, User-Centric Approach to Anticipating AI Impacts18 cited

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