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Discerning Between the “Easy” and “Hard” Problems of AI Governance
16 references·0 citing·47 second hop
Discerning Between the “Easy” and “Hard” Problems of AI Governance (2023)Discerning Between the “Easy” and “Hard” …The Ethics of AI Ethics: An Evaluation of Guidelines (2020)The Ethics of AI Ethics: An E…Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities (2020)Paradoxes of artificial intel…Designing conceptual articles: four approaches (2020)Designing conceptual articles…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…The Emergence of Deepfake Technology: A Review (2019)The Emergence of Deepfake Tec…AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)AI Fairness 360: An extensibl…Ethical Implications and Accountability of Algorithms (2018)Ethical Implications and Acco…AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations (2018)AI4People—An Ethical Framewor…What is data justice? The case for connecting digital rights and freedoms globally (2017)What is data justice? The cas…A Layered Model for AI Governance (2017)A Layered Model for AI Govern…A Vision of Responsible Research and Innovation (2013)A Vision of Responsible Resea…Understanding privacy (2008)Understanding privacyFacing Up to the Problem of Consciousness (1996)Facing Up to the Problem of C…Explaining Development and Change in Organizations (1995)Explaining Development and Ch…Organizations: A Dialectical View (1977)Organizations: A Dialectical …Midstream Modulation of Technology: Governance From Within (2006)Public Value Mapping and Science Policy Evaluation (2011)Where are the politics in responsible innovation? European governance, technology assessments, and beyond (2014)The Emerging Concept of Responsible Innovation. Three Reasons Why It Is Questionable and Calls for a Radical Transformation of the Concept of Innovation (2015)Collingridge and the dilemma of control: Towards responsible and accountable innovation (2017)A Framework for the Comparative Analysis of Organizations (1967)The Social Construction of Reality (1967)Organizational dissidence: The case of whistle-blowing (1985)Complex Organizations: A Critical Essay (1990)Multiparadigm Perspectives on Theory Building (1990)Instabilities of Strategic Alliances: An Internal Tensions Perspective (2000)The Social Psychology of Organizations. (1979)Capitalism, Socialism and Democracy (1997)ORGANIZATIONAL CHANGE AND DEVELOPMENT (1999)Strategies for Theorizing from Process Data (1999)A Multi‐Dimensional Framework of Organizational Innovation: A Systematic Review of the Literature (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)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. (2009)Principles alone cannot guarantee ethical AI (2019)Ethics of AI in Education: Towards a Community-Wide Framework (2021)Certifying and Removing Disparate Impact (2015)Equality of Opportunity in Supervised Learning (2016)Mitigating Unwanted Biases with Adversarial Learning (2018)Addressing bias in big data and AI for health care: A call for open science (2021)Trustworthy Artificial Intelligence: A Review (2022)Artificial Intelligence, Deepfakes and a Future of Ectypes (2018)Infodemics and health misinformation: a systematic review of reviews (2022)Is digital transformation threatened? A systematic literature review of the factors influencing firms’ digital transformation and internationalization (2022)Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions (2023)Experimental evidence of massive-scale emotional contagion through social networks (2014)Emerging challenges in AI and the need for AI ethics education (2020)Ethical principles for artificial intelligence in education (2022)International Journal of Physical Distribution and Logistics Management (1990)Evolving to a New Dominant Logic for Marketing (2003)The Uses of Argument (2003)Understanding Customer Experience Throughout the Customer Journey (2016)Conceptualising overtourism: A sustainability approach (2020)Guidelines for advancing theory and practice through bibliometric research (2022)A cognitive theory of consciousness (1988)Consciousness Explained. (1993)On a confusion about a function of consciousness (1995)Consciousness and its Place in Nature (2003)Towards a true neural stance on consciousness (2006)A materialist theory of the mind (2017)On the Opportunities and Risks of Foundation Models (2021)Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy (2023)
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References

  • 2019The global landscape of AI ethics guidelines6,172 cited
  • 2018AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations4,732 cited
  • 1995Explaining Development and Change in Organizations3,759 cited
  • 2020Designing conceptual articles: four approaches2,209 cited
  • 1996Facing Up to the Problem of Consciousness1,966 cited
  • 2020The Ethics of AI Ethics: An Evaluation of Guidelines1,900 cited
  • 2013A Vision of Responsible Research and Innovation1,302 cited
  • 2019The Emergence of Deepfake Technology: A Review1,135 cited
  • 1977Organizations: A Dialectical View914 cited
  • 2019AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias884 cited
  • 2008Understanding privacy820 cited
  • 2017What is data justice? The case for connecting digital rights and freedoms globally798 cited
  • 2018Ethical Implications and Accountability of Algorithms754 cited
  • 2020Bridging the Gap Between Ethics and Practice747 cited
  • 2020Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities559 cited

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A Layered Model for AI Governance
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