Responsible AI Governance: A Response to UN Interim Report on Governing AI for Humanity
- URL: http://arxiv.org/abs/2412.12108v3
- Date: Tue, 31 Dec 2024 18:52:58 GMT
- Title: Responsible AI Governance: A Response to UN Interim Report on Governing AI for Humanity
- Authors: Sarah Kiden, Bernd Stahl, Beverley Townsend, Carsten Maple, Charles Vincent, Fraser Sampson, Geoff Gilbert, Helen Smith, Jayati Deshmukh, Jen Ross, Jennifer Williams, Jesus Martinez del Rincon, Justyna Lisinska, Karen O'Shea, Márjory Da Costa Abreu, Nelly Bencomo, Oishi Deb, Peter Winter, Phoebe Li, Philip Torr, Pin Lean Lau, Raquel Iniesta, Gopal Ramchurn, Sebastian Stein, Vahid Yazdanpanah,
- Abstract summary: The report emphasizes the transformative potential of AI in achieving the Sustainable Development Goals.<n>It acknowledges the need for robust governance to mitigate associated risks.<n>The report concludes with actionable principles for fostering responsible AI governance.
- Score: 15.434533537570614
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This report presents a comprehensive response to the United Nation's Interim Report on Governing Artificial Intelligence (AI) for Humanity. It emphasizes the transformative potential of AI in achieving the Sustainable Development Goals (SDGs) while acknowledging the need for robust governance to mitigate associated risks. The response highlights opportunities for promoting equitable, secure, and inclusive AI ecosystems, which should be supported by investments in infrastructure and multi-stakeholder collaborations across jurisdictions. It also underscores challenges, including societal inequalities exacerbated by AI, ethical concerns, and environmental impacts. Recommendations advocate for legally binding norms, transparency, and multi-layered data governance models, alongside fostering AI literacy and capacity-building initiatives. Internationally, the report calls for harmonising AI governance frameworks with established laws, human rights standards, and regulatory approaches. The report concludes with actionable principles for fostering responsible AI governance through collaboration among governments, industry, academia, and civil society, ensuring the development of AI aligns with universal human values and the public good.
Related papers
- Bridging the Gap: Integrating Ethics and Environmental Sustainability in AI Research and Practice [57.94036023167952]
We argue that the efforts aiming to study AI's ethical ramifications should be made in tandem with those evaluating its impacts on the environment.
We propose best practices to better integrate AI ethics and sustainability in AI research and practice.
arXiv Detail & Related papers (2025-04-01T13:53:11Z) - Media and responsible AI governance: a game-theoretic and LLM analysis [61.132523071109354]
This paper investigates the interplay between AI developers, regulators, users, and the media in fostering trustworthy AI systems.
Using evolutionary game theory and large language models (LLMs), we model the strategic interactions among these actors under different regulatory regimes.
arXiv Detail & Related papers (2025-03-12T21:39:38Z) - What is Ethical: AIHED Driving Humans or Human-Driven AIHED? A Conceptual Framework enabling the Ethos of AI-driven Higher education [0.6216023343793144]
This study introduces the Human-Driven AI in Higher Education (HD-AIHED) Framework to ensure compliance with UNESCO and OECD ethical standards.
The study applies a participatory co-system, Phased Human Intelligence, SWOC analysis, and AI ethical review boards to assess AI readiness and governance strategies for universities and HE institutions.
arXiv Detail & Related papers (2025-02-07T11:13:31Z) - Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground [55.2480439325792]
I argue that efforts to promote responsible and ethical AI can inadvertently contribute to and seemingly legitimize this disregard for established contextual norms.
I question the current narrow prioritization in AI ethics of moral innovation over moral preservation.
arXiv Detail & Related papers (2024-12-06T15:36:13Z) - From Principles to Practice: A Deep Dive into AI Ethics and Regulations [13.753819576072127]
The article thoroughly analyzes the ground-breaking AI regulatory framework proposed by the European Union.<n>Considering the technical efforts and strategies undertaken by academics and industry to uphold these principles, we explore the synergies and conflicts among the five ethical principles.
arXiv Detail & Related papers (2024-12-06T00:46:20Z) - Strategic AI Governance: Insights from Leading Nations [0.0]
Artificial Intelligence (AI) has the potential to revolutionize various sectors, yet its adoption is often hindered by concerns about data privacy, security, and the understanding of AI capabilities.
This paper synthesizes AI governance approaches, strategic themes, and enablers and challenges for AI adoption by reviewing national AI strategies from leading nations.
arXiv Detail & Related papers (2024-09-16T06:00:42Z) - Particip-AI: A Democratic Surveying Framework for Anticipating Future AI Use Cases, Harms and Benefits [54.648819983899614]
General purpose AI seems to have lowered the barriers for the public to use AI and harness its power.
We introduce PARTICIP-AI, a framework for laypeople to speculate and assess AI use cases and their impacts.
arXiv Detail & Related papers (2024-03-21T19:12:37Z) - Towards Responsible AI in Banking: Addressing Bias for Fair
Decision-Making [69.44075077934914]
"Responsible AI" emphasizes the critical nature of addressing biases within the development of a corporate culture.
This thesis is structured around three fundamental pillars: understanding bias, mitigating bias, and accounting for bias.
In line with open-source principles, we have released Bias On Demand and FairView as accessible Python packages.
arXiv Detail & Related papers (2024-01-13T14:07:09Z) - A Review of the Ethics of Artificial Intelligence and its Applications
in the United States [0.0]
The paper highlights the impact AI has in every sector of the US economy and the resultant effect on entities spanning businesses, government, academia, and civil society.
Our discussion explores eleven fundamental 'ethical principles' structured as overarching themes.
These encompass Transparency, Justice, Fairness, Equity, Non- Maleficence, Responsibility, Accountability, Privacy, Beneficence, Freedom, Autonomy, Trust, Dignity, Sustainability, and Solidarity.
arXiv Detail & Related papers (2023-10-09T14:29:00Z) - A multilevel framework for AI governance [6.230751621285321]
We propose a multilevel governance approach that involves governments, corporations, and citizens.
The levels of governance combined with the dimensions of trust in AI provide practical insights that can be used to further enhance user experiences and inform public policy related to AI.
arXiv Detail & Related papers (2023-07-04T03:59:16Z) - Putting AI Ethics into Practice: The Hourglass Model of Organizational
AI Governance [0.0]
We present an AI governance framework, which targets organizations that develop and use AI systems.
The framework is designed to help organizations deploying AI systems translate ethical AI principles into practice.
arXiv Detail & Related papers (2022-06-01T08:55:27Z) - Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable
Claims [59.64274607533249]
AI developers need to make verifiable claims to which they can be held accountable.
This report suggests various steps that different stakeholders can take to improve the verifiability of claims made about AI systems.
We analyze ten mechanisms for this purpose--spanning institutions, software, and hardware--and make recommendations aimed at implementing, exploring, or improving those mechanisms.
arXiv Detail & Related papers (2020-04-15T17:15:35Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.