Advances in AI Transparency and Governance

The field of artificial intelligence is moving towards increased transparency and accountability, with a focus on developing trustworthy and ethically aligned systems. Recent research has highlighted the importance of transparency in AI decision-making processes, and the need for standardized metrics and explainable AI techniques to facilitate accountability. The development of frameworks and guidelines for AI governance is also a key area of focus, with a emphasis on ensuring that AI systems are designed and deployed in a responsible and ethical manner. Noteworthy papers in this area include 'Towards Transparent Ethical AI: A Roadmap for Trustworthy Robotic Systems', which proposes a framework for implementing transparency in AI systems, and 'A Moral Agency Framework for Legitimate Integration of AI in Bureaucracies', which presents a three-point framework for ensuring that AI systems are used in a way that is consistent with human values and principles. Additionally, 'Never Compromise to Vulnerabilities: A Comprehensive Survey on AI Governance' provides a comprehensive framework for AI governance, integrating technical and societal dimensions to promote transparency, accountability, and trust in AI systems.

Sources

Towards Transparent Ethical AI: A Roadmap for Trustworthy Robotic Systems

Generative AI and the Future of the Digital Commons: Five Open Questions and Knowledge Gaps

Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks

A Moral Agency Framework for Legitimate Integration of AI in Bureaucracies

EU Digital Regulation and Guatemala: AI, 5G, and Cybersecurity

Do AI Companies Make Good on Voluntary Commitments to the White House?

AI Agents and the Law

AI Security Map: Holistic Organization of AI Security Technologies and Impacts on Stakeholders

Dead Zone of Accountability: Why Social Claims in Machine Learning Research Should Be Articulated and Defended

Never Compromise to Vulnerabilities: A Comprehensive Survey on AI Governance

TechOps: Technical Documentation Templates for the AI Act

Can We Trust AI to Govern AI? Benchmarking LLM Performance on Privacy and AI Governance Exams

STREAM (ChemBio): A Standard for Transparently Reporting Evaluations in AI Model Reports

Legal Zero-Days: A Novel Risk Vector for Advanced AI Systems

Amazon Nova AI Challenge -- Trusted AI: Advancing secure, AI-assisted software development

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