Accountability and Responsibility
in AI Governance
Examines who bears responsibility for AI systems’ decisions and actions, covering mechanisms for oversight, auditing, and recourse. Discusses frameworks for establishing clear chains of responsibility, liability issues, and best practices for responsible AI development.
Stay updated with insights on the evolving landscape of Accountability and Responsibility.
UN Maintenance of international peace and security Meeting
World reknown Fei-Fei Li and Yann LeCun opinions at UN «Maintenance of international peace and security» meeting.
AI GRC Explained
Discover how AI GRC help on governance, risk, and compliance with innovative, efficient solutions.
Implementing third-party AI tools
Discover essential strategies for implementing third-party AI tools safely and effectively. Learn best practices for vendor assessment, risk management and governance from industry experts. A comprehensive guide for privacy and AI governance professionals.
What are your ideas for shaping AI to serve the public good?
The findings from a extensive global consultation of citizens and experts on shaping AI to serve the public good, with dual validation from citizens and experts across five continents.
Third-Party AI Assurance: Building Trust in the Age of Artificial Intelligence
Explore how third-party AI assurance methods help organizations validate AI systems, manage risks and build stakeholder trust in AI implementations.
The AI Black Box: Approaches to Transparency and Accountability
Global approaches to AI transparency: regulations, tools, and industry practices in modern governance including model cards, system cards, and watermarking.
AI Governance in the Age of Autonomous Agents: A Critical Look at the Evolution from LLMs to AI Agents
Explore autonomous AI agents and understand its governance challenges. Learn about the benefits, risks, and essential framework for responsible AI agent development and deployment.
The Data Challenge
Discover how organizations can master AI training data management: from data types, quality considerations, and practical strategies for building robust data governance frameworks.
The Critical Imperative of AI Governance: Why Your Organization Can’t Wait Any Longer
Discover why AI governance is crucial for modern organizations and learn how to implement effective frameworks to manage AI risks while maximizing benefits.
What Should Be Internationalized in AI Governance ?
Explore the framework from Oxford Marting AI Governance Initiative for prioritizing AI governance issues for international cooperation. Discover key areas like compute oversight, content provenance, and model evaluations, where global standards are critical for a trustworthy AI future.
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