Articles
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How Organizations Move from Competing Stakeholder Perspectives to Evidence-Based AI Deployment Decisions
When governance begins with structured risk assessment rather than assumptions, organizations are able to translate stakeholder perspectives into measurable risks, document them in a…
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Disclosure Is Not Accountability: New York’s AI Court Rule and the Future of Legal Responsibility
Can simply disclosing AI use satisfy legal responsibility? As courts embrace artificial intelligence, the real challenge is no longer transparency, but ensuring meaningful accountability…
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AI Agents and the Rule of Law: Can Existing Safeguards Govern Machine Agency?
AI agents are no longer just assisting lawyers. They are making decisions. Can existing legal safeguards govern machines acting with increasing autonomy before accountability…
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Getting Ahead of AI Copyright: A Governance Roadmap for Organizations
The greatest AI copyright risk is not tomorrow’s lawsuit but today’s governance gap. Is your organisation prepared before legal uncertainty becomes institutional liability?
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How Do We Know if an AI System Is Safe, Fair, Reliable, and Trustworthy?
One of the most consequential questions in technology governance today is also one of the most underexamined: how do we establish, and sustain, meaningful…
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Why High-Risk AI in Employment Demands More Than Ethics Statements
Artificial intelligence is no longer sitting at the edges of human resources as an experimental productivity tool. It is increasingly being used to influence…

THOUGHTS THAT INSPIRE
Governments can make a greater effort to encourage computer science education, especially among young girls, racial minorities, and other groups whose perspectives have been underrepresented in AI.

Dr. Fei‑Fei Li
Co-Director, Stanford’s Human-Centered AI Institute
