Media Release
Danielle Allen’s Radical Duke Recasts the Origins of the Age of Revolution
A new book from Harvard scholar Danielle Allen revisits the forgotten British radical movement that helped shape modern democracy.
Democracy’s Tripwire: Global Corruption and Whistleblowing in Europe and the U.S.
This paper compares whistleblower protection politics in Europe and the United States to bring into fuller relief the vital role insider truth-telling plays in combatting global corruption, keeping elites honest, and sustaining liberal democracy.
Misconduct by those in high places is dangerous to reveal, even in political regimes that protect freedom of expression. Whistleblowers in democracies thus face a paradox: by challenging and exposing transgressions by the powerful, they perform a vital public service; yet without the sustained support of the voting public, they always suffer for it. This paper compares whistleblower protection politics in Europe and the United States to bring into fuller relief the vital role insider truth-telling plays in combatting global corruption, keeping elites honest, and sustaining liberal democracy.
Related Resources
Media Release
AI models appear to recognize moral complexity — then ignore it, new study by researchers affiliated with Harvard Kennedy School’s Allen Lab finds
New study published in AI and Ethics introduces a new ethical-moral intelligence framework for AI and finds that leading AI models mimic human moral concern while making decisions that reveal a hidden value hierarchy.
Q+A
Q & A: Crocodile tears, Can the ethical-moral intelligence of AI models be trusted?
As artificial intelligence becomes more embedded in everyday decision-making, its role in shaping how people think about ethics and morality is drawing increasing scrutiny. In this conversation with researcher Sarah Hubbard, we discuss insights from her co-authored paper, “Crocodile Tears: Can the Ethical-Moral Intelligence of AI Models Be Trusted?”—examining how AI systems respond to moral dilemmas, and what this reveals about the risks, limitations, and need for greater transparency and human oversight in AI-driven ethical guidance.