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.
Video
Optimizing for What? Algorithmic Amplification and Society
GETTING-Plurality Workstream Lead Aviv Ovadya recently discussed his work on bridging systems as part of “Optimizing for What? Algorithmic Amplification and Society.” This two-day symposium at Columbia University’s Knight First Amendment Institute explored algorithmic amplification and distortion as well as potential interventions.
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.