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.
When AI is seen as a source of truth and scientific knowledge, it may lend public legitimacy to harmful ideas about identity.
Critics now articulate their worries about the technologies, social practices and mythologies that comprise Artificial Intelligence (AI) in many domains. In this paper, we investigate the intersection of two domains of criticism: identity and scientific knowledge. On one hand, critics of AI in public policy emphasise its potential to discriminate on the basis of identity. On the other hand, critics of AI in scientific realms worry about how it may reorient or disorient research practices and the progression of scientific inquiry. We link the two sets of concerns—around identity and around knowledge—through a series of case studies. In our case studies, about autism and homosexuality, AI figures as part of scientific attempts to find, and fix, forms of identity. Our case studies are instructive: they show that when AI is deployed in scientific research about identity and personality, it can naturalise and reinforce biases. The identity-based and epistemic concerns about AI are not distinct. When AI is seen as a source of truth and scientific knowledge, it may lend public legitimacy to harmful ideas about identity.
Media Release
A new book from Harvard scholar Danielle Allen revisits the forgotten British radical movement that helped shape modern democracy.
Media Release
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
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.
Media Release
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.
Article
A new chapter in APSA Preprints by Archon Fung, Winthrop Laflin McCormack Professor of Citizenship and Self-Government and Director of the Ash Center, Bailey Flanigan, former postdoctoral fellow at the Ash Center and co-authors explores how generative AI is reshaping four dimensions of democratic practice—political campaigns, election administration, social movements, and citizen deliberation. The authors argue that AI’s ultimate democratic impact will depend less on the technology itself, and more on how institutions and leaders implement and regulate it.
Q+A
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.