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.
Policy Brief
How AI Fails Us
Researchers and funders should redirect focus from centralized autonomous general intelligence to a plurality of established and emerging approaches that extend cooperative and augmentative traditions as seen in successes such as Taiwan’s digital democracy project to collective intelligence platforms like Wikipedia.
Issues
The dominant vision of artificial intelligence imagines a future of large-scale autonomous systems outperforming humans in an increasing range of fields. This “actually existing AI” vision misconstrues intelligence as autonomous rather than social and relational. It is both unproductive and dangerous, optimizing for artificial metrics of human replication rather than for systemic augmentation, and tending to concentrate power, resources, and decision-making in an engineering elite. Alternative visions based on participating in and augmenting human creativity and cooperation have a long history and underlie many celebrated digital technologies such as personal computers and the internet. Researchers and funders should redirect focus from centralized autonomous general intelligence to a plurality of established and emerging approaches that extend cooperative and augmentative traditions as seen in successes such as Taiwan’s digital democracy project to collective intelligence platforms like Wikipedia. We conclude with a concrete set of recommendations and a survey of alternative traditions.
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.
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.
Article
Artificial Intelligence and Democracy: Campaigns, Elections, Movements, and Deliberation
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
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.