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.
Occasional Paper
In a new working paper, Crocodile Tears: Can the Ethical-Moral Intelligence of AI Models Be Trusted?, Allen Lab authors Sarah Hubbard, David Kidd, and Andrei Stupu introduce an ethical-moral intelligence framework for evaluating AI models across dimensions of moral expertise, sensitivity, coherence, and transparency.
Additional Resource
Creating a healthy digital civic infrastructure ecosystem means not just deploying technology for the sake of efficiency, but thoughtfully designing tools built to enhance democratic engagement from connection to action.
Commentary
Last week’s leak of the U.S. Department of Education’s proposed “Compact for Academic Excellence in Higher Education” drew intense reactions across academia. Critics call it government overreach threatening free expression, while supporters see a chance for reform and renewed trust between universities and policymakers. Danielle Allen, James Bryant Conant University Professor at Harvard University, director of the Democratic Knowledge Project and the Allen Lab for Democracy Renovation, weighs in.
Occasional Paper
In a new working paper, Crocodile Tears: Can the Ethical-Moral Intelligence of AI Models Be Trusted?, Allen Lab authors Sarah Hubbard, David Kidd, and Andrei Stupu introduce an ethical-moral intelligence framework for evaluating AI models across dimensions of moral expertise, sensitivity, coherence, and transparency.
Additional Resource
Creating a healthy digital civic infrastructure ecosystem means not just deploying technology for the sake of efficiency, but thoughtfully designing tools built to enhance democratic engagement from connection to action.
Feature
Public engagement has long been too time-consuming and costly for governments to sustain, but AI offers tools to make participation more systematic and impactful. Our new Reboot Democracy Workshop Series replaces lectures with hands-on sessions that teach the practical “how-to’s” of AI-enhanced engagement. Together with leading practitioners and partners at InnovateUS and the Allen Lab at Harvard, we’ll explore how AI can help institutions tap the collective intelligence of our communities more efficiently and effectively.