10 citations · 13 across the 9 of their papers we have counts for
9 papers
AI and Collective Decisions: Strengthening Legitimacy and Losers' Consent
Suyash Fulay, Prerna Ravi, Emily Kubin +3
AI is increasingly used to scale collective decision-making, but far less attention has been paid to how such systems can support procedural legitimacy, particularly the conditions…
Agora: Teaching the Skill of Consensus-Finding with AI Personas Grounded in Human Voice
Prerna Ravi, Om Gokhale, Suyash Fulay +3
Deliberative democratic theory suggests that civic competence: the capacity to navigate disagreement, weigh competing values, and arrive at collective decisions is not innate but d…
From Delegates to Trustees: How Optimizing for Long-Term Interests Shapes Bias and Alignment in LLM
Suyash Fulay, Jocelyn Zhu, Michiel Bakker
Large language models (LLMs) have shown promising accuracy in predicting survey responses and policy preferences, which has increased interest in their potential to represent human…
Shareholder Democracy with AI Representatives
Suyash Fulay, Sercan Demir, Galen Hines-Pierce +2
A large share of retail investors hold public equities through mutual funds, yet lack adequate control over these investments. Indeed, mutual funds concentrate voting power in the…
The Empty Chair: Using LLMs to Raise Missing Perspectives in Policy Deliberations
Suyash Fulay, Dimitra Dimitrakopoulou, Deb Roy
Deliberation is essential to well-functioning democracies, yet physical, economic, and social barriers often exclude certain groups, reducing representativeness and contributing to…
On the Relationship between Truth and Political Bias in Language Models
Suyash Fulay, William Brannon, Shrestha Mohanty +4
Language model alignment research often attempts to ensure that models are not only helpful and harmless, but also truthful and unbiased. However, optimizing these objectives simul…
Outgroup Animosity Has Risen for Politicians, Journalists, and a Sample of Partisan Users on Twitter and Reddit
Suyash Fulay, Deb Roy
Using language models, we analyze a sample of 67 million tweets and 30 million Reddit comments referencing a set of 215 political entities from 2010-2023 from partisan users, journ…
ConGraT: Self-Supervised Contrastive Pretraining for Joint Graph and Text Embeddings
William Brannon, Wonjune Kang, Suyash Fulay +4
Learning on text-attributed graphs (TAGs), in which nodes are associated with one or more texts, has been the subject of much recent work. However, most approaches tend to make str…
Divergences in Following Patterns between Influential Twitter Users and Their Audiences across Dimensions of Identity
Suyash Fulay, Nabeel Gillani, Deb Roy
Identity spans multiple dimensions; however, the relative salience of a dimension of identity can vary markedly from person to person. Furthermore, there is often a difference betw…