collaborators

5 papers

cs.CY2025

Why They Disagree: Decoding Differences in Opinions about AI Risk on the Lex Fridman Podcast

Nghi Truong, Phanish Puranam, Özgecan Koçak

The emergence of transformative technologies often surfaces deep societal divisions, nowhere more evident than in contemporary debates about artificial intelligence (AI). A strikin…

cs.AI2025

Can LLMs Help Improve Analogical Reasoning For Strategic Decisions? Experimental Evidence from Humans and GPT-4

Phanish Puranam, Prothit Sen, Maciej Workiewicz

This study investigates whether large language models, specifically GPT4, can match human capabilities in analogical reasoning within strategic decision making contexts. Using a no…

cs.AI2025

Why Trust in AI May Be Inevitable

Nghi Truong, Phanish Puranam, Ilia Testlin

In human-AI interactions, explanation is widely seen as necessary for enabling trust in AI systems. We argue that trust, however, may be a pre-requisite because explanation is some…

cs.CL2025

Thinking with Many Minds: Using Large Language Models for Multi-Perspective Problem-Solving

Sanghyun Park, Boris Maciejovsky, Phanish Puranam

Complex problem-solving requires cognitive flexibility--the capacity to entertain multiple perspectives while preserving their distinctiveness. This flexibility replicates the "wis…

cs.CL2024

LLMs as mediators: Can they diagnose conflicts accurately?

Özgecan Koçak, Phanish Puranam, Afşar Yegin

Prior research indicates that to be able to mediate conflict, observers of disagreements between parties must be able to reliably distinguish the sources of their disagreement as s…