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cs.HC2026
WhatIf: Interactive Exploration of Large-Scale LLM Agent Simulations for Policy Reasoning
Yuxuan Li, Kyzyl Monteiro, Hirokazu Shirado +1
Policymakers in domains such as emergency management, public health, and urban planning must make decisions under deep uncertainty, where outcomes depend on how large populations i…
cs.HC2026
Faith in AI can narrow the futures individuals consider
Aoi Naito, Hirokazu Shirado
Artificial intelligence (AI) predictions are increasingly used to inform human decisions. Here, using a behavioral implementation of the classic Newcomb's paradox in 1,305 particip…
cs.HC2025
What Makes LLM Agent Simulations Useful for Policy Practice? An Iterative Design Study in Emergency Preparedness
Yuxuan Li, Sauvik Das, Hirokazu Shirado
Policymakers must often act under conditions of deep uncertainty, such as emergency response, where predicting the specific impacts of a policy apriori is implausible. Large Langua…