1 citations · 1 across the 4 of their papers we have counts for
7 papers
ExploraTwin, a Non-Profit Research Platform for Digital Twin Simulations
Naveen Venkat, Naveen Venkatanarayanan, Yuchen Qiu +3
Digital twin simulations show promise, but current empirical evidence suggests that the approach should be tested before being deployed in any particular context. To lower the fric…
Innovating with Generative AI: A Human Bottleneck Framework
Julian De Freitas, Ayelet Israeli, Gideon Nave +2
We propose a human bottleneck perspective for understanding how generative AI transforms the innovation process. The central premise is that many constraints traditionally plaguing…
Synthetic Contact with AI Reduces Cross-Partisan Animosity
Benjamin Lira, Noah Castelo, Stefano Puntoni +1
Americans' warmth toward members of the opposing political party has fallen sharply over the past three decades -- yet meaningful cross-partisan contact remains scarce, in part bec…
Digital Twins as Funhouse Mirrors: Five Key Distortions
Tianyi Peng, George Gui, Melanie Brucks +20
Scientists and practitioners are increasingly moving to deploy digital twins--LLM-based models of real individuals--across social science and policy research. We conduct 19 pre-reg…
Examining and Addressing Barriers to Diversity in LLM-Generated Ideas
Yuting Deng, Melanie Brucks, Olivier Toubia
Ideas generated by independent samples of humans tend to be more diverse than ideas generated from independent LLM samples, raising concerns that widespread reliance on LLMs could…
The Challenge of Using LLMs to Simulate Human Behavior: A Causal Inference Perspective
George Gui, Olivier Toubia
Large Language Models (LLMs) have shown impressive potential to simulate human behavior. We identify a fundamental challenge in using them to simulate experiments: when LLM-simulat…