most citedFuture of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce

6 citations · 14 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CY2026

Method, Mind, and Morality: How People Make Sense of Artificial Intelligence

Jacy Reese Anthis, Erik Brynjolfsson, James Evans

How can humans make sense of the rapid takeoff of artificial intelligence (AI)? We studied the sensemaking dynamics of AI through an open-ended, mixed-methods study with computatio…

cs.AI2026

AISPA: User-Centric System Prompt Auditing for Large Language Model Applications

Xiangning Lin, Shenzhe Zhu, Shu Yang +23

System prompts are instructions configured by developers to govern the behaviors of foundation models in AI applications. They are used throughout commercial AI products, but are r…

cs.CL2026★ 1 cited

How Do AI Agents Spend Your Money? Analyzing and Predicting Token Consumption in Agentic Coding Tasks

Longju Bai, Zhemin Huang, Xingyao Wang +5

The wide adoption of AI agents in complex human workflows is driving rapid growth in LLM token consumption. When agents are deployed on tasks that require a significant amount of t…

cs.CL2026

On Safety Risks in Experience-Driven Self-Evolving Agents

Weixiang Zhao, Yichen Zhang, Yingshuo Wang +8

Experience-driven self-evolution has emerged as a promising paradigm for improving the autonomy of large language model agents, yet its reliance on self-curated experience introduc…

cs.AI2025★ 3 cited

A Definition of AGI

Dan Hendrycks, Dawn Song, Christian Szegedy +30

The lack of a concrete definition for Artificial General Intelligence (AGI) obscures the gap between today's specialized AI and human-level cognition. This paper introduces a quant…

cs.HC2025

AI Behavioral Science: A Framework and Agenda

Matthew O. Jackson, Qiaozhu Me, Stephanie W. Wang +16

We discuss the challenges and opportunities present in the rapidly emerging area of ``AI Behavioral Science.'' We frame it via three subfields. First, as AI becomes ubiquitous and…

cs.CY2025★ 6 cited

Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce

Yijia Shao, Humishka Zope, Yucheng Jiang +4

The rapid rise of compound AI systems (a.k.a., AI agents) is reshaping the labor market, raising concerns about job displacement, diminished human agency, and overreliance on autom…

cs.HC2025★ 4 cited

LLM Social Simulations Are a Promising Research Method

Jacy Reese Anthis, Ryan Liu, Sean M. Richardson +5

Accurate and verifiable large language model (LLM) simulations of human research subjects promise an accessible data source for understanding human behavior and training new AI sys…