activity
20242026
most citedHuman Creativity in the Age of LLMs: Randomized Experiments on Divergent and Convergent Thinking

44 citations · 49 across the 11 of their papers we have counts for

collaborators

14 papers

cs.LG2026

Social Priors: Descriptions of AI Users Shape How Language Models Trust and Cooperate

Harsh Kumar, George Eilender, Ashton Anderson

Descriptions of how people use AI are becoming training data for the next generation of models. We ask whether what a model reads about its users changes how it treats people. Usin…

cs.CL2026

Emulate or Estimate? The Divergent Strengths of Base and Post-Trained Language Models for Opinion Simulation

Seth Grief-Albert, Jessica Bo, Difan Jiao +1

Large language models are increasingly used to simulate human opinions, but prior work reports conflicting results: some studies find promising alignment with human survey data, wh…

cs.CY2026

Position: We Need Large Language Models Optimized For Our Well-Being

Ashton Anderson, Harsh Kumar, Louis Tay +1

Large language models are useful because we taught them to give us what we want. This works when success can be judged immediately, but people increasingly bring these systems thei…

cs.CY2026

Studying People to Study AI: Expert Perspectives on the Epistemic Fit and Barriers of Human Research in AI Safety & Ethics

Jessica Y. Bo, Paula Akemi Aoyagui, Shalaleh Rismani +3

Safety risks of AI are becoming increasingly evident in human interactions with AI technologies. The prominent approaches to evaluating these risks favor technical methods, such as…

cs.CY2026

Diagnosing and Repairing Persona Collapse in LLM Advice

Harsh Kumar, Karina Vold, Louis Tay +1

A good advisor comforts someone in crisis, challenges someone in denial, and gives practical guidance on a logistical question. We ask whether large language models (LLMs) vary the…

cs.HC2026★ 1 cited

Human Thinking under Plural LLM Assistance: Mathematical Problem Solving and Open-Ended Writing

Harsh Kumar, Jace Mu, Jonathan Vincentius +1

Large language models are changing not only the kind of assistance people receive, but also how that assistance is organized. Instead of working with a single general-purpose chatb…

cs.HC2026

The Social Sycophancy Scale: A psychometrically validated measure of sycophancy

Jean Rehani, Victoria Oldemburgo de Mello, Dariya Ovsyannikova +2

Large Language Model (LLM) sycophancy is a growing concern. The current literature has largely examined sycophancy in contexts with clear right and wrong answers, like coding. Howe…

cs.AI2026

Language Models Exhibit Inconsistent Biases Towards Algorithmic Agents and Human Experts

Jessica Y. Bo, Lillio Mok, Ashton Anderson

Large language models are increasingly used in decision-making tasks that require them to process information from a variety of sources, including both human experts and other algo…

cs.HC2026

Large Language Lovers: Lived Experiences of Negotiating Agency and Platform Control in AI Companionship

Patrick Yung Kang Lee, Jessica Y. Bo, Zixin Zhao +6

Individuals are turning to increasingly anthropomorphic, general-purpose chatbots for AI companionship, rather than roleplay-specific platforms. However, not much is known about ho…

cs.HC2025

Invisible Saboteurs: Sycophantic LLMs Mislead Novices in Problem-Solving Tasks

Jessica Y. Bo, Majeed Kazemitabaar, Mengqing Deng +2

Sycophancy, the tendency of LLM-based chatbots to express excessive agreement with their users, even when inappropriate, is emerging as a significant risk in human-AI interactions.…

cs.HC2025

Who's the Leader? Analyzing Novice Workflows in LLM-Assisted Debugging of Machine Learning Code

Jessica Y. Bo, Majeed Kazemitabaar, Emma Zhuang +1

While LLMs are often touted as tools for democratizing specialized knowledge to beginners, their actual effectiveness for improving task performance and learning is still an open q…

cs.HC2024★ 1 cited

To Rely or Not to Rely? Evaluating Interventions for Appropriate Reliance on Large Language Models

Jessica Y. Bo, Sophia Wan, Ashton Anderson

As Large Language Models become integral to decision-making, optimism about their power is tempered with concern over their errors. Users may over-rely on LLM advice that is confid…

cs.HC2024★ 44 cited

Human Creativity in the Age of LLMs: Randomized Experiments on Divergent and Convergent Thinking

Harsh Kumar, Jonathan Vincentius, Ewan Jordan +1

Large language models are transforming the creative process by offering unprecedented capabilities to algorithmically generate ideas. While these tools can enhance human creativity…

cs.HC2024★ 3 cited

Large Language Model Agents for Improving Engagement with Behavior Change Interventions: Application to Digital Mindfulness

Harsh Kumar, Suhyeon Yoo, Angela Zavaleta Bernuy +6

Although engagement in self-directed wellness exercises typically declines over time, integrating social support such as coaching can sustain it. However, traditional forms of supp…