activity
20212026
most citedChatbot Companionship: A Mixed-Methods Study of Companion Chatbot Usage Patterns and Their Relationship to Loneliness in Active Users

25 citations · 94 across the 27 of their papers we have counts for

collaborators

32 papers

cs.HC2026

Open Benchmark of AI Impact on Humans (ImpactBench): an expert-guided, open platform for the holistic evaluation of AI impact on humans

Chayapatr Archiwaranguprok, Krystal Kirkland, Rachel Poonsiriwong +17

The present work is concerned with how to measure, at scale, the multi-dimensional impact of generative AI models on the individuals who use them. In service of this goal, we intro…

cs.AI2026

AI Watchdog: Agent Interfaces for Detecting and Defending Against Manipulative Dark Patterns in AI Conversations

Rachel Poonsiriwong, Chayapatr, Archiwaranguprok +4

Conversational AI increasingly shapes consequential decisions, yet users have limited support for recognizing and resisting manipulation. We present AI Watchdog, a browser-based ag…

cs.LG2026

Dissociating the Internal Representations of Sycophancy in LLMs

Anthony Baez, Sheer Karny, Pat Pataranutaporn

Large Language Models (LLMs) frequently exhibit sycophancy, agreeing with a user's statement even when it is incorrect. While often studied as a single, uniform behavior, sycophanc…

cs.HC2026

Surfacing Neural Activations Over Multi-Turn Conversation Improves User Calibration to LLM Behavioral Drift

Sheer Karny, Anthony Baez, Pat Pataranutaporn

Current human-AI interaction (HAI) only surfaces model outputs, hiding how LLM behavior can shift unpredictably toward unsafe behaviors in multi-turn conversations, potentially und…

cs.HC2026

AI-Wrapped: Participatory, Privacy-Preserving Measurement of Longitudinal LLM Use In-the-Wild

Cathy Mengying Fang, Sheer Karny, Chayapatr Archiwaranguprok +3

Alignment research on large language models (LLMs) increasingly depends on understanding how these systems are used in everyday contexts. Yet naturalistic interaction data is diffi…

cs.CY2026

AI-Generated Letters from the Future: A Randomized Test of Personalized Climate Communication

Nattavudh Powdthavee, Pat Pataranutaporn, Sandra J. Geiger +2

We examined whether personalized, AI-generated letters from the future can increase public engagement with climate action. In a preregistered online experiment with 1,654 U.S. pare…

cs.HC2026★ 1 cited

"Death" of a Chatbot: Investigating and Designing Toward Psychologically Safe Endings for Human-AI Relationships

Rachel Poonsiriwong, Chayapatr Archiwaranguprok, Pat Pataranutaporn

Millions of users form emotional attachments to AI companions like Character AI, Replika, and ChatGPT. When these relationships end through model updates, safety interventions, or…

cs.HC2025

Human-AI Interaction Alignment: Designing, Evaluating, and Evolving Value-Centered AI For Reciprocal Human-AI Futures

Hua Shen, Tiffany Knearem, Divy Thakkar +9

The rapid integration of generative AI into everyday life underscores the need to move beyond unidirectional alignment models that only adapt AI to human values. This workshop focu…

cs.HC2025

Simulating Life Paths with Digital Twins: AI-Generated Future Selves Influence Decision-Making and Expand Human Choice

Rachel Poonsiriwong, Chayapatr Archiwaranguprok, Constanze Albrecht +6

Major life transitions demand high-stakes decisions, yet people often struggle to imagine how their future selves will live with the consequences. To support this limited capacity…

cs.HC2025★ 2 cited

Future You: Designing and Evaluating Multimodal AI-generated Digital Twins for Strengthening Future Self-Continuity

Constanze Albrecht, Chayapatr Archiwaranguprok, Rachel Poonsiriwong +7

What if users could meet their future selves today? AI-generated future selves simulate meaningful encounters with a digital twin decades in the future. As AI systems advance, comb…

cs.HC2025

Neural Transparency: Mechanistic Interpretability Interfaces for Anticipating Model Behaviors for Personalized AI

Sheer Karny, Anthony Baez, Pat Pataranutaporn

Millions of users now design personalized LLM-based chatbots that shape their daily interactions, yet they can only roughly anticipate how their design choices will manifest as beh…

cs.HC2025★ 3 cited

Simulating Psychological Risks in Human-AI Interactions: Real-Case Informed Modeling of AI-Induced Addiction, Anorexia, Depression, Homicide, Psychosis, and Suicide

Chayapatr Archiwaranguprok, Constanze Albrecht, Pattie Maes +2

As AI systems become increasingly integrated into daily life, their potential to exacerbate or trigger severe psychological harms remains poorly understood and inadequately tested.…

cs.HC2025

Atlas of Human-AI Interaction: An Interactive Knowledge Graph for Research Sensemaking at Scale

Chayapatr Archiwaranguprok, Awu Chen, Rachel Poonsiriwong +4

The growth and fragmentation of scientific literature make it increasingly difficult for researchers to synthesize findings and build on prior work. This paper presents a framework…

cs.HC2025★ 7 cited

"My Boyfriend is AI": A Computational Analysis of Human-AI Companionship in Reddit's AI Community

Pat Pataranutaporn, Sheer Karny, Chayapatr Archiwaranguprok +3

The emergence of AI companion applications has created novel forms of intimate human-AI relationships, yet empirical research on these communities remains limited. We present the f…

cs.HC2025

Large Language Models Predict Human Well-being -- But Not Equally Everywhere

Pat Pataranutaporn, Nattavudh Powdthavee, Chayapatr Archiwaranguprok +1

Subjective well-being is a key metric in economic, medical, and policy decision-making. As artificial intelligence provides scalable tools for modelling human outcomes, it is cruci…

cs.HC2025★ 17 cited

Investigating Affective Use and Emotional Well-being on ChatGPT

Jason Phang, Michael Lampe, Lama Ahmad +8

As AI chatbots see increased adoption and integration into everyday life, questions have been raised about the potential impact of human-like or anthropomorphic AI on users. In thi…

cs.CY2025★ 1 cited

Can AI Solve the Peer Review Crisis? A Large Scale Cross Model Experiment of LLMs' Performance and Biases in Evaluating over 1000 Economics Papers

Pat Pataranutaporn, Nattavudh Powdthavee, Chayapatr Achiwaranguprok +1

This study examines the potential of large language models (LLMs) to augment the academic peer review process by reliably evaluating the quality of economics research without intro…

cs.HC2025

AI persuading AI vs AI persuading Humans: LLMs' Differential Effectiveness in Promoting Pro-Environmental Behavior

Alexander Doudkin, Pat Pataranutaporn, Pattie Maes

Pro-environmental behavior (PEB) is vital to combat climate change, yet turning awareness into intention and action remains elusive. We explore large language models (LLMs) as tool…

cs.HC2025

How AI and Human Behaviors Shape Psychosocial Effects of Extended Chatbot Use: A Longitudinal Randomized Controlled Study

Cathy Mengying Fang, Auren R. Liu, Valdemar Danry +8

As people increasingly seek emotional support and companionship from AI chatbots, understanding how such interactions impact mental well-being becomes critical. We conducted a four…

cs.CY2025

Algorithmic Inheritance: Surname Bias in AI Decisions Reinforces Intergenerational Inequality

Pat Pataranutaporn, Nattavudh Powdthavee, Pattie Maes

Surnames often convey implicit markers of social status, wealth, and lineage, shaping perceptions in ways that can perpetuate systemic biases and intergenerational inequality. This…

cs.HC2025

OceanChat: The Effect of Virtual Conversational AI Agents on Sustainable Attitude and Behavior Change

Pat Pataranutaporn, Alexander Doudkin, Pattie Maes

Marine ecosystems face unprecedented threats from climate change and plastic pollution, yet traditional environmental education often struggles to translate awareness into sustaine…

cs.HC2024★ 25 cited

Chatbot Companionship: A Mixed-Methods Study of Companion Chatbot Usage Patterns and Their Relationship to Loneliness in Active Users

Auren R. Liu, Pat Pataranutaporn, Pattie Maes

Companion chatbots offer a potential solution to the growing epidemic of loneliness, but their impact on users' psychosocial well-being remains poorly understood, raising critical…

cs.HC2024★ 2 cited

Synthetic Human Memories: AI-Edited Images and Videos Can Implant False Memories and Distort Recollection

Pat Pataranutaporn, Chayapatr Archiwaranguprok, Samantha W. T. Chan +2

AI is increasingly used to enhance images and videos, both intentionally and unintentionally. As AI editing tools become more integrated into smartphones, users can modify or anima…

cs.HC2024

Text2Tradition: From Epistemological Tensions to AI-Mediated Cross-Cultural Co-Creation

Pat Pataranutaporn, Chayapatr Archiwaranguprok, Phoomparin Mano +3

This paper introduces Text2Tradition, a system designed to bridge the epistemological gap between modern language processing and traditional dance knowledge by translating user-gen…