Human-AI Collaboration

Striking a Balance: Evaluating How Aggregations of Multiple Forecasts Impact Judgment Under Uncertainty

With the growing availability of quantitative forecasts from various sources, effectively communicating these multiple forecasts has become increasingly crucial. Recent advances have explored using Multiple-Forecast Visualizations (MFVs) to display …

Exploring Collaboration Breakdowns Between Provider Teams and Patients in Post-Surgery Care

Post-surgery care involves ongoing collaboration between provider teams and patients, which starts from post-surgery hospitalization through home recovery after discharge. While prior HCI research has primarily examined patients’ challenges at home, …

XSynth: GenAI-Empowered Shared Mental Model Building for Conceptual Design Collaboration in Extended Reality

Through the Lens of Human-Human Collaboration: An Configurable Research Platform for Exploring Human-Agent Collaboration

Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight

The dark patterns, deceptive interface designs manipulating user behaviors, have been extensively studied for their effects on human decision-making and autonomy. Yet, with the rising prominence of LLM-powered GUI agents that automate tasks from …

Bridging Knowledge Gaps in Clinical AI: An Activity Theory Perspective on Interdisciplinary Data Work for Telehealth

Vital Insight: Assisting Experts’ Context-Driven Sensemaking of Multi-modal Personal Tracking Data Using Visualization and Human-in-the-Loop LLM

“Mango Mango, How to Let The Lettuce Dry Without A Spinner?”: Exploring User Perceptions of Using An LLM-Based Conversational Assistant Toward Cooking Partner

Secret Use of Large Language Model (LLM)

The advancements of Large Language Models (LLMs) have decentralized the responsibility for the transparency of AI usage. Specifically, LLM users are now encouraged or required to disclose the use of LLM-generated content for varied types of …

Towards Feature Engineering with Human and AI’s Knowledge: Understanding Data Science Practitioners’ Perceptions in Human&AI-Assisted Feature Engineering Design