arXiv AI

Designing AI-Supported Focus Groups: A Role x Modality Playbook

arXiv:2606. 11835v1 Announce Type: cross Abstract: Collecting participants' lived experiences is central to design research.

arXiv AI
Jun 15

Thinking Outside the [Chat]Box: Bridging Computer Science and Industrial Design for Cognitive-Inclusive Generative AI

arXiv:2606. 14306v1 Announce Type: cross Abstract: Current Generative AI (GenAI) interfaces remain largely constrained to chatbox interaction, which can impose high cognitive demands on users and create substantial barriers for people with intellectual disabilities (ID), including prompt formulation difficulties, response overload, and limited mechanisms to assess information reliability.

By Virginia Francisco, Daniel Guasch, Raquel Herv\'as
arXiv AI
Jun 10

Human-AI Coordination Zones: A Framework for Designing Human-in-the-Loop Experiences with Agentic AI

arXiv:2606. 09848v1 Announce Type: cross Abstract: As generative and agentic AI becomes embedded in everyday products, practitioners face a persistent challenge: how to design human-AI coordination -- the ongoing mutual adjustment between users and AI systems as mediate through interfaces-that supports usability, trust, and safety.

By James Pierce, Vaiva Kalnikait\.e, Siddharth Gupta, Brian Granger
arXiv AI
Jul 15

Toward Metaphor-Fluid Conversation Design for Voice User Interfaces

arXiv:2502. 11554v3 Announce Type: replace-cross Abstract: Metaphors play a critical role in shaping user experiences with Voice User Interfaces (VUIs), yet existing designs often rely on static, human-centric metaphors that fail to adapt to diverse contexts and user needs.

By Smit Desai, Jessie Chin, Dakuo Wang, Benjamin Cowan, Michael Twidale
arXiv AI
Jul 24

HARP: The Human--AI Research Platform

arXiv:2607. 20773v1 Announce Type: cross Abstract: Large language models (LLMs) have shifted human--computer interaction from `traditional'' interface journeys toward more conversational exchanges.

By Zeshu Zhu, Natalie Friedman, Kevin Weatherwax, Emily Eiben
Hugging Face Trending Papers
Jul 4

ProACT: Towards Breakdown-Aware Proactive Agent in Multi-User Collaboration

Conversational agents are increasingly embedded in human collaborative work, yet they remain fundamentally passive and reactive: they respond to explicit user requests rather than proactively recognizing moments when a team would benefit from timely intervention as human collaborators often do. This reactive design substantially limits the use of agents as active participants in multi-user collaboration, where disagreements, ambiguous goals, forgotten constraints, underspecified plans, discussion loops, and imbalanced participation can gradually undermine group progress.