HAIC2027

The 1st Human–AI Interaction Conference

A dedicated venue for the science, design, and practice of how people and AI systems work together.

Call for Papers coming soon Key dates
DatesJune 27–30, 2027
LocationWashington, DC
Submission deadlineLate January 2027

Why a new conference

Human–AI interaction is already studied at CHI, CSCW, and UIST; at NeurIPS, ICML, ICLR, and COLM; at ACL, CVPR, and HRI; and at FAccT and AIES. No venue treats it as the central problem.

HAIC is built for work that examines people and AI systems as collaborators in shared activity — the protocols, representations, and mechanisms that make that collaboration work, and the methods that let us measure whether it does.

Frontier capabilities now move substantially within a single publication cycle. HAIC keeps pace through deep participation from the teams building and deploying frontier systems, a dedicated practice and deployment track, and review timelines calibrated to fast-moving capabilities.

Engagement with frontier AI

The program is designed to track foundation models and agentic systems as they are actually built, and to study collaboration on the most capable systems available rather than yesterday’s.

Translational impact

Moving findings into deployed systems across industry, science, healthcare, education, manufacturing, and public services — and bringing deployment lessons back into research.

Topic areas

Collaborative Intelligence & Teaming

How people and AI divide the work and the authority between them, and how a person keeps meaningful oversight of behavior that runs long or carries real risk.

Ethics, Safety & Societal Impact

Who gains and who loses as these systems enter workplaces and institutions, and what kind of oversight lets one be deployed safely without stalling it.

Interfaces, Techniques & Interactive Systems

Interaction past the chat box: direct manipulation, shared representations of state and intent, sensing and context, and the toolkits people build them with.

Evaluation, Methodology & Theories

How to tell whether a human–AI system actually works. Measures for collaboration quality, and studies that run long enough and close enough to real use to find out.

Human–AI Collaboration in Scientific Discovery

Research itself as a site of collaboration, from forming a hypothesis to running an autonomous lab and vouching for what comes out of it.

The full call for papers, with detailed topics and submission categories, is coming soon.