About

“Human-AI teaming” has become one of the most widely invoked concepts in AI research, design, and policy. Yet beneath the surface of this appealing phrase lies a set of unresolved questions that the research community has largely deferred. Rather than asking whether teaming is the correct term, this workshop asks a more generative question: what work does the teaming construct actually do, and for whom?

For researchers, it may offer a frame for studying coordination and division of labor. For designers, it may suggest interaction structures that go beyond tool use. For end-users, it may set expectations — helpful or misleading — about agency, accountability, and trust.

We bring together researchers from human-computer interaction, cognitive science, clinical studies, and AI to examine the functions and limits of the teaming concept, compare it against alternative framings such as augmentation, delegation, and scaffolding, and work toward a more precise vocabulary for describing and designing expert-AI collaboration.

Call for Participation

We invite position papers (2-4 pages, ACM format) that take a clear stance on whether teaming is a useful framework or a misleading metaphor for human-AI collaboration.

Submit via EasyChair (link TBD) by [DATE TBD], 11:59pm AOE. Notifications by August 7, 2026. At least one author must attend the workshop in person.