Human-AI Cognition & Performance / Human–AI Collaboration
SUB-0029Agent Collaboration with Humans
Definition
Agent Collaboration with Humans examines the mechanisms, conditions and outcomes through which this factor shapes human cognition, learning, collaboration or sustainable performance in AI-supported settings.
Why this matters
Agent Collaboration with Humans may materially affect human capability, independence, confidence, safety and productivity. Poorly designed assistance can create hidden costs even where short-term output appears to improve.
Research questions
How should autonomous agents coordinate with people across multi-step work?
Hypotheses
Explicit commitments, checkpoints and state visibility will improve reliability more than conversational status updates.
Proposed methods
workflow experiments; task-allocation trials; simulation; incident analysis; ethnography; decision audits; controlled handover tests; pre-registered analysis; active comparison; subgroup and accessibility analysis; delayed retention or longitudinal follow-up; adverse-effect capture; reproducibility testing; participant debrief
Stakeholders and beneficiaries
workers; team leaders; boards; risk officers; AI vendors; unions; customers; regulators; auditors; team-science researchers; workflow architects