Human–AI Task Allocation

Definition

Human–AI Task Allocation 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

Human–AI Task Allocation 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

Which tasks should remain human-led, AI-led or jointly performed under different risk and capability conditions?

Hypotheses

Allocation using consequence, reversibility and comparative capability will outperform automation-potential scoring.

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; work design specialists; labour representatives