Human-AI Cognition & Performance / Cognitive Performance
SUB-0005Decision Quality Under Load
Definition
Decision Quality Under Load 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
Decision Quality Under Load 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 AI present recommendations and uncertainty to improve decision quality during high-load conditions?
Hypotheses
Ranked options with explicit uncertainty and a forced independent judgement step will outperform single-answer recommendations under load.
Proposed methods
controlled task experiments; repeated-measures studies; ecological momentary assessment; interaction telemetry; interviews; 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
cognitive scientists; occupational psychologists; human-factors engineers; employers; educators; workers; AI product teams; decision scientists; accountable executives