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Human-Computer Decision Systems

Describes work to use learning theory advances to account for persistent human expert teams and experiments to improve the human-computer decision system

Software Engineering Institute



After examining why current approaches are inadequate, the SEI researchers examined what is needed to know whether a new approach works. They explore these factors: realistic data (class and feature distributions that relate to a transition domain), human participants (actual errors and learning patterns), and ground truth (because we know labelers are fallible).