Addressing Cognitive Biases in Augmented Business Decision Systems
This addresses the problem of cognitive biases in business decision systems for managers and organizations, with incremental improvements in bias mitigation.
The study investigated how algorithmic decision aids affect business decision performance, finding that human-system collaboration achieved a 76% success rate, higher than either alone, but complacency bias degraded decisions by 5% when the recommender was wrong, and optional presentation was effective in reducing this bias.
How do algorithmic decision aids introduced in business decision processes affect task performance? In a first experiment, we study effective collaboration. Faced with a decision, subjects alone have a success rate of 72%; Aided by a recommender that has a 75% success rate, their success rate reaches 76%. The human-system collaboration had thus a greater success rate than each taken alone. However, we noted a complacency/authority bias that degraded the quality of decisions by 5% when the recommender was wrong. This suggests that any lingering algorithmic bias may be amplified by decision aids. In a second experiment, we evaluated the effectiveness of 5 presentation variants in reducing complacency bias. We found that optional presentation increases subjects' resistance to wrong recommendations. We conclude by arguing that our metrics, in real usage scenarios, where decision aids are embedded as system-wide features in Business Process Management software, can lead to enhanced benefits.