Work

Five Degrees of Separation: Investigating the Unexpected Potential of Displaced Human-AI Collaboration Protocols for Apter AI Support

Year: 2025

Type: article

Abstract: The integration of AI into decision-making processes offers substantial benefits, particularly in enhancing accuracy and efficiency. However, long-term consequences, such as over-reliance, skill erosion, and loss of human agency, present significant challenges. This study investigates various human-AI collaboration protocols~-~traditional, inhibition, displacement, and replacement~-~across multiple medical settings, including radiological imaging, ECG, and endoscopy. We introduce a novel framework that includes a choice nomogram and qualitative assessment tool, designed to optimize both decision accuracy and socio-technical impacts. Our findings reveal that the displacement protocol consistently outperformed others in several contexts, achieving 87% accuracy in MRI analysis, 89% in x-ray reading and 85% in endoscopy; conversely, the traditional protocol was most effective only in ECG analysis, with 82% accuracy. These results demonstrate that no single protocol is universally optimal, highlighting the need for context-specific selection to ensure effective and sustainable AI-supported decision-making, with a focus on balancing short-term performance with long-term human factors.

Source: Proceedings of the ACM on Human-Computer Interaction

DOI: 10.1145/3757601