AI Shall Have No Dominion: on How to Measure Technology Dominance in AI-supported Human Decision ...

AI Shall Have No Dominion: on How to Measure Technology Dominance in AI-supported Human Decision ...
Federico Cabitza, Andrea Campagner, Riccardo Angius, Chiara Natali, Carlo Reverberi

CHI 2023: The ACM CHI Conference on Human Factors in Computing Systems
Session: Human AI Collaboration_B

In this article, we propose a conceptual and methodological framework for measuring the impact of the introduction of AI systems in decision settings, based on the concept of technological dominance, i.e. the influence that an AI system can exert on human judgment and decisions. We distinguish between a negative component of dominance (automation bias) and a positive one (algorithm appreciation) by focusing on and systematizing the patterns of interaction between human judgment and AI support, or reliance patterns, and their associated cognitive effects. We then define statistical approaches for measuring these dimensions of dominance, as well as corresponding qualitative visualizations. By reporting about four medical case studies, we illustrate how the proposed methods can be used to inform assessments of dominance and of related cognitive biases in real-world settings. Our study lays the groundwork for future investigations into the effects of introducing AI support into naturalistic and collaborative decision-making.

Web:: https://programs.sigchi.org/chi/2023/program/content/96403

Pre-recorded presentation videos for papers at CHI 2023

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