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

AI-Assisted Decision-Making & AutomationAI Ethics, Fairness & AccountabilityAlgorithmic Transparency & AuditabilityData Scientists & AnalystsAI/ML Researchers & Engineers

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.

Quick Actions

Share

Share this page

ios_share

https://hci.top/en/papers/chi/96403/2023

AdRecommended

Learn AI Coding at CodeNow

open_in_newOpen DOI Link
DOI: https://doi.org/10.1145/3544548.3581095
At a Glance

Paper Snapshot

fact_check
dataset
Source
CHI
calendar_month
Year
2023
emoji_events
Award
No award tagged
group
Authors
5 authors
sell
Subtopics
AI-Assisted Decision-Making & Automation, AI Ethics, Fairness & Accountability, Algorithmic Transparency & Auditability
work
Professions
Data Scientists & Analysts, AI/ML Researchers & Engineers
article
Content Status
Abstract only
hub
Related Papers
4 related papers