Effect of System Type And Information on Miners’ Decisions and Trust in AI-based Monitoring Systems

Abstract

Trust in AI systems and the nature and amount of information about the system can influence decision-making. It is, therefore, crucial to understand how AI-powered monitoring systems (e.g., gas monitoring systems) influence miners' trust and decision-making in emergency evacuation. This work focused on measuring the differences between how participants respond to a simulated underground mine emergency evacuation situation when warnings are represented as coming from a human or AI-based monitoring system. We also manipulated the amount of information participants received about the system, yielding a 2x2 between-participants survey design. The participants received an alert message about rising gas levels in a mine and provided a response on how they would react and reported their perceived safety. We also asked questions to assess their trust in, preference for AI over human-based gas monitoring systems, and whether they are willing to delegate the duties of underground gas monitoring to AI systems. The experiment results show the amount of information had a significant influence on miners' trust and decision-making. The safety perception of participants based on age, number of children and ethnicity was significantly different from one category to another. This work provides valuable insights as the mining industry deploys AI systems to aid mine safety.

Department(s)

Mining Engineering

Second Department

Psychological Science

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2025 Society for Mining, Metallurgy and Exploration, Inc., All rights reserved.

Publication Date

01 Jan 2025

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