Citation

Lyons JB, Stokes CK. Hum. Factors 2012; 54(1): 112-121.

Affiliation

Air Force Office of Scientific Research, 875 N. Randolph Street, Suite 325, Arlington, VA 22203, USA. Joseph.lyons@afosr.af.mil

Copyright

(Copyright © 2012, Human Factors and Ergonomics Society, Publisher SAGE Publishing)

DOI

unavailable

PMID

22409106

Abstract

OBJECTIVE: The current study examined human-human reliance during a computer-based scenario where participants interacted with a human aid and an automated tool simultaneously. BACKGROUND: Reliance on others is complex, and few studies have examined human-human reliance in the context of automation. Past research found that humans are biased in their perceived utility of automated tools such that they view them as more accurate than humans. Prior reviews have postulated differences in human-human versus human-machine reliance, yet few studies have examined such reliance when individuals are presented with divergent information from different sources. METHOD: Participants (N = 40) engaged in the Convoy Leader experiment.They selected a convoy route based on explicit guidance from a human aid and information from an automated map. Subjective and behavioral human-human reliance indices were assessed. Perceptions of risk were manipulated by creating three scenarios (low, moderate, and high) that varied in the amount of vulnerability (i.e., potential for attack) associated with the convoy routes. RESULTS: Results indicated that participants reduced their behavioral reliance on the human aid when faced with higher risk decisions (suggesting increased reliance on the automation); however, there were no reported differences in intentions to rely on the human aid relative to the automation. CONCLUSION: The current study demonstrated that when individuals are provided information from both a human aid and automation,their reliance on the human aid decreased during high-risk decisions. APPLICATION: This study adds to a growing understanding of the biases and preferences that exist during complex human-human and human-machine interactions.

Language: en