Literature DB >> 31422272

Who's the real expert here? Pedigree's unique bias on trust between human and automated advisers.

Carl J Pearson1, Michael Geden2, Christopher B Mayhorn2.   

Abstract

OBJECTIVE: We assessed the effects of source type bias (human or automation) on adviser trust in a dual adviser decision-making task.
BACKGROUND: Source type and reliability's effects on adviser trust have been studied in a dual-adviser context, but the influence of pedigree (perceived expertise) across source types lacked robust investigation. As situations with two decision-aids of uneven pedigree can easily arise, it is critical to understand how operators are biased towards a decision-aid of a certain source type and pedigree.
METHOD: A decision-making task similar to the paradigm of Convoy Leader (Lyons and Stokes, 2012) was given to participants, where a military convoy route had to be selected in the presence of IEDs and insurgent activity. We measured behavioral reliance and trust attitudes. Pedigree was manipulated via controlled adviser descriptions, in a manner consistent with past investigations (Madhavan and Wiegmann, 2007a).
RESULTS: We found a trust bias towards the human adviser, reversed only when there is a far greater pedigree in the automated adviser. Trust attitudes were also strongly indicative of reliance behaviors.
CONCLUSION: Pedigree is a strong influencer of trust in a decision-aid and biased towards human advisers. Trust is highly predictive of reliance decisions. APPLICATION: System designers must take care with how "expert" automation is portrayed, particularly if it is used in conjunction with other human advisers (e.g.: conflicting advice from air-traffic control and an onboard system).
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Decision aid; Decision support system; Decision-making; Dual adviser; Reliance; Trust in automation

Mesh:

Year:  2019        PMID: 31422272     DOI: 10.1016/j.apergo.2019.102907

Source DB:  PubMed          Journal:  Appl Ergon        ISSN: 0003-6870            Impact factor:   3.661


  1 in total

1.  Clinician and computer: a study on patient perceptions of artificial intelligence in skeletal radiography.

Authors:  Thomas York; Heloise Jenney; Gareth Jones
Journal:  BMJ Health Care Inform       Date:  2020-11
  1 in total

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