Literature DB >> 16884046

Automation failures on tasks easily performed by operators undermine trust in automated aids.

Poornima Madhavan1, Douglas A Wiegmann, Frank C Lacson.   

Abstract

OBJECTIVE: We tested the hypothesis that automation errors on tasks easily performed by humans undermine trust in automation.
BACKGROUND: Research has revealed that the reliability of imperfect automation is frequently misperceived. We examined the manner in which the easiness and type of imperfect automation errors affect trust and dependence.
METHOD: Participants performed a target detection task utilizing an automated aid. In Study 1, the aid missed targets either on easy trials (easy miss group) or on difficult trials (difficult miss group). In Study 2, we manipulated both easiness and type of error (miss vs. false alarm). The aid erred on either difficult trials alone (difficult errors group) or on difficult and easy trials (easy miss group; easy false alarm group).
RESULTS: In both experiments, easy errors led to participants mistrusting and disagreeing more with the aid on difficult trials, as compared with those using aids that generated only difficult errors. This resulted in a downward shift in decision criterion for the former, leading to poorer overall performance. Misses and false alarms led to similar effects.
CONCLUSION: Automation errors on tasks that appear "easy" to the operator severely degrade trust and reliance. APPLICATION: Potential applications include the implementation of system design solutions that circumvent the negative effects of easy automation errors.

Entities:  

Mesh:

Year:  2006        PMID: 16884046     DOI: 10.1518/001872006777724408

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  13 in total

1.  A Little Anthropomorphism Goes a Long Way.

Authors:  Ewart J de Visser; Samuel S Monfort; Kimberly Goodyear; Li Lu; Martin O'Hara; Mary R Lee; Raja Parasuraman; Frank Krueger
Journal:  Hum Factors       Date:  2017-02       Impact factor: 2.888

Review 2.  Improving cardiac surgical care: a work systems approach.

Authors:  Douglas A Wiegmann; Ashley A Eggman; Andrew W Elbardissi; Sarah Henrickson Parker; Thoralf M Sundt
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3.  Trust in Medical Technology by Patients and Health Care Providers in Obstetric Work Systems.

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Review 4.  A systematic review of patient acceptance of consumer health information technology.

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Journal:  J Am Med Inform Assoc       Date:  2009-04-23       Impact factor: 4.497

5.  How different types of users develop trust in technology: a qualitative analysis of the antecedents of active and passive user trust in a shared technology.

Authors:  Jie Xu; Kim Le; Annika Deitermann; Enid Montague
Journal:  Appl Ergon       Date:  2014-05-29       Impact factor: 3.661

6.  Who Is to Blame? The Appearance of Virtual Agents and the Attribution of Perceived Responsibility.

Authors:  Tetsuya Matsui; Atsushi Koike
Journal:  Sensors (Basel)       Date:  2021-04-09       Impact factor: 3.576

7.  Automation Inner Speech as an Anthropomorphic Feature Affecting Human Trust: Current Issues and Future Directions.

Authors:  Alessandro Geraci; Antonella D'Amico; Arianna Pipitone; Valeria Seidita; Antonio Chella
Journal:  Front Robot AI       Date:  2021-04-23

Review 8.  From Trust in Automation to Decision Neuroscience: Applying Cognitive Neuroscience Methods to Understand and Improve Interaction Decisions Involved in Human Automation Interaction.

Authors:  Kim Drnec; Amar R Marathe; Jamie R Lukos; Jason S Metcalfe
Journal:  Front Hum Neurosci       Date:  2016-06-30       Impact factor: 3.169

9.  Psychological, Relational, and Emotional Effects of Self-Disclosure After Conversations With a Chatbot.

Authors:  Annabell Ho; Jeff Hancock; Adam S Miner
Journal:  J Commun       Date:  2018-05-30

10.  Learning From the Slips of Others: Neural Correlates of Trust in Automated Agents.

Authors:  Ewart J de Visser; Paul J Beatty; Justin R Estepp; Spencer Kohn; Abdulaziz Abubshait; John R Fedota; Craig G McDonald
Journal:  Front Hum Neurosci       Date:  2018-08-10       Impact factor: 3.169

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