Literature DB >> 15151155

Trust in automation: designing for appropriate reliance.

John D Lee1, Katrina A See.   

Abstract

Automation is often problematic because people fail to rely upon it appropriately. Because people respond to technology socially, trust influences reliance on automation. In particular, trust guides reliance when complexity and unanticipated situations make a complete understanding of the automation impractical. This review considers trust from the organizational, sociological, interpersonal, psychological, and neurological perspectives. It considers how the context, automation characteristics, and cognitive processes affect the appropriateness of trust. The context in which the automation is used influences automation performance and provides a goal-oriented perspective to assess automation characteristics along a dimension of attributional abstraction. These characteristics can influence trust through analytic, analogical, and affective processes. The challenges of extrapolating the concept of trust in people to trust in automation are discussed. A conceptual model integrates research regarding trust in automation and describes the dynamics of trust, the role of context, and the influence of display characteristics. Actual or potential applications of this research include improved designs of systems that require people to manage imperfect automation.

Entities:  

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Year:  2004        PMID: 15151155     DOI: 10.1518/hfes.46.1.50_30392

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


  115 in total

1.  [Clinical efficiency and the influence of human factors on ear, nose, and throat navigation systems].

Authors:  G Strauss; K Koulechov; S Röttger; J Bahner; C Trantakis; M Hofer; W Korb; O Burgert; J Meixensberger; D Manzey; A Dietz; T Lüth
Journal:  HNO       Date:  2006-12       Impact factor: 1.284

2.  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

3.  Toward a framework for levels of robot autonomy in human-robot interaction.

Authors:  Jenay M Beer; Arthur D Fisk; Wendy A Rogers
Journal:  J Hum Robot Interact       Date:  2014-07

4.  Understanding reliance on automation: effects of error type, error distribution, age and experience.

Authors:  Julian Sanchez; Wendy A Rogers; Arthur D Fisk; Ericka Rovira
Journal:  Theor Issues Ergon Sci       Date:  2014-03

Review 5.  Automation bias: a systematic review of frequency, effect mediators, and mitigators.

Authors:  Kate Goddard; Abdul Roudsari; Jeremy C Wyatt
Journal:  J Am Med Inform Assoc       Date:  2011-06-16       Impact factor: 4.497

6.  Opinion: The dangers of faulty, biased, or malicious algorithms requires independent oversight.

Authors:  Ben Shneiderman
Journal:  Proc Natl Acad Sci U S A       Date:  2016-11-23       Impact factor: 11.205

7.  Organizational and technological correlates of nurses' trust in a smart intravenous pump.

Authors:  Enid Montague; Onur Asan; Erin Chiou
Journal:  Comput Inform Nurs       Date:  2013-03       Impact factor: 1.985

8.  Directing driver attention with augmented reality cues.

Authors:  Michelle L Rusch; Mark C Schall; Patrick Gavin; John D Lee; Jeffrey D Dawson; Shaun Vecera; Matthew Rizzo
Journal:  Transp Res Part F Traffic Psychol Behav       Date:  2013-01

9.  Leading Teams in the Digital Age: Four Perspectives on Technology and What They Mean for Leading Teams.

Authors:  Lindsay Larson; Leslie DeChurch
Journal:  Leadersh Q       Date:  2020-01-13

10.  Social and personal normative influences on healthcare professionals to use information technology: Towards a more robust social ergonomics.

Authors:  Richard J Holden
Journal:  Theor Issues Ergon Sci       Date:  2011-03-28
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