Literature DB >> 18689046

Review of a pivotal Human Factors article: "Humans and automation: use, misuse, disuse, abuse".

John D Lee1.   

Abstract

OBJECTIVE: This paper considers the influence of "Humans and Automation: Use, Misuse, Disuse, Abuse" and examines how it relates to the evolving issue of human-automation interaction.
BACKGROUND: Automation presents important practical challenges that can dramatically affect satisfaction, performance, and safety; philosophical challenges also arise as automation changes the nature of work and human cognition.
METHOD: Papers cited by and citing "Humans and Automation" were reviewed to identify enduring and emerging themes in human-automation research.
RESULTS: "Humans and Automation" emerges as an important node in the network of automation-related papers, citing many and being cited by many recent influential automation-related papers. In their article, Parasuraman and Riley (1997) integrated previous research and identified differing expectations across designers, managers, and operators regarding the need to support operators as a source of automation problems. They also foresaw and inspired research that addresses problems of overreliance and underreliance on automation.
CONCLUSION: This pivotal article and associated research show that even though automation seems to relieve people of tasks, automation requires more, not less, attention to training, interface design, and interaction design. The original article also alludes to the emergence of vicious cycles and dysfunctional meta-control. These problems reflect the coevolution of automation and humans, in which both adapt to the responses of the other. APPLICATION: Understanding this coevolution has important philosophical implications for the nature of human cognition and practical implications for satisfaction, performance, and safety.

Entities:  

Mesh:

Year:  2008        PMID: 18689046     DOI: 10.1518/001872008X288547

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


  7 in total

1.  Automatic notifications mediated by anesthesia information management systems reduce the frequency of prolonged gaps in blood pressure documentation.

Authors:  Jesse M Ehrenfeld; Richard H Epstein; Stephen Bader; Sachin Kheterpal; Warren S Sandberg
Journal:  Anesth Analg       Date:  2011-03-17       Impact factor: 5.108

2.  Looking for Age Differences in Self-Driving Vehicles: Examining the Effects of Automation Reliability, Driving Risk, and Physical Impairment on Trust.

Authors:  Ericka Rovira; Anne Collins McLaughlin; Richard Pak; Luke High
Journal:  Front Psychol       Date:  2019-04-26

3.  Automation-Induced Complacency Potential: Development and Validation of a New Scale.

Authors:  Stephanie M Merritt; Alicia Ako-Brew; William J Bryant; Amy Staley; Michael McKenna; Austin Leone; Lei Shirase
Journal:  Front Psychol       Date:  2019-02-19

4.  Scared to Trust? - Predicting Trust in Highly Automated Driving by Depressiveness, Negative Self-Evaluations and State Anxiety.

Authors:  Johannes Kraus; David Scholz; Eva-Maria Messner; Matthias Messner; Martin Baumann
Journal:  Front Psychol       Date:  2020-01-23

5.  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

6.  Out of the Loop, in Your Bubble: Mind Wandering Is Independent From Automation Reliability, but Influences Task Engagement.

Authors:  Jonas Gouraud; Arnaud Delorme; Bruno Berberian
Journal:  Front Hum Neurosci       Date:  2018-09-20       Impact factor: 3.169

7.  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

  7 in total

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