Open AccessJournal Article
Humans and automation: Use, misuse, disuse, abuse
Raja Parasuraman,Victor Riley +1 more
2.4K
TL;DR: In this paper, the authors address theoretical, empirical, and analytical studies pertaining to human use, misuse, disuse, and abuse of automation technology, and propose a method to detect false alarms and omissions.
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Abstract: This paper addresses theoretical, empirical, and analytical studies pertaining to human use, misuse, disuse, and abuse of automation technology. Use refers to the voluntary activation or disengagement of automation by human operators. Trust, mental workload, and risk can influence automation use, but interactions between factors and large individual differences make prediction of automation use difficult. Misuse refers to over reliance on automation, which can result in failures of monitoring or decision biases. Factors affecting the monitoring of automation include workload, automation reliability and consistency, and the saliency of automation state indicators. Disuse, or the neglect or underutilization of automation, is commonly caused by alarms that activate falsely. This often occurs because the base rate of the condition to be detected is not considered in setting the trade-off between false alarms and omissions. Automation abuse, or the automation of functions by designers and implementation by man...
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Citations
Trust in Automation: Designing for Appropriate Reliance
John D. Lee,Katrina A. See +1 more
TL;DR: This review considers trust from the organizational, sociological, interpersonal, psychological, and neurological perspectives, and considers how the context, automation characteristics, and cognitive processes affect the appropriateness of trust.
A model for types and levels of human interaction with automation
Raja Parasuraman,Thomas B. Sheridan,Christopher D. Wickens +2 more
- 01 May 2000
TL;DR: A model for types and levels of automation is outlined that can be applied to four broad classes of functions: 1) information acquisition; 2) information analysis; 3) decision and action selection; and 4) action implementation.
Artificial Intelligence (AI) : Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy
Yogesh K. Dwivedi,Laurie Hughes,Elvira Ismagilova,Gert Aarts,Crispin Coombs,Tom Crick,Yanqing Duan,Rohita Dwivedi,John S. Edwards,Aled Eirug,Vassilis Galanos,P. Vigneswara Ilavarasan,Marijn Janssen,Paul Jones,Arpan Kumar Kar,Hatice Kizgin,Bianca Kronemann,Banita Lal,Biagio Lucini,Rony Medaglia,Kenneth Le Meunier-FitzHugh,Leslie Caroline Le Meunier-FitzHugh,Santosh K. Misra,Emmanuel Mogaji,Sujeet Kumar Sharma,Jang Bahadur Singh,Vishnupriya Raghavan,Ramakrishnan Raman,Nripendra P. Rana,Spyridon Samothrakis,Jak Spencer,Kuttimani Tamilmani,Annie Tubadji,Paul Walton,Michael D. Williams +34 more
TL;DR: This research offers significant and timely insight to AI technology and its impact on the future of industry and society in general, whilst recognising the societal and industrial influence on pace and direction of AI development.
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Trust in Automation: Integrating Empirical Evidence on Factors That Influence Trust
Kevin A. Hoff,Masooda Bashir +1 more
TL;DR: A three-layered trust model provides a new lens for conceptualizing the variability of trust in automation and can be applied to help guide future research and develop training interventions and design procedures that encourage appropriate trust.
1.9K
A meta-analysis of factors affecting trust in human-robot interaction.
Peter A. Hancock,Deborah R. Billings,Kristin E. Schaefer,Jessie Y. C. Chen,Ewart J. de Visser,Raja Parasuraman +5 more
TL;DR: Factors related to the robot itself, specifically, its performance, had the greatest current association with trust, and environmental factors were moderately associated; there was little evidence for effects of human-related factors.
References
Adaptive aiding for human/computer control
TL;DR: Adaptive aiding is a human-machine system design concept that involves using aiding/automation only at those points in time when human performance in a system needs support to meet operational requ...
Automation- Induced "Complacency": Development of the Complacency-Potential Rating Scale
TL;DR: In this article, a 20-item scale was developed for measuring attitudes toward commonly encountered automated devices that reflect a potential for complacency, including confidence, reliance, trust, and safety.
Human factors and safety in the design of intelligent vehicle-highway systems (IVHS)
TL;DR: Several safety and human factors issues relevant to the design of IVHS technologies, both near-term and long-term, are discussed, and successful resolution of these issues will provide for fully functional systems that will serve the twin needs of reducing traffic congestion and improving highway safety.