A model for types and levels of human interaction with automation

By Raja Parasuraman, Thomas B. Sheridan, C. Wickens. 2000

4,147 citations recorded by the source corpus.

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Citations in the corpus

Research Priorities for Robust and Beneficial Artificial Intelligence (2015, background): “…the themes of short-term research, research enabling veriﬁable low-level software and hardware can eliminate large classes of bugs and problems in general AI systems; if such systems become increasingly powerful and safety-critical, veriﬁable safety properties will become increasingly valuable.”
Human–Agent Teaming for Multirobot Control: A Review of Human Factors Issues (2014, background): “acquisition, information analysis, decision making, and action implementation) [68]; they reported that automating the information acquisition part of the task was most beneficial for sup-”
Situation Awareness and Workload in Aviation (2002, background): “…upon this complexity are the fascinating challenges of understanding how powerful yet imperfect computer automation, in predictor displays, warnings, inference making, and flight management, affects pilots’ situation awareness, mental workload, and task management (Parasuraman et al., 2000).”
The Automation-by-Expertise-by-Training Interaction (2017, background): “…system status changes or not, and the automation can change operating modes with varying levels of agreement with and/or input from the operator (Parasuraman, Bahri, Deaton, Morrison, & Barnes, 1992; Parasuraman, Sheridan, & Wickens, 2000; Taylor, Reinerman-Jones, Szalma, Mouloua, & Hancock, 2013).”
Position: Levels of AGI for Operationalizing Progress on the Path to AGI (2023, neutral): “At levels below “Expert AGI” (e.g., “Emerging AGI,” “Competent AGI,” and all “Narrow” AI categories), risks likely stem more from human actions (e.g., risks of AI mis-use, whether accidental, incidental, or malicious).”
From Here to Autonomy (2017, methodology): “Parasuraman et al. (2000) presented a similar stage of automation taxonomy with the information monitoring factor divided into two levels, information filtering and information integration or inference, and with option generation and action selection combined in their action selection category.”
Collision Warning Timing, Driver Distraction, and Driver Response to Imminent Rear-End Collisions in a High-Fidelity Driving Simulator (2002, background): “Whether drivers view the collision warning system as automation that triggers a response or as automation that redirects attention can have important implications for design (Parasuraman et al., 2000).”
Human-Automation Interaction (2005, background): “Some can be automated to a greater degree and others to a lesser degree (Parasuraman et al., 2000).”
Understanding human management of automation errors (2013, background): “These technologies are designed to support overall system performance, assisting human operators with tasks such as information acquisition and processing, decision-making and action execution (Parasuraman, Sheridan, and Wickens 2000).”
Effects of Mental Model Quality on Collaborative System Performance (2007, background): “Parasuraman et al. (2000) also categorized automation into ten different levels based on the automation’s level of control or human lack of control.”
Highly automated job interviews: Acceptance under the influence of stakes (2019, positive): “In particular, the tool should include all aspects of highly-automated interviews: acquire information, analyze information, select and decide about potential actions, and implement these actions (Hoff & Bashir, 2015; Parasuraman et al., 2000).”
Creating moral buffers in weapon control interface design (2004, background): “” Humans have a tendency to disregard contradictory information in light of a computer-generated recommendation, and this automation bias can cause erroneous decisions, often with high costs [11], [14], [15].”
Automation spectrum, inner / outer compatibility and other potentially useful human factors concepts for assistance and automation (2008, background): “While the approach of Parasuraman et al. (2000) is quite helpful, essential aspects of automation might be efficiently communicated with a one-dimensional spectrum of continuous automation degrees (figure 1).”