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Automation and Its Effects

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Reduced Active Engagement

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Possible deskilling and loss of situational awareness

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Human-Automation Trust

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Need to establish appropriate levels of trust to ensure effective use

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Ironies of Automation

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More advanced systems can fail in more complex ways, requiring more skilled intervention

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Vigilance and Attention

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Automated systems can lead to lower levels of vigilance and attention among operators

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Out-of-the-Loop Familiarity

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Operators may lose the ability to manually perform tasks when automation fails

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Automation Complacency

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Tendency to over-rely on automation and not detect automation failures

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System Transparency

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Automation should provide feedback that is easily interpretable by human operators

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Error Detection and Recovery

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Automation can make error detection and recovery more challenging for operators

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Ergonomic Design

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Automation interfaces should be designed considering human physical limitations

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Cognitive Workload

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Properly designed automation should balance and not overload human cognitive workload

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Operator Training and Knowledge

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Continued training is necessary to maintain operator expertise in automated environments

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Job Satisfaction

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Automation can affect job satisfaction through changes in task nature and operator roles

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Mental Models

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Operators must develop accurate mental models of the automated system to use it effectively

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Shared Situational Awareness

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Automation should support situational awareness for all team members

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Workload Distribution

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Automation changes the distribution of workload among team members

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Liability and Ethics

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Determining responsibility for actions taken by automated systems can be complex

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Impact on Skill Development

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Automated systems can influence the development and maintenance of operator skills

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Adaptation to Changing Conditions

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Automation must be designed to adapt to dynamic operating environments

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Feedback Mechanisms

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Effective design of feedback from automation is essential for human operator performance

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Autonomous Decision Making

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Increased autonomy in systems challenges the operator's role in decision-making

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