Augmented Cognition Meets AI: Enhancing Human Performance with Real-Time, Adaptive, and Trustworthy Intelligence

This panel explores how advancements in artificial intelligence (AI) are transforming the field of augmented cognition (AC). Traditionally focused on adapting system behavior based on user state, augmented cognition is now expanding into new territory with AI technologies that can sense, interpret, and respond in real time. Emerging AI (e.g., large language models, multimodal machine learning, and generative agents) enables new modes of measurement, prediction, and interaction for AI-based augmented cognition. Panelists will highlight how AC systems differ from earlier automation approaches, offering examples from diverse application domains. Use cases include AI copilots that monitor driver fatigue and distraction, adaptive digital teammates that guide workers through complex tasks, and cognitive assistants that support rapid decision- making in high-pressure environments. The conversation will address key design considerations such as the level of human involvement, how to calibrate interaction, and what AI capabilities are still needed. They will also examine critical implementation challenges, including data privacy, cybersecurity, user trust, and ethical concerns. As AI increasingly acts as a synthetic collaborator, the panel will consider how augmented cognition is defined and applied. They will identify research gaps, propose future directions, and explore how human-AI systems can enhance safety, performance, and decision-making across complex domains.

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Publication Details

Journal
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Published
2025-08-28
DOI
https://doi.org/10.1177/10711813251367751
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.00

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article

Augmented Cognition Meets AI: Enhancing Human Performance with Real-Time, Adaptive, and Trustworthy Intelligence

Xiaoyun Yin, Michael Hildebrandt, Heejin Jeong, Shuchisnigdha Deb et al.
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Human-Automation Interaction and Safety
article

Augmented Cognition Meets AI: Enhancing Human Performance with Real-Time, Adaptive, and Trustworthy Intelligence

Xiaoyun Yin, Michael Hildebrandt, Heejin Jeong, Shuchisnigdha Deb, Jackie Cha
article en

Abstract

This panel explores how advancements in artificial intelligence (AI) are transforming the field of augmented cognition (AC). Traditionally focused on adapting system behavior based on user state, augmented cognition is now expanding into new territory with AI technologies that can sense, interpret, and respond in real time. Emerging AI (e.g., large language models, multimodal machine learning, and generative agents) enables new modes of measurement, prediction, and interaction for AI-based augmented cognition. Panelists will highlight how AC systems differ from earlier automation approaches, offering examples from diverse application domains. Use cases include AI copilots that monitor driver fatigue and distraction, adaptive digital teammates that guide workers through complex tasks, and cognitive assistants that support rapid decision- making in high-pressure environments. The conversation will address key design considerations such as the level of human involvement, how to calibrate interaction, and what AI capabilities are still needed. They will also examine critical implementation challenges, including data privacy, cybersecurity, user trust, and ethical concerns. As AI increasingly acts as a synthetic collaborator, the panel will consider how augmented cognition is defined and applied. They will identify research gaps, propose future directions, and explore how human-AI systems can enhance safety, performance, and decision-making across complex domains.

Proceedings of the Human Factors and Ergonomics Society Annual MeetingVol. 69(1)
The University of Texas at Arlington (US), Institute for Energy Technology (NO), Arizona State University (US), Clemson University (US)
Division of Information and Intelligent Systems
Openalex Percentile: Top 74%
Human-Automation Interaction and Safety
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