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.
Hildebrandt et al. (Thu,) studied this question.