ORCID

0000-0002-3913-6162 (Johnson)

Document Type

Conference Paper

Publication Date

2025

DOI

10.54941/ahfe1006995

Publication Title

Human Factors in Design, Engineering, and Computing

Volume

199

Pages

1841-1851

Conference Name

Applied Human Factors and Ergonomics International, July 26-30, 2025, Orlando, FL, USA

Abstract

Adaptive automation enables dynamic reallocation of functions between people and autonomous agents to improve performance in complex work. This paper presents a meta-analysis of experimental and quasi-experimental studies (2000-2025) on joint cognitive systems in industrially relevant contexts, quantifying effects on task performance, safety/failure management, workload, trust, and learning. Across studies, adaptive automation reliably reduces operator workload and shows moderate gains in task performance and safety, with healthier trust dynamics when adaptations are triggered by human-state or event cues, made transparent to the user, and remain rapidly overridable. Risks emerge when performance-triggered switching is opaque or poorly timed, which can erode trust, induce cognitive tunneling, or hinder skill retention. The findings translate into actionable guidance for human-factors researchers, system designers, and operations leaders seeking industry 5.0 outcomes: human-centric, resilient, and sustainable work systems in which digital teammates help people do their best work.

Rights

© 2025 The Author.

"The author(s) of papers published in the AHFE Open Access Proceedings will retain full copyrights as specified by the provisions of the Creative Commons Attribution 4.0 International (CC BY 4.0) License."

Original Publication Citation

Johnson, J. M. (2025). Teaming with technology: Adaptive automation in joint cognitive systems for Industry 5.0. In T. Ahram, W. Karwowski, & J. Kalra (Eds.) Applied Human Factors and Ergonomics International (pp.1841-1851). AHFE International.  https://doi.org/10.54941/ahfe1006995

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