English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper proposes the innovative concept of "human factors science" tocharacterize engineering psychology, human factors engineering, human-computerinteraction, and other similar fields. Although the perspectives in thesefields differ, they share a common approach: "human-centered design." In the AIera, the human-machine relationship presents a trans-era evolution to "human-AIteaming." The change has raised challenges for human factors science,compelling us to re-examine current research paradigms and agendas. Based onour previous work, this paper proposes three research paradigms: (1) human-AIjoint cognitive systems: this regards an intelligent agent as a cognitive agentwith a certain level of cognitive capabilities. A human-AI system can becharacterized as a joint cognitive system in which humans and intelligentagents work as teammates for collaboration; (2) human-AI joint cognitiveecosystems: an intelligent ecosystem with multiple human-AI systems can berepresented as a human-AI joint cognitive ecosystem. The overall performance ofthe ecosystem depends on optima collaboration and design across the multiplehuman-AI systems; (3) intelligent sociotechnical systems (iSTS): human-AIsystems are design, developed, and deployed in an iSTS environment. Thesuccessful design, development, and deployment of a human-AI system within aniSTS environment depends on the synergistic optimization between thesubsystems. This paper looks forward to the future research agenda of humanfactors science from three aspects: human-AI interaction, intelligenthuman-machine interface, and human-AI teaming. Analyses show that the three newresearch paradigms will benefit future research in human factors science. Webelieve the proposed research paradigms and the future research agenda willmutually promote each other, further advancing human factors science in the AIera.

New research paradigms and agenda of human factors science in the intelligence era