AI Could Help Factories Keep Workers at the Center, New Research Suggests
European researchers propose using artificial intelligence to support human-centered manufacturing by enhancing worker awareness and on-the-job learning. The findings could reshape how factories design AI systems—focusing on augmenting human capability rather than replacing workers, a shift with major implications for workforce strategy and productivity.
Originaltitel: An interdisciplinary perspective on generative AI as support for human-centricity in Industry 5.0
**Generativ AI stödjer operatörskunskap i framtidens produktionsmiljöer** Industri 5.0-visionens fokus på människocentrerad produktion kräver att maskiner och system förstår hur personal faktiskt arbetar. Högskolan i Halmstad och RISE analyserade hur artificiell intelligens kan stödja detta genom två begrepp: distribuerad situationmedvetenhet (DSA) och situerad inlärning (SL). Forskarna intervjuade operatörer och analyserade deras arbetsprocesser. Tre huvudsakliga rön framkom: DSA och SL kompletterar varandra för att förstå operatörsarbete. Att kombinera teoretiska perspektiv — både faktorbaserade och processuella — ger djupare insikt. Operatörer lär sig kontinuerligt under sitt arbete. För inköpschefer och regulatoriska specialister betyder detta att nya produktionssystem måste designas för att fånga och integrera denna naturliga lärprocessen. Implementering kräver iterativ metodutveckling och bredare syn på hur kunskap skapas på arbetsplatsen.
<p>This article addresses an interdisciplinary approach to human centricity in Industry 5.0. Industry 5.0 is the vision outlined by the European commission to place humans at the centre of production. The interdisciplinary research focuses on distributed situation awareness (DSA) and situated learning (SL). Contribution in the article is a set of lessons learned from interdisciplinary research on industry 5.0 and the research approach has been stimulated recall interviews followed by a process analysis. Three lessons learned were identified: 1) DSA and SL not only complement each other in the understanding of operators it also enriches and expands our understanding of interdisciplinary research. 2) Combining theories with a factor perspective (no temporal dimension) and a process perspective (with a temporal dimension) enhances a deeper understanding of operators and 3) Learning is always present during operators’ work. Hence it is important to apply a broad perspective on learning, such as combining cognition and socio-cultural learning theories. Future work will study the implications of iterative implementation of DSA and SL in industry. © 2025 The Authors.</p>