While AI-driven automation can increase the performance and safety of systems, humans should not be replaced in safety-critical systems but should be integrated to collaborate and mitigate each other’s limitations. The current trend in Industry 5.0 is towards human-centric collaborative paradigms, with an emphasis on collaborative intelligence (CI) or Hybrid Intelligent Systems. In this survey, we search and review recent work that employs AI methods for collaborative intelligence applications, specifically those that focus on safety and safety-critical industries. We aim to contribute to the research landscape and industry by compiling and analyzing a range of scenarios where AI can be used to achieve more efficient human–machine interactions, improved collaboration, coordination, and safety. We define a domain-focused taxonomy to categorize the diverse CI solutions, based on the type of collaborative interaction between intelligent systems and humans, the AI paradigm used and the domain of the AI problem, while highlighting safety issues. We investigate 91 articles on CI research published between 2014 and 2023, providing insights into the trends, gaps, and techniques used, to guide recommendations for future research opportunities in the fast developing collaborative intelligence field.

Collaborative Intelligence for Safety-Critical Industries: A Literature Review / I.F. Ramos, G. Gianini, M.C. Leva, E. Damiani. - In: INFORMATION. - ISSN 2078-2489. - 15:11(2024 Nov 12), pp. 728.1-728.42. [10.3390/info15110728]

Collaborative Intelligence for Safety-Critical Industries: A Literature Review

G. Gianini
Secondo
;
E. Damiani
Ultimo
2024

Abstract

While AI-driven automation can increase the performance and safety of systems, humans should not be replaced in safety-critical systems but should be integrated to collaborate and mitigate each other’s limitations. The current trend in Industry 5.0 is towards human-centric collaborative paradigms, with an emphasis on collaborative intelligence (CI) or Hybrid Intelligent Systems. In this survey, we search and review recent work that employs AI methods for collaborative intelligence applications, specifically those that focus on safety and safety-critical industries. We aim to contribute to the research landscape and industry by compiling and analyzing a range of scenarios where AI can be used to achieve more efficient human–machine interactions, improved collaboration, coordination, and safety. We define a domain-focused taxonomy to categorize the diverse CI solutions, based on the type of collaborative interaction between intelligent systems and humans, the AI paradigm used and the domain of the AI problem, while highlighting safety issues. We investigate 91 articles on CI research published between 2014 and 2023, providing insights into the trends, gaps, and techniques used, to guide recommendations for future research opportunities in the fast developing collaborative intelligence field.
collaborative intelligence; AI; safety-critical industries;
Settore INFO-01/A - Informatica
   Collaborative Intelligence for Safety Critical systems (CISC)
   CISC
   EUROPEAN COMMISSION
   H2020
   955901

   Sovereign Edge-Hub: un’architettura cloud-edge per la sovranità digitale nelle scienze della vita - SOV-EDGE-HUB
   SOV-EDGE-HUB
   UNIVERSITA' DEGLI STUDI DI MILANO
12-nov-2024
https://www.mdpi.com/2078-2489/15/11/728
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1118636
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