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An alliance of humans and machines for machine learning: Hybrid intelligent systems and their design principles
Linnaeus University, Faculty of Technology, Department of Informatics.
Linnaeus University, Faculty of Technology, Department of Informatics.ORCID iD: 0000-0003-4301-478x
Linnaeus University, Faculty of Technology, Department of Informatics.ORCID iD: 0000-0002-4437-8297
2021 (English)In: Technology in society, ISSN 0160-791X, E-ISSN 1879-3274, Vol. 66, article id 101647Article in journal (Refereed) Published
Sustainable development
SDG 9: Build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation
Abstract [en]

With the growing number of applications of artificial intelligence such as autonomous cars or smart industrial equipment, the inaccuracy of utilized machine learning algorithms could lead to catastrophic outcomes. Human-in-the-loop computing combines human and machine intelligence resulting in a hybrid intelligence of complementary strengths. Whereas machines are unbeatable in logic and computation speed, humans are contributing with their creative and dynamic minds. Hybrid intelligent systems are necessary to achieve high accuracy and reliability of machine learning algorithms. In a design science research project with a Swedish manufacturing company, this paper presents an application of human-in-the-loop computing to make operational processes more efficient. While conceptualizing a Smart Power Distribution for electric industrial equipment, this research presents a set of principles to design machine-learning algorithms for hybrid intelligence. From being AI-ready as an organization to clearly focusing on the customer benefits of a hybrid intelligent system, designers need to build and strengthen the trust in the human-AI relationship to make future applications successful and reliable. With the growing trends of technological advancements and incorporation of artificial intelligence in more and more applications, the alliance of humans and machines have become even more crucial.

Place, publisher, year, edition, pages
Elsevier, 2021. Vol. 66, article id 101647
Keywords [en]
Hybrid intelligence, Human-in-the-loop (HITL) computing, Design principles, Design science research, Machine learning, Artificial intelligence
National Category
Information Systems
Research subject
Computer and Information Sciences Computer Science, Information Systems
Identifiers
URN: urn:nbn:se:lnu:diva-105645DOI: 10.1016/j.techsoc.2021.101647ISI: 000687240300009Scopus ID: 2-s2.0-85109353683Local ID: 2021OAI: oai:DiVA.org:lnu-105645DiVA, id: diva2:1576376
Available from: 2021-06-30 Created: 2021-06-30 Last updated: 2021-09-03Bibliographically approved

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Chowdhury, SoumitraIqbal, Sarfraz

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