Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/307520 
Year of Publication: 
2021
Citation: 
[Journal:] Journal of Organization Design [ISSN:] 2245-408X [Volume:] 10 [Issue:] 2 [Year:] 2021 [Pages:] 75-81
Publisher: 
Springer, Cham
Abstract: 
The promise of collaboration between humans and algorithms in producing good decisions is stimulating much experimentation. Drawing on research in organization design can help us to approach this experimentation systematically. I propose typologies for considering different forms of division of labor between human and algorithm as well as the learning configurations they are arranged in, as basic building blocks for this endeavor.
Subjects: 
AI
Organization design
Machine learning
Learning configurations
Division of labor
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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