Embracing Levin’s Legacy: Advancing Socio-Technical Learning and Development in Human-Robot Team Design Through STS Approaches

Karyne Ang (), Shankar Sankaran, Dikai Liu and Jeffrey Scales
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Karyne Ang: University of Technology Sydney
Shankar Sankaran: University of Technology Sydney
Dikai Liu: University of Technology Sydney
Jeffrey Scales: University of Technology Sydney

Systemic Practice and Action Research, 2024, vol. 37, issue 6, No 5, 678 pages

Abstract: Abstract This paper investigates the synergy between Levin’s theories on technology transfer as a socio-technical learning and developmental process (TLD process), and what we learnt about socio-technical systems (STS) theories in a case study developing human robot solutions for the construction sector. Levin’s extensive work highlights the significance of technology transfer as a means for organizational development. His TLD process emphasizes the intricate interplay between technology, organizational change, and learning and highlights the importance of incorporating cultural knowledge and skills into the technological transfer process. Contemporary STS views developed through our own work are introduced to complement and extend Levin’s theories by providing a systemic lens to understand the broader socio-technical context in which technology transfer occurs. To illustrate the synergies and potential challenges from Levin’s theories of technology transfer with contemporary STS concepts, we use a qualitative study of a unique case about the design and development of human-robot teams (HRTs) for construction tasks. Our findings reveal that while Levin’s theories provide a valuable foundation for understanding technology transfer and organizational change, contemporary socio-technical systems face unique challenges in the context of AI-driven human-robot teams, where intelligent robots also contribute to the socio-technical learning process. Moreover, the rapidly evolving nature of technology and innovations could exponentially impact on multidisciplinary design teams, stakeholder participation and inter-organizational dynamics. The discussions suggest an extension of co-generative learning to incorporate ‘collaborative intelligence’ between human-robot teams enabled by artificial intelligence (AI). Consequently, we suggest that Levin’s theories of technology transfer, developed before the rapid application of AI, may not have fully considered further social challenges caused by the introduction of autonomous systems such as AI-driven HRT systems. We extend Levin’s important work by suggesting that addressing such challenges requires ongoing dialogue and collaboration among researchers, practitioners, and policymakers with different disciplinary backgrounds to develop robust and reliable socio-technical systems frameworks to navigate the complexities of robotics and AI in today’s rapidly evolving technological landscape.

Keywords: Socio-technical systems; Technology transfer; Human-robot teams; Multidisciplinary teams; Design and development (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11213-024-09705-y

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