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1. Introduction
Artificial intelligence (AI) regained high attention during the past years, as it can serve as a technology for not only enhancing learning processes but also changing learning cultures and interactions (Gadanidis, 2017). The cultural component results from the interrelatedness between the concept of knowing and the use of technology. In this regard, AI has the potential to open up for new ways of collaborative knowledge creation (Fischer et al., 2020). The use of AI is obviously more than the integration of a new technological component but unfolds socio-technical system dynamics. There is a need to better understand these dynamics, to explore the collaboration potential but also the risks and unintended consequences that might result from integrating AI in the workplace.
The exploration of socio-technical system dynamics can be related to macro level effects, to workplace issues on meso level and even be explored with a subject-oriented approach on micro level. This paper gives emphasis to the meso level of the workplace. It refers to individual and organizational learning theory to evaluate whether AI can unfold an augmentation potential and support individual abilities instead of substituting or duplicating them. It also searches for the prerequisites to gear into this direction. The core question is how to combine AI and individual intelligence for creating a system with distributed intelligence (Cobb, 1998) and where there are limitations. The course of argumentation is based on individual and organizational learning theory as well as competency research which are related to the potential of machine learning methods.
The paper addresses the audience with interest in the use of AI in education. However, the focus is not on dynamics and change issues in educational institutions but on learning and development in the workplace as place and space for competence development. This unit of analysis is thematically related to the overall sociological and economic discourse reflecting on the effects of new technologies on labor and workforce. The research on automation and substitution of human labor due to new technologies and smart machines has a long tradition (Blau et al., 1976; Zuboff, 1988). It has recently been extended to the effects of AI (Ekbia and Nardi, 2017; Susskind, 2020). Generally speaking more pessimistic and more optimistic scenarios coexist in the...