Assimilierende versus komplementäre Adaptivität

Artificial intelligence in the practice of work

“…If we consider connectionist AI as an empirical object of research on work, we can see that it is a technology that can be used and interpreted in very different ways in different fields and contexts (Brynjolfsson & McAfee, 2014;Ford, 2016). Broadly speaking, discussions on AI in the sociology of work focus on how it can replace human work (substitution), complement human work (complementarity) or empower working subjects (augmentation) (Huchler, 2019(Huchler, , 2022. This raises further questions concerning possible uses of AI in the world of work: 4 does AI accelerate automation by itself, or does it act as a tool?…”

“…Still, AI is not only surrounded by work, as just argued but must also be embedded in the existing socio-technical context in order to become productive. Failure to consider these limits has AI-specific social consequences (Huchler, 2019;Heinlein & Huchler, 2023). These consequences include intensified work and an increase in contradictions, pressure and friction between formal and informal but necessary work.…”

“…Consequently, some of the handling of complexity and uncertainty is transferred into the AI systems themselves -beyond management and work process design, but also beyond 'if-then' programming towards a more goaloriented 'in order to' . The situational adaptivity associated with this can be described as 'assimilating adaptivity' (Huchler, 2019), which differs from a 'complementary adaptivity' (ibid.) in that it is based on translating contingency in the system environment into the inherent logic of the AI system (that is, data that can be gathered and processed by AI).…”

“…A typical effect of the quest for technological controllability of complexity and uncertainty is the standardisation of the social environment or practice (for example, the Taylorisation of work) (Böhle & Busch, 2012). Yet making the practical environment compatible, adaptable and controllable for formal systems can be at the expense of diversity, quality and individual freedom (Huchler, 2019). This also applies beyond the context of paid work: for example, autonomous road transport can more easily be implemented in a highly regulated environment.…”

“…AI is thus always accompanied by an adaptation of the environment to the processing logic of the AI systems. However, the quality and quantity as well as the social implications of these mutual adaptivities are crucial (Huchler, 2019).…”