Paper Short Abstract:

This paper examines the integration of artificial intelligence (AI) into academic labour (research, teaching, and service), addressing the challenges within the higher education sector subsumed under capital.

Paper Abstract:

This paper examines the integration of artificial intelligence (AI) into academic labour, addressing the challenges within the higher education sector subsumed under capital. Under the claim of enhanced efficiency, academic institutions increasingly deploy machine learning and natural language processing-generated AI technologies to streamline recruitment, admission, and performance evaluation processes, as well as to customize teaching materials and assessments. AI's (costly) 'purchase' comes both as a tool for administrative convenience and an instrument of surveillance and standardization, but as other recently embraced new technologies, it introduces serious concerns regarding discipline, control, and transformations of academic labour. The potential for AI to infringe on academic freedom, intellectual property, and worker rights through intensified monitoring and profiling activities reflecting and reinforcing intersectional inequalities are all critical concern. Yet, employing a materialist lens, the paper shows venues overlooked by most emergent academic literature on the subject: the enormous surplus extraction and value capture in higher education through formal and real subsumption of academic labor into segmented tasks that can be easily automated and outsourced, casualised, deprofessionalised and disembodied. At the same time, I show how traditional hierarchies, rituals, temporal and spatial dimensions of scholarly work make it particularly susceptible to such changes. Here, I also outline where anthropology stands in comparison/contrast with other disciplines. I thus outline potential venues for research and resistance, taking into account new vantage points of capitalist capture and their strategic choke points.