Abstract
John Preston’s monograph Artificial Intelligence in the Capitalist University: Academic Labour, Commodification, and Value offers a Marxian value-critical perspective on the manifestation of Artificial Intelligence (AI) within Higher Education (HE). The book presents a comprehensive analysis of how AI operates within the broader framework of capitalism, highlighting its role in shaping power dynamics, reinforcing the capitalist value structure, and uncovering hidden labor alienation and class struggle within HE.
The book is structured into seven chapters that progressively explore different aspects of AI in the capitalist university. Chapter 1 serves as an introduction, providing an overview of the subsequent sections. It establishes the importance of employing a Marxist theoretical framework to understand the relationship between AI and capitalism. Preston asserts that AI within the capitalist university is an integral part of the overall capitalist system, setting the tone for the book’s critique of capitalism itself. Chapter 2 argues from a Marxist perspective that all universities are inherently capitalist, as they operate within capitalist social forms and relations. It challenges opposing theories like ‘Object Orientated Ontology (OOO)’ (p. 35) and advocates for an approach rooted in the class struggle as the basis for analyzing the capitalist university.
In Chapter 3, the concept of HE as a producer of commodity-like outputs exchanged for monetary value is delineated. It explores how AI accelerates labor quantification and optimization, leading to increased surplus value and the absorption of more labor. The substitution of AI for collective academic labor reinforces subordination to capitalism, exploiting academic workers and facilitating capital accumulation. The chapter also discusses the potential transformation of AI into a new labor subject if humans were to disappear, highlighting the challenges and alternatives within the capitalist university. Chapter 4 introduces the concept of Pixarfication, which refers to the attribution of anthropomorphic qualities and perceptual abilities to commodities, facilitating their exchange, and value realization. It examines how this practice distorts the essence of labor and commodifies various entities within the academic sector, subordinating intrinsic use value to exchange value, and resulting in the proletarianization and exploitation of the academic sector.
Chapter 5 focuses on the heightened exploitation of academic labor within capitalist universities during the pandemic, as AI and digital technologies are embraced as the ‘New Normal’. It discusses the acceleration of exploitation, the prevalence of abstract time over concrete time, and the intensification of work within the virtual university. The chapter challenges the notion that the ‘New Normal’ represents a profound shift, emphasizing the continuation of capitalist dynamics. Chapter 6 engages in a debate with the perspectives of Nick Bostrom and Nick Land, critiquing their inability to transcend the capitalist framework and fully grasp the nature of capitalism. The chapter advocates for the application of Marxist critical theory to analyze AI, rather than simplifying it as a mere technological progress. Chapter 7 scrutinizes the concept of Full Automation Luxury Communism (FALC), highlighting its limitations in comprehending Marxist theory and conducting critical analysis. The author argues that Marxist critical theory should guide the examination of the relationship between AI and capitalism, cautioning against relying solely on a single technological solution. The book concludes by asserting that communism, as the ultimate negation of capitalism, offers the only escape.
The book has several notable strengths that contribute to its significance and value. First, it demonstrates a profound theoretical foundation, displaying a deep understanding of Marxian theory and its application to the analysis of HE and AI within contemporary capitalist society. The author’s command of the subject matter is evident throughout the book, allowing readers to gain a comprehensive understanding of the complex relationship between AI and capitalism. Second, the book exhibits a rigorous academic demeanor and keen insight. Preston’s arguments are well-reasoned and supported by a range of scholarly references and evidence. The author’s ability to critically analyze and evaluate various perspectives adds depth and nuance to the discussion, elevating the book’s scholarly contribution. Third, the book’s structure is organized with precision and logical coherence. Each chapter builds upon the previous one, leading readers through a carefully constructed argument. The author’s clear and coherent writing style facilitates understanding and enables readers to follow the progression of ideas effortlessly. Furthermore, the author skillfully incorporates relevant perspectives for comparison or corroboration, enriching the theoretical analysis. By integrating real-world events and examples, Preston effectively grounds abstract concepts in concrete contexts, making the content more accessible and relatable to readers. Nonetheless, one minor limitation is the lack of empirical research specifically focused on universities, as the author relies on research centered on ‘digital manufacturing’. Collaboration with universities would have provided more comprehensive data and a deeper understanding of the complexities within HE.
Overall, the book Artificial Intelligence in the Capitalist University offers a comprehensive framework for comprehending the role and function of AI in today’s capitalist society. It stands out for the author’s theoretical expertise, rigorous analysis, and logical structure. By presenting a distinctive and innovative perspective, the book makes a significant contribution to the academic discussion surrounding HE within a capitalist framework. It thoroughly explores the utilization and effects of AI in the interdisciplinary intersection of higher education studies, artificial intelligence research, social theory, and the ethics of technology, encompassing areas like labor, teaching, research, and value creation. The book is suitable for scholars, researchers, education practitioners, students, and readers interested in the social and technological implications of AI. However, it is important to note that the book’s content is specialized, requiring some prior knowledge in the relevant fields for a better understanding.