TL;DR
It is argued that contemporary artificial intelligence is best understood as a symptom and accelerator of modern nihilism rather than as a neutral instrument or proto-subject because it allows values to persist as calculable effects rather than contested commitments, thereby insulating human agents from the burden of judgment.
Artificial intelligence is commonly portrayed as a technical innovation that inaugurates a new social epoch defined by efficiency, automation, and rational governance. This article advances a dialectical anthropological critique of such narratives by situating artificial intelligence within the historical dynamics of capitalism, colonial power, and struggles over labor and knowledge. Conceptualizing artificial intelligence as a social relation rather than a neutral technology, the article draws on Marxian political economy, Fanonian analyses of colonial domination, Gramscian theories of hegemony, Polanyian insights about market disembedding, and Comaroffian critiques of contemporary capitalism. It contends that AI, through labour, epistemology, or governance, is the new hyper-driven moment of commodification and cycle of global inequalities. Meanwhile, AI creates inconsistencies that break down established value and authority regimes, laying the ground for contestation and possible other trajectories. The paper outlines new directions for a critical anthropology of AI that foregrounds historical materiality and contradictions while committing the field to decolonial epistemologies and transformative praxis.
Contemporary AI systems are increasingly designed to reduce uncertainty, ambiguity, and cognitive burden. This article argues that such systems do not merely expand human capacities but progressively externalize forms of judgment and existential burden that Christian traditions have historically understood as necessary conditions for the cultivation of moral agency. Drawing on the theological anthropologies of Augustine, Søren Kierkegaard, and Dietrich Bonhoeffer, the article develops a theological-anthropological critique of what it terms optimization culture: the normative logic through which the reduction of friction and existential difficulty becomes a dominant telos of technological design. Contemporary articulations of this logic are examined through the work of Jacques Ellul, Byung-Chul Han, Peter Thiel, Balaji Srinivasan, and William Davies. The article argues that AI systems shaped by this logic risk progressively externalizing the practices of disciplined attention, existential responsibility, and costly judgment through which mature moral agency has historically been cultivated. In response, it proposes a formative anthropology of technology as a framework for evaluating AI not only according to functional criteria such as safety or efficiency, but according to the kinds of human beings such systems actively help to form.
This introduction argues that anthropology requires a new conceptual framework for understanding the contemporary social life of artificial intelligence (AI). We propose "the magic of AI" as an analytical concept that shifts attention from AI's technical capacities to the beliefs, uncertainties, and sociotechnical imaginaries through which it acquires authority and efficacy. Revisiting anthropological theories of magic, particularly the work of Ernesto De Martino, Bruce Kapferer, and Francesco Della Costa, we argue that AI's apparent autonomy functions less as a property of the technology itself than as a collectively sustained form of belief. These beliefs naturalize AI's purported inevitability, mobilize political and economic investments, and obscure the human labour, infrastructures, and relations of power through which AI is continually produced. Rather than employing magic as a metaphor, we develop it as a theoretical lens for analysing how opacity, trust, and anticipation generate material sociopolitical effects. In doing so, this introduction offers a conceptual framework for understanding AI as a contingent sociotechnical formation whose power rests as much in collective imagination as in computation itself, while introducing the contributions that develop this argument ethnographically across diverse settings.
The rise of artificial intelligence has revived a fundamentally Cartesian question: what conditions must hold for something to count as genuinely thinking? This paper examines the relationship between cognitive delegation and the Cartesian cogito, arguing that contemporary AI systems challenge not the logical validity of the cogito itself, but its cultural and epistemic centrality. Drawing on a methodological distinction between functional, Cartesian, and agential forms of thinking, the paper develops what is termed the "Cartesian paradox": while humans increasingly delegate judgment and reasoning to AI without necessarily ceasing to exist, machines increasingly reproduce the external markers of intelligence without thereby becoming res cogitantes. The analysis shows that the cogito guarantees certainty of existence through first-person self-presence, but does not imply that the suspension of reflective thought entails ontological annihilation. At the same time, the paper argues that AI systems, despite their growing functional sophistication, remain forms of res extensa insofar as they lack subjective self-awareness and agential self-relation. The conclusion is that the real danger posed by AI is not the replacement of human beings by conscious machines, but the progressive reduction of thinking to operational performance, externalized computation, and algorithmic delegation.
This article introduces the concept of “alienated intelligence” to critically examine contemporary cultural perceptions of artificial intelligence (AI). Drawing on Ludwig Feuerbach’s theory of projection and alienation, it argues that certain visions of AI function as cultural projections of human cognitive capacities that become externalized, idealized, and reified in technological systems. The analysis situates this claim within a broader philosophical framework, engaging Socrates’ notion of wisdom as awareness of ignorance, Dilthey’s account of embodied and integrated cognition, and Damasio’s critique of the Cartesian separation of reason and emotion. Against reductive computational models of mind, the article emphasizes that human cognition is not merely calculative but structurally unified, affective, and contextually embedded. It further argues that the outsourcing of cognitive activities to AI risks not only diminishing retained knowledge but also narrowing our awareness of what we do not know. Finally, the article examines the anthropomorphization and mystification of algorithmic systems as expressions of a broader cultural tendency to mythologize opaque technologies.