Algorithmic meaning-making

The operation was a success, but the patient died.

[excerpt] We live in a world increasingly shaped by algorithmic infrastructures and cognitive machines that reflect the hegemony of the left hemisphere: the mode of thinking that privileges linearity, control, prediction and efficiency. In contrast, the right hemisphere attends to context, relationships, and the whole. This neurological metaphor reveals a cultural split. The rhetoric of the left hemisphere, seen in ‘strong AI’, the cult of technology and computational capitalism, has given rise to a civilization of unprecedented alienation. It commodifies human abilities, flattening complexity into data-driven value systems. Under the banner of progress, the world has optimized itself into disconnection. Its procedures reduce human experience to mechanistic processes. The cult of technology privileges operation over understanding, reducing the human to “the effective (practical) reduction of the human being to the best dimension that can be best handled technically” (Lefevbre, apud Fuchs, 2022, p.122). The rise of computational capitalism commodifies cognition itself. Labour is fragmented into algorithmically managed micro-tasks, and human faculties are mined as data for predictive systems. Granting AI autonomy to reduce uncertainty simultaneously endangers agency, accountability and the very qualities ( i.e. ethics, imagination, dignity ) that technology was meant to augment. Under the guise of neutrality, algorithms optimise relentlessly for shareholder value, eroding civic life, education and the capacity to distinguish truth from manipulation.

These infrastructures now function not merely as tools but as ideological mechanisms of power, embedding control into the unnoticed routines of everyday life. Consequently, human reasoning becomes dependent on externalised technical memory. What was once the interior dialogue of conscience and imagination is now co-authored by code. Concepts such as instrumentalization and infrasomatization (Berry, 2019) , “humans-as-a-service” (Bezos, 2017), and Žižek’s “wired brain” (2020) reveal a decentralized yet tightly monitored regime of computation, one that redefines autonomy as surveillance. Even the phrase “artificial intelligence” reinforces a cognitive trap, suggesting intelligence where there is none (Nardelli, 2024, p. 103). We anthropomorphize machines, seduced by science-fiction mythologies that disguise how we are interacting not with minds but with mirrors (Weizenbaum, 1976). For the first time in cultural history, humanity is producing technological artefacts that inhabit both the symbolic and physical spaces of social life. These “social others” blur the boundary between human and machine, demanding philosophical and ethical scrutiny. With generative AI, we have shifted from interacting through technologies to interacting with them, introducing a new symbolic component into the domain of algorithmic governance. These systems influence knowledge production, agency and collective life through their semantic and epistemic authority. As code evolves from a neutral instrument into a socio-technical system of power, it organises subjectivity, culture and behaviour under the illusion of objectivity. Digital platforms exploit discourse through framing effects, echo chambers and algorithmic curation, concentrating communicative power while generating new forms of exclusion and surveillance. Under the guise of neutrality, these systems optimize relentlessly for shareholder value, eroding civic life, education, and the capacity to discern truth from manipulation. Extractive metaphors such as “data is the new oil” (Humby, 2006) reinforce this cognitive reductionism, framing knowledge as a resource rather than a right. As David Berry (2019) observed, we now inhabit a “horizon of interpretability” shaped by data capture and algorithmic infrastructures hidden within the black box of computational capitalism (pp. 43–45). There is an urgent need to challenge the myth of algorithmic neutrality to avoid reducing human affairs and their complex cultural and social realities into data-deterministic systems. This trajectory reveals a paradox: granting AI autonomy to reduce uncertainty simultaneously risks the loss of agency, accountability, and essential human qualities such as ethics, imagination, and dignity, the very values technology was meant to enhance. This evolution calls for a new form of critical algorithm theory, one that examines how algorithms structure knowledge, power, and inequality by shaping visibility and meaning. Without such a framework, algorithmic infrastructures risk becoming invisible systems of domination. To advance this paradigm is to resist reduction, to reclaim technology for collective sense-making and democratic imagination. This is the essence of digital humanism: to restore balance by placing wisdom, dignity, and democratic freedom (the patient) at the centre of technological progress (the operation).

Berry, D. M. (2019). Against infrasomatization: Towards a critical theory of algorithms. In D. Bigo, E. Isin, & E. Ruppert (Eds.), Data politics: Worlds, subjects, rights (1st ed.). Routledge.

Fuchs, C. (2022). Digital humanism: A philosophy for 21st century digital society. Emerald Publishing Limited.

Humby, C. (2006, November). Data is the new oil [Conference presentation]. Association of National Advertisers Conference, London, United Kingdom.

Lefebvre, H. (1966). Le langage et la société. Gallimard.

¹McGilchrist, I. (2019). The Master and His Emissary: The Divided Brain and the Making of the Western World. Yale University Press.

Nardelli, E. (2024). No digital citizens without digital humanism. In H. Werthner, C. Ghezzi, J. Kramer, J. Nida-Rümelin, B. Nuseibeh, E. Prem, & A. Stanger (Eds.), Introduction to digital humanism: A textbook (pp. 99–114). Springer.

Weizenbaum, J. (1976). Computer Power and Human Reason: From Judgment to Calculation. W.H. Freeman and Company.

Žižek, Slavoj (2020). Hegel in a wired brain. New York: Bloomsbury Academic.