Fabulating Futures in the Digital Condition

Although machine learning systems have contributed positively to society in some ways, as we see in improved diagnostics, the tendency towards widespread automation has produced unparalleled challenges related to knowledge and power asymmetries, and the long-term sustainability of natural and social environments, not to mention the health of our mental ecologies. More perplexing is the ease with which many people have accepted the appropriation of our intellectual commons by Large Language Models (LLMs), and the false assumptions about consciousness this has propagated, including the idea that General Artificial Intelligence is immanent, if not already here. This obscures the many ways in which the increased omnipresence of ambient technologies – like smart home devices and wearables – have seamlessly integrated surveillance into our everyday lives. In other words, the normalisation of these tools invisibilises surveillance by transforming private spaces into sites of data generation and mining. For example, technologies like Fitbits and smart watches, which are very often linked to mobile health apps, covertly gather continuous, intimate health and other behavioural data like sleep patterns and stress levels, in turn creating risks related to discrimination, increased premiums, and so on.

While much of the work currently done on digital technologies focuses on cybersecurity and AI ethics to address issues like opacity and bias in algorithmic processes, less attention is paid to philosophical problems related to the mechanisation of human thought and its reliance on knowledge extractivism – an ongoing legacy of colonialism. In a recent article, Meredith Whittaker (2023) traces contemporary AI-driven work surveillance techniques to technologies first developed on plantations. Although she cautions the reader not to draw easy equivalences between contemporary labour regimes and the violently enforced racialised labour practices of plantation slavery, she nevertheless argues that the relationship between neoliberal worker surveillance and worker control on plantations is foundational. Relatedly, in her 2015 book, Dark Matters: On the Surveillance of Blackness, Simone Browne argues that identities are not simply mapped by biometric technologies like fingerprints, iris scans, or voice recognition for authentication and security purposes, but that subjectivities in fact emerge from and in opposition to them. What she is pointing at is that these technologies are not neutral but embedded in existing, and often reductive, categorisations – like race, nationality and gender – that render the world more computable, thereby articulating new arrangements of power and knowledge. 

These kinds of processes have detrimental effects on more informal economic sectors and local knowledges, because automation and surveillance disproportionately threaten low-income and indigenous communities. Overcoming existing biases like these does not simply mean incorporating more marginalised perspectives into data sets because, rather than addressing the actual problems associated with prejudice in the real world, this kind of integration lends itself to algorithmic homogenisation. That is, heterogeneous ways of being and seeing are ‘flattened out’ because they are seamlessly merged into standardised and prefabricated digital frameworks that are already overdetermined by Global North paradigms. This has very real consequences for the production of knowledge because this type of retrospective intervention short-circuits opportunities for thinking outside the logic of the algorithm. This is exacerbated by the fact that the speed of technological innovation is far outpacing our ability to theorise their effects. In other words, the very conditions of possibility for thinking have become subjected to the logic of algorithmic reason and extractivism, which not only threatens our livelihoods but our veritable lifeworlds, or collectively produced frameworks of meaning-making for the amelioration of existential dread. 

The fact that algorithms are implicated in processes of worldmaking with and for us does not mean we simply have to accept their encroachment into every aspect of our lives. Instead, we should be interrogating the short- and long-term effects of these calculative processes on our social, mental, and environmental ecologies. If we are to fabulate futures that can support not just life, but thriving, thought as such needs to be shifted outside the logic of digitality. The philosopher Gilles Deleuze, drawing on Friedrich Nietzsche, would say that this requires that we become clinicians of culture, which for him does not simply mean diagnosing the ‘illnesses’ of the past or present, but invoking the untimely, the yet-to-come. This is not a call to think from the ‘ivory towers’ of academic institutions, but to wrest thought from cognitive surrender to AI slop machines and neoliberal extractivism. This is a reorientation towards a practical ethics of care – for the planet, for societies, and for thought, so that we can become capable of prefiguring the futures we want. But this presupposes overcoming what Mark Fisher calls ‘reflexive impotence’ – an apathetic cynicism or collective ‘meh’ that keeps people from acting because they believe change is impossible. Small wonder people opt for ‘Netflix and chill’. Recognising the ways in which thought is constrained by the digital is not easy, but it is also not impossible. What is required is that we be on the lookout for encounters: not with technologies, but with that which will shock thought from its slumber.

Works Cited:

Browne, S. 2015. Dark Matters: On the Surveillance of Blackness. Durham: Duke University Press.

Deleuze, G. 2006. Nietzsche and Philosophy. Translated by H. Tomlinson. New York: Columbia University Press.

Fisher, M. 2009. Capitalist Realism: Is there No Alternative? London: Zero Books.

Whittaker, M. 2023. Supa Dupa Skies (Move Slow and Heal Things). Logic(s) [Online] Available: https://logicmag.io/supa-dupa-skies/origin-stories-plantations-computers-and-industrial-control/ [Accessed 17.05.2026].