Knowledge resides in our stomachs, spines and skin. It lies dormant; subdued by computational noise. Within each of us is a lifetime of sensory memories that communicate to us through our nervous system; stitched together in a delicate web that binds our bones, blood and flesh to the external world. This is embodied knowledge. Overreliance on digital technologies silences these neural messages. The exploitation of capitalism’s social and financial side effects (ie. time poor, fatigue, etc.) has led to the integration of Large Language Models (LLMs) like ChatGPT into many people’s daily lives. Recent studies have shown that a major risk for overuse of these technologies leads to cognitive atrophy, due to the closure of the gap between asking a question and receiving the answer.[1] The in–between steps are where we learn to think critically and creatively, problem solve and contextualise answers to questions. These technologies will continue to exacerbate the disconnect from our bodies and the bodies around us through the reduction of important friction.
Technosolutionism, the idea that all human problems can be seamlessly solved through digital tools, seems an organic response to the psychological struggles of daily life. This, along with an exhausted working class, is a function of the capitalist system in which profit and hyperindividualism are incentivised. To earn money is to survive and so it is both the exhaustion and cortisol that drives fingers to screens that spew it back out as dopamine and a job well done.
Decades of research into the world’s largest tech corporations — most of which have their own LLM chatbot — show that these companies make decisions that prioritise profit over worker and consumer wellbeing.[2] To train their AIs they contract third party data labellers in countries with weak legal protections and cheap labour. These contractors are subjected to unethical working standards, algorithmic surveillance and wages as low $2 per hour.[3] Many of them are forced to categorise graphic pornography, child sexual abuse, and violence, causing psychological damage for which they have no right to redress for in their countries.[4] These human collaborators aren’t ever framed as such. Instead, they are hidden under the pretence that this technology functions without human intervention.
The sacrifice of creative vulnerability is a risk when artists employ LLMs in their making process. Being an artist is a vulnerable pursuit and while not all practices are inherently collaborative, the way artists engage with each other often is. Through critique sessions, artist talks, mentorships and workshops, we connect with other artists, arts workers and writers in meaningful ways that aid in the development of our own ideas. This process, especially receiving criticism, is rewarding but often uncomfortable: oscillating between feelings of self-doubt and self-trust. The unspoken social parameters around how much reassurance I can ask for from my peers and mentors are not present with chatbots. I could request and receive validation from LLMs during every step of the creative process, if I wanted, but doing so would slowly sever any trust I have in my own capacity to develop authentic ideas. Given that these technologies cannot view art corporeally, misplaced trust in their capacity to relate to art could hinder how embodied intelligences might create without machine intervention.
Opposingly, in her body of work After (2020), Kaurna and Peramangk-based textile artist Kasia Töns investigates a post–technological world that thrives on collaboration between humans and nature. Töns hand embroiders, beads, paints and stitches her works, ritualistically pulling needles through fabric, felt, and whatever else she finds. After was inspired by E.M Forster’s novella The Machine Stops (1909) and fuelled by her own reckoning with addictive technologies that were universally accelerated during the COVID-19 lockdown. Through a diverse exhibition of textile, photographic and animation works, Töns stitches together stories of a future in which humans and nature connect through bodies instead of screens. Her commitment to labour-intensive processes rejects the immediacy of online culture and offers slowness, tactility and collaboration as a remedy to digitally-induced hyperaroused nervous systems. This process can also speak to how we build relationships with each other in the physical world. Through care, touch and tension our bodies release endorphins that embellish our sensory webs with emotionally intimate relationships. These are unstitched and stitched again as rupture and repair inevitably occur; they are reinforced when we are vulnerable with each other.
The increasingly more common outsourcing of companionship, administrative and financial tasks, writing and idea consolidation to LLMs are a result of the overworked and underpaid working and middle classes. With this in mind, I aim for my life to resemble the one Töns imagines in After. By engaging with a sensorial world that embraces collaboration, conflict, friction and self-trust, I will mend the delicate web inside my body. I will be vulnerable with the people close to me because there will never be a technology that can put its flesh on mine to trigger sweet, remedying chemicals to flow through my skin. I could ask ChatGPT everyday for tips on managing grief, but it will never stroke my back while I sob.
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[1] Ioan Roxin, interviewed by Anne Orliac, ‘Generative AI: the risk of cognitive atrophy,’ Polytechnique Insights, 3 July 2025, https://www.polytechnique-insights.com/en/columns/neuroscience/generative-ai-the-risk-of-cognitive-atrophy/ (accessed 2 February 2026).
[2] Max Fisher, The Chaos Machine: The Inside Story of How Social Media Rewired Our Minds and Our World, Little, Brown and Company, New York, 2022.
[3] ‘Humans in the AI loop: the data labelers behind some of the most powerful LLMs' training datasets,’ Privacy International, 15 August 2024, https://privacyinternational.org/explainer/5357/humans-ai-loop-data-labelers-behind-some-most-powerful-llms-training-datasets (accessed 6 February 2026).
[4] Anuj Behal, ‘“In the end, you feel blank”: India’s female workers watching hours of abusive content to train AI,’ The Guardian, 5 February 2026, https://www.theguardian.com/global-development/2026/feb/05/in-the-end-you-feel-blank-indias-female-workers-watching-hours-of-abusive-content-to-train-ai?CMP=Share_iOSApp_Other (accessed 6 February 2026).
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