

AI Receipt
Every time you ask Chat GPT a question, someone somewhere pays with mined cobalt, with clean water, with invisible labor. A never-ending stack of receipts spills from an Bluetooth thermal printer controlled by an ESP32. Each one logs the hidden cost of a single prompt: grams of CO₂, liters of water, seconds of exploited work. It’s simple, almost mundane, like a supermarket ticket. But it reveals what tech giants want you to ignore.
Each query increases the need for more energy, more raw materials, more water. While humanity struggles to stay within the fragile boundaries of our planet, AI surges forward, devouring energy at a rate that could rival the annual electricity consumption of entire nations. Its current consumption already matches that of the Netherlands and continues to grow exponentially.
Behind the sleek algorithms and seamless user interfaces lie workers in sweatshops, miners in conflict zones, and servers burning through endless watts of power. Yet, most AI companies refuse to disclose the environmental impact of their models or the labor conditions that sustain them. Instead, they reshape public perception: AI becomes a miracle, intelligence without effort, output without origin. But this is an illusion. AI is not immaterial. It is an infrastructure of extraction, disguised as magic. It’s built on the backs of workers and the depletion of the planet. Leading tech companies wants you to forget the labor. To overlook the damage. But the receipt makes the invisible visible again.
References
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Li, Pengfei, et al. "Making AI Less 'Thirsty': Uncovering and Addressing the Secret Water Footprint of AI Models." arXiv, 3 Apr. 2023, https://doi.org/10.48550/arXiv.2304.03271.
Perrigo, Billy. "Exclusive: OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic." Time, 18 Jan. 2023, https://time.com/6247678/openai-chatgpt-kenya-workers/.
Regilme, Salvador Santino F. "Artificial Intelligence Colonialism: Environmental Damage, Labor Exploitation, and Human Rights Crises in the Global South." SAIS Review of International Affairs, vol. 44, no. 2, 2024, pp. 75-92. Project MUSE, https://dx.doi.org/10.1353/sais.2024.a950958.
Van Noorden, Richard. "The Carbon Footprint of ChatGPT." Towards Data Science, 19 Jan. 2023, https://towardsdatascience.com/the-carbon-footprint-of-chatgpt-66932314627d.