Hyper-datafication in frontier AI increases resource consumption and redistributes environmental burdens, labor risks, and representational harms toward the Global South, data workers, and under-represented cultures, based on analysis of 550,000 Hugging Face datasets and Kenyan worker responses.
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Chatbot AI systems often fail complex needs while projecting authority, contributing to deskilling, labor displacement, economic concentration, and high environmental costs, so alternative pluralistic and task-specific designs are needed.
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How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI
Hyper-datafication in frontier AI increases resource consumption and redistributes environmental burdens, labor risks, and representational harms toward the Global South, data workers, and under-represented cultures, based on analysis of 550,000 Hugging Face datasets and Kenyan worker responses.
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What if AI systems weren't chatbots?
Chatbot AI systems often fail complex needs while projecting authority, contributing to deskilling, labor displacement, economic concentration, and high environmental costs, so alternative pluralistic and task-specific designs are needed.