Tournament-informed task selection in adversarial QD produces higher quality and diversity in coevolved solutions across Pong, cat-and-mouse, and pursuers-evaders games.
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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.
citing papers explorer
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Tournament Informed Adversarial Quality Diversity
Tournament-informed task selection in adversarial QD produces higher quality and diversity in coevolved solutions across Pong, cat-and-mouse, and pursuers-evaders games.
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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.