My Weird Prompts
AI companies market their models as self-learning miracles, but the reality is far messier. Behind every polished chatbot and self-driving car is a global workforce of data annotators — mostly in Kenya, India, and the Philippines — labeling images, ranking responses, and filtering toxic content for $1-2 per hour. This episode unpacks the booming $13.7 billion data annotation industry, the difference between supervised learning labeling and RLHF, the psychological toll on workers exposed to traumatic content, and the uncomfortable truth that AI's intelligence is built on invisible human labor. We explore why this work exists, who does it, and what it means for the future of AI development.
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