This connects to decades of research on ensemble methods, mixture of experts, and collective intelligence. But having a clear taxonomy helps us understand when and why AI transcendence happens - crucial for building systems we can trust and understand.
The practical takeaway? When designing AI training data, diversity isn't just nice to have - it's fundamental to achieving capabilities that genuinely serve human needs. The future might be less about human vs. AI and more about human with AI in ways we're just beginning to understand.