Thinking in Experiments. How AI Changes DoE Fundamentals (Part-1)

Thinking in experiments under an AI‑rich toolbox requires re‑centering on first principles: biological systems are interactive, nonlinear, and noisy; DoE is still the most defensible way to interrogate them; and AI is useful only to the extent that it operates inside that logic. The sub‑topics below articulate how classical DoE concepts, biological variability, and a human–AI division of labor fit together into acoherent decision framework.

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