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I heard a confession from a friend the other day who's working on ML in health care who's leaving that field as soon as he can because as best as he and his team can measure, the most important thing ML analytics can bring to hospitals is the mathematical certainty they should have taken the money they spent on ML analytics and hired nurses instead.
To understand how they do this, people need to understand how science is structured. Who does it? Where, and paid by whom? What motivates them? What are their incentives and reward structures? What makes someone credible as a scientist? What constitutes expertise, and how is it acquired and demonstrated? What is the role of peer review in science? How does the scientific community deal with uncertainty and disagreement? What is scientific consensus? How is it formed? How can it be overturned?