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The Half Life of Facts

This book should start with chapters eight and nine, which establish the following principles:

  1. Humans are not a reliable source of information, and often take a long time to come around to a fact.
  2. There are noted biases in the pool of established scientific truth though published papers, both in terms of what does and does not get published.

The second point is the most important, because it puts a shade on every other chapter, which uses as its evidence usually a network graph of research papers as a way of establishing how truth changes. I found the argument to be challenging to accept because research is such a faulty mechanism except in the scientific and academic communities, and even then, we are working with only a portion of the full story, at best.

I really wanted this book to be a good treatise on quantifying the half life of information, something I wholly support as an intuition. Information changes at a regular rate, and some information changes faster than other information, a notion I have often used to advocate for taking the long view on learning.

I am endlessly interested in science and philosophy of science, but I felt this book made too bold a claim based on the backing of only research papers. I'd have loved to dig more into network effects or innovation curves.

One good thing that does come out of it is the reinforcement of the sigma curve as a mental model for a whole host of problems.