Algorithms to Live By

It takes decades of computer science learning and shows us how to apply it to our everyday lives. They call it “human algorithm design—searching for better solutions to the challenges people encounter every day”. In learning to think algorithmically about common daily problems, Algorithms to Live By teaches us how to reduce the cognitive processing required to make good decisions, which in turn can improve our quality of life by not only optimizing the probability that our decisions result in our desired outcomes, but also by reducing stress and the time required to make informed decisions. It does this by contrasting computer algorithms, or the methods with which computers make decisions, with the methods people commonly use to make decisions.

Algorithms to Live By covers 11 different areas of problem solving:

  1. Optimal Stopping
  2. Explore/Exploit
  3. Sorting
  4. Caching
  5. Scheduling
  6. Bayes’s Rule
  7. Overfitting
  8. Relaxation
  9. Randomness
  10. Networking
  11. Game Theory

Ultimately, it shows us:

How to manage finite space, finite time, limited attention, unknown unknowns, incomplete information, and an unforeseeable future; how to do so with grace and confidence; and how to do so in a community with others who are all simultaneously trying to do the same.

If you’ve read books like Superintelligence or Reality is Broken, or have been interested in non-fiction writing of similar emerging technology categories, definitely put Algorithms to Live By on your reading list. It’s a wonderful, thought-provoking and truly eye-opening read.

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