Algorithms to Live By: The Computer Science of Human Decisions

All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such problems for decades. And the solutions they've found have much to teach us.

I am reading this book now. So far I have gotten through the Optimal Stopping chapter which has spurred me to do a lot more research on the 37% rule. If 73 is the best number, 73 is the 21st prime number. Its mirror, 37, is the 12th and its mirror, 21, is the product of multiplying 7 and 3, and in binary 73 is a palindrome, 1001001, which backwards is 1001001. I may need to add that the mirror 37 is the optimal stopping percentage :-).

The explore/exploit chapter has helped me to refine my solution frameworks in my daily work for clients. It also adds more data science to my 'start with the end in mind' and Amazon's working backwards which are both more qualitative in nature.

In chapter 3 we dive into SORTING and the author makes a very compelling argument for me to stop worrying about organizing my emails. The effort to sort time is a waste because the search is so powerful that I don't get any real value from all those folders. I am just going to archive emails so they are out of my way, and let search do all the lifting when I need to find something.

Here is the Link to the Amazon book.