Thursday, February 15, 2024

Algorithms to Live By: by Brian Christian and Tom Griffiths **

Algorithms to Live By begins with a clever premise. Here is a Self-Help book based on Computer Science. The first half of the book offers advice on: • what to do when faced with many alternatives, • how to divide your time between familiar and novel pursuits, • how to organize your stuff, and • how to organize your time. For example, if you need to deal with many documents, a stack is more efficient than sorting or filing them. However, after chapter 5 the book becomes a Computer Science history book with more math and less accessible advice. If you are not familiar with Lagrange and Laplace, you might want to stop reading at that point. An interesting addition to the Self-Help genre that unfortunately loses its way.

The authors explore the problem of what to do when faced with many alternatives. They represent this problem by considering someone with a long list of job applicants (too many to interview them all) and how they might decide that they’ve seen enough people, and it is time to hire someone. The problem is called the “secretary problem,” with the notion that the interviewer is male, and the applicants are female. The authors acknowledge this label is sexist, but with the excuse, “The first explicit mention of it by name as the “secretary problem” appears to be in a 1964 paper, and somewhere along the way the name stuck.” With the word “somewhere,” the authors continue this sexist language (“Secretary problem” is used 63 times).

Often while reading the book, I admired the brilliance of the analysis contrasted with the uselessness of the result in everyday life. Once the problem was modeled and solved, the real world was left behind and the solution, clever as it was, was not practical. As an example, after a long analysis of parking in a busy city, we have this: We asked Shoup if his research allows him to optimize his own commute, through the Los Angeles traffic to his office at UCLA. Does arguably the world’s top expert on parking have some kind of secret weapon? He does: “I ride my bike.”

Some of the classical problems discussed in the second half of the book are: the traveling salesman problem, the halting problem, the prisoner’s dilemma, packet switching, and the tragedy of the commons. Though they have little to do with computers, the book also takes time to debunk the marshmallow test and to analyze professional poker.

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