The algorithmic strategies that have been honed for computers turn out to be applicable to our daily lives.
I've read a lot of computer-related books in my time. Some of them were really interesting, some were "sort of OK," and quite a few bored my socks off. Happily, every now and then, I've been lucky enough to run across an offering that stands proud in the crowd. One such work is Algorithms to Live By: The Computer Science of Human Decisions by renowned author Brian Christian and cognitive scientist Tom Griffiths.
The underlying premise of Algorithms to Live By is that computer scientists have spent a humongous amount of time and effort researching and honing computer algorithms so as to make them provide results in the shortest time and as efficiently as possible. The thing is that these strategies that have been honed for computers are also applicable to our daily lives. As the authors say in their introduction:
How should a processor allocate its "attention" to perform all that the user asks of it, with the minimum overhead and in the least amount of time? When should it switch between different tasks, and how many tasks should it take on in the first place? What is the best way for it to use its limited memory resources? Should it collect more data, or take an action based on the data it already has?
As an example, suppose you've recently moved to a large city and you have 100 days to look for an apartment, but these little rascals tend to be snapped up almost as soon as they come on the market. Further assume that you are new to the city and you arenít fully sure what to expect in your price range. You could simply plonk your money down on the first residence that comes along, but then you'll be left wondering if this was in fact the worst of the bunch and if you could have done much better. Alternatively, you could hold out all the way to the last day, but then the chances are that you've already seen -- and missed out on -- the best apartment going.
The solution is to look at enough apartments to establish a baseline standard, and then accept the next apartment that comes along that meets, or exceeds, this standard. But how long should you look? The answer -- as we discover in Chapter 1 -- is 37% of your time, which would be 37 days in this example.
The end result is an exploration of the workings of both computers and the human mind, including optimal stopping, deciding whether to explore or exploit, sorting, caching, scheduling, overfitting, relaxation, randomness, networking, and game theory. In addition to learning how computers perform their magic, you'll also discover strategies to optimize your to-do list and organize your bedroom closet.
All of this information is presented in an interesting, humorous, and thought-provoking way, including quotes that really make you contemplate the meaning of "life, the universe, and everything." In the case of the chapter on exploring or exploiting, for example, the following quote really gave me pause for thought:
I had reached a juncture in my reading life that is familiar to those who have been there: in the allotted time left to me on earth, should I read more and more new books, or should I cease with that vain consumption -- vain because it is endless -- and begin to reread those books that had given me the intensest pleasure in my past. -- Lydia Davis
This really hit home for me. I've reached the stage that, when I've finished a new book, I now look at it and think "Was this good enough that I may one day wish to read it again?" Only a very small number of tomes pass this test -- the rest are given away or donated to a good cause.
When I'm engrossed in a book like Algorithms to Live By, I tend to fold the corners of pages that hold some nugget of knowledge or tidbit of trivia I find to be particularly interesting. I just looked at my copy of the book that's sitting in front of me to discover that the corners of the first three pages are folded -- and that's just in the introduction! The bottom line is that this book is a keeper that I would heartily recommend to anyone.
— Max Maxfield, Editor of All Things Fun & Interesting