One of the most important and crucial element of our life is inarguably decision making. It is a process that we all perform incessantly with varying outcomes. From the most trivial decisions like which Netflix series to binge watch, to the most existential ones like what is the right occasion to deploy a nuclear weapon, decisions decide the quality of our individual and collective being.
Algorithms To Live By: The Computer Science Of Human Decisions is a book written by Brian Christian and Tom Griffiths, that tries to compare human decision making with algorithms developed by engineers for the efficient running of computer systems. The books points out several daily life cases where algorithmic logic can be employed for decision making. Algorithms are basically a series of steps that solve a problem, which is what we do in our life too, sometimes consciously, like when we assemble a furniture using instructions or many times unconsciously, like when we plan a shopping trip across multiple shops.
The book is divided into 11 chapters, and in each one, authors demonstrate how a specific type of algorithm can be logically used to solve certain problems that are encountered in life. The book also details the evolution of these algorithms and surprisingly most of them are tweaked from solutions existing mathematical puzzles. In some cases, human mind follows the same logic unconsciously to reach the solution by itself.
It is also important to note that, most of the algorithms are not mathematical formulas, which once applied lead us to a perfect solution. Application of algorithmic logic doesn't lead us to the best decision, but it can show us the one solution that has best probability to be perfect.
For example, if you want to find a rental place in a month's time, 'optimal stopping' algorithm will suggest a look/leap approach. You start looking and apprising all the apartments without selecting any for a period of time and then going for a leap and selecting the next best that comes your way. Your looking period should be 37% of the total time you have to maintain the probability to get the best possible apartment for you.
Likewise consider that you are in a new town for a period of one month and you have to eat in restaurants for the whole period. Would you explore as many restaurants as possible in a month, or will you settle for the first good one after finding it by exploring for it. Algorithmic approach of explore/exploit logic would be to explore initially and once your departure from the town is near, go for the best ones that you find by exploring and exploit them. Another intersting example for this approach is Hollywood, which explored many types of movie making for decades and now when it perceive its end, started exploiting all that it explored by making sequels, reboots and spin-offs.
Apart from these approaches, other chapters deals with human activities of sorting, caching, scheduling, communicating and dealing with other persons. I loved the chapter on using game theory to maximise mutual benefitting from human interactions. One important concept to clearly comprehend while using these techniques is that none of these are instant fixes. Applying algorithmic logic to real world problems will result only in the best probable result. Using it consistently over longer periods of time will better the probability to get the best solutions.In the author's own words:
...the best algorithms are all about doing what makes the most sense in the least amount of time, which by no means involves giving careful consideration to every factor and pursuing every computation to the end. Life is just too complicated for that.