Luke Dormehl - The Formula: How Algorithms Solve All Our Problems-And Create More

A t their root, algorithms are little more than a series of step-by-step instructions, usually carried out by a computer. However, if their description is straightforward, their inner workings and impact on our lives are anything but.

Algorithms sort, filter and select the information that is presented to us on a daily basis. They are responsible for the search results shown to us by Google, the information about our friends that is highlighted by Facebook, and the type of products Amazon predicts we will be most likely to buy. Increasingly, they will also be responsible for what movies, music and other entertainment look like, which people we are partnered with in predictive relationships, and even the ways in which laws are enforced and police operate. An algorithm can scan through your metadata and recommend that you will likely make a hardworking employee, just as one could accuse you of a crime, or determine that you are unfit to drive a car. In the process, algorithms are profoundly changing the way that we view (to quote Douglas Adams) life, the universe and everything.

One of my favorite observations about technology is the one often attributed to the cultural theorist Paul Virilio: The invention of the ship was also the invention of the shipwreck. One could, of course, turn this around and say that the inventor of the shipwreck was also the person that invented the ship. Algorithms have had their fair share of shipwrecks (which I will discuss during the course of this book), but they also perform incredibly useful functions: allowing us to navigate through the 2.5 quintillion bytes of data that are generated each day (a million times more information than the human brain is capable of holding) and draw actionable conclusions from it.

As with the old adage about how to carve an elephant statue (you chip away everything that isnt an elephant), I will start out by explaining what this book is not. It is not, for one thing, a computer science textbook about algorithms. There are far better books (and, indeed, far more qualified writers) to achieve this task.

Neither is it a history of the algorithm as a concept. While I considered attempting such a thing, I was put off by both the sheer scale of the project and the fact that its end resultwhile no doubt fascinating under the stewardship of the right authorwould be not entirely dissimilar to the textbook I also shied away from. By this I do not mean that a history book and a textbook are necessarily the same thing, but rather that a history of a once-niche mathematical concept would likely appeal only to those mathematicians or computer scientists already familiar with it.

Instead, I want to tell the story of the myriad ways (some subtle, others less so) that algorithms affect all of our lives: from the entertainment we enjoy to the way we think about human relationships. What do scoring hot dates, shooting Hollywood turkeys, bagging your own poo, and cutting opportunities for lawyers fees have in common? This is a book about the algorithmization of life as we know it.

In my day job, writing about a field known as the digital humanities for Fast Company, Im constantly considering the implications of algorithmic culture and the idea (not always a misguided one) that no matter what the problem, it can be solved with the right algorithm.

A typical illustration of what I mean can be seen in Bill Tancers 2009 book Click: What We Do Online and Why It Matters. Tancerdescribed in at least one place as the worlds preeminent expert on online [behavior]begins his book by describing a radio interview he listened to in the car one day. Being interviewed was a British psychologist referring to a mathematical formula he had developed to determine the most objectively depressing week of the year. After much work, he had discovered that this was the third week of January, a feat brought about by the convergence of failed New Years resolutions, credit-card debt accumulated over the holiday season, and the usual dismal weather patterns. Tancer notes that he remained unconvinced: a perspective that was later backed up when the formula was severely criticized for its lack of scientific rigor. However, his lack of conviction has nothing to do with the suggestion that a reductive formula could possibly provide answers on a topic as complex and multifaceted as depression, but rather because he believes that he had come up with a better formula.