Gen-Xer, software engineer, and lifelong avid reader. Soft spots for sci-fi, fantasy, and history, but I'll read anything good.
Self-organization -- it's a profoundly self-evident quality of nature, but one that so far has eluded much deep understanding in science. Strogatz makes it easy to see why: nature, from atoms up to cells up to societies, is made up of many non-linear components working together, and non-linear systems, with their feedback loops, impulses, and fractal components, are fiendishly difficult to get one's head around, nothing like the idealized systems we encounter in Freshman Physics. Yet, their non-linearity is the key to... well, maybe everything?
Sync explores the synchronization phenomena inherent in many complex systems, the way they coordinate their actions with respect to time, building order out of seeming noise. From fireflies to circadian rhythms to swinging pendulums to brain neurons to orbiting bodies to Higgs boson fields, there's an eerie tendency in nature for things to fall in step.
Despite being free of equations, it's a book that delves into some pretty dense territory, and might not be well suited to audiobook form. In most chapters, I found that a moment of daydreaming or distraction would have me rewinding to get back on track with the lecture. Strogatz spends a lot of time explaining abstract models, which held my interest as an engineer (the runners-on-a-track metaphor actually mirrored a traffic simulation I’d developed, which had sync issues of its own), but might appeal less to other readers. There are also some rather esoteric topics in physics, which I didn’t understand very well. I kinda wish he'd put those chapters towards the end, because I almost quit listening after one frustrating section dealing with spiral waves, which luckily turned out to be followed by a much more interesting and accessible overview of Chaos Theory. I also liked the chapters that explore networks and their characteristics (think of the connections between film actors, exemplified by the party game “Six Degrees of Kevin Bacon”).
If you're hoping for some grand unifying theory of synchronization, you won't find it here, just an examination of some different systems in which sync is present and praise for the work of several different researchers. I wouldn’t have minded more resonance between the separate parts (as it were), but I was curious about the topic and the book was worth my time. It’s always cool to learn about a field in which many key developments have happened within my own lifetime. Strogatz convinced me that the qualities that make self-organizing systems difficult to model with traditional mathematics might be the same qualities that are most important to understand. As a software developer, I found it exciting to think about how computers will be used to further exploration of the universe’s emergent interconnectedness, and how discoveries might feed back into how we think about software design. We might even find out something profound.
A better title for this book might be "How Humans Misunderstand Randomness". If you want to feel nervous about an upcoming performance review at work or day in court, Mlodinow can help you do so. Here, he shows how non-intuitive statistics and probability can be, and how people biased by their natural desire to attribute definite causes to events tend to discount the winds of chance. Consider how "brilliant" CEOs are often hired for enormous salaries, then fired a few years later when the company doesn't make the profits expected. But how much control does a typical CEO really have over all the factors that determine a company's near-term success? And consider how obvious the "clues" to Japan's WWII attack on Pearl Harbor looked in hindsight, but how they actually wouldn't have jumped out to analysts among all the other "noise" in the intelligence network. (These themes might be familiar to those who've read Nassim Taleb's book on unpredictability, The Black Swan.)
On the other hand, when we *do* think about randomness, we often have incorrect expectations about its properties. Gamblers don't always realize that it's not unlikely for a roulette wheel to favor a certain color over many spins, even when the roulette wheel is behaving correctly. Or, think about some of the mistakes the legal system has made. An example is the couple in 1960s Los Angeles who were convicted of an attack on the basis of witness testimony that reported two people with similar appearances and a similar car. The prosecution cited the one-in-a-million odds that the criminals could be anyone else. Yet, they made a few critical mistakes: the variables weren't independent and Los Angeles is a city of multiple millions: the real odds were closer to two-in-three. Yikes.
The Drunkard's Walk includes, along the way, a compelling history of the science of chance, covering figures such as Pascal, Bayes, Laplace, Brown (of Brownian Motion fame), and Einstein. Though I've studied probability and statistics before, as part of my college coursework, I find them to be fun subjects, and enjoyed the refresher (if not so much the reminders that our legal system is flawed). A bit of a nerdy book, but perfectly engaging.
Chaos, the concept, is often explained in terms of a butterfly flapping its wings in one part of the world, which sets off a long chain of consequences leading to rain falling in another part of the world. It's an overworn cliche by now, but one that still gets to the heart of a quality of nature that scientists and mathematicians prior to the 20th century didn't really grasp. It was hardly their fault. Living in the age of slide rules and tables (or before), they can't really be blamed for focusing on phenomena that were predictable, linear, and led to stable outcomes, and ignoring those that seemed too noisy, erratic, and error-prone to be represented with an equation.
Yet, as the age of computers dawned, it became clear that the "noise" in many natural systems wasn't error at all, but held its own elusive underlying order. The feedback loops in these systems would magnify initial discrepancies over time, but they would also perform a sort of self-correction, giving rise to repeated patterns and patterns-within-patterns -- similar, like the shape of clouds, but never exactly the same. It's now apparent that this complex dance between coherence and instability, between the macroscopic and the microscopic, drives many of nature's most interesting phenomena, from the branching of blood vessels into smaller ones, to how particles of smoke curl around each other, to the way a snowflake's shape reflects its journey through the atmosphere. Human consciousness itself seems to be an example of a chaotic, endlessly self-referential system.
Chaos, the book, though written in 1987, still does an excellent job of connecting the discoveries that opened the door to Chaos Theory. Gleick introduces us to figures like Edward Lorenz, whose work in weather prediction revealed that tiny differences in input in even simple mathematical models could lead to vast differences in output over time; Robert May, who discovered chaotic patterns in population dynamics; and Benoit Mandelbrot, now considered the father of fractals. Along the way, he touches on fundamental concepts like strange attractors, fractal dimension, bifurcation, complex boundaries, and the Mandlebrot set (whose astonishing visual representation you've seen if you’ve set foot in a poster shop in the last 25 years).
This is one of those books I'd recommend to people who already have some familiarity with the topic. While its purpose is introductory and there's little math, per se, I think the underlying profundities will be more obvious to readers who have taken a college-level math course or two or three. That disclaimer aside, I found Gleick's writing articulate, and seldom had much trouble visualizing what he was talking about, even listening to the audiobook. It's worth having the print edition on hand for the pictures and diagrams, but if you don't, the internet should suffice.
Despite being 25 years old, Chaos remains an invigorating read, offering a sense of discoveries and inventions yet to be made, and demonstrating that separate fields like physics, chemistry, biology, information theory, computing, cognitive science, climatology, and economics aren't as separate as we might think. As bonus, a 2000s-era afterward in the audiobook provides a brief update of progress in some areas since the book's original publication, and some thoughts on its cultural impact.