There is a new Big Thing coming. I’m not talking about the election, but a deep secular cycle in technology that has enormous implications for our economy.

The pessimists are wrong about the end of innovation, and growth, just as they have been serially wrong for as long as there’s been techno-pessimists and intellectual Malthusians. But the end-of-growth meme is now running rampant again. See for example recently in The Financial Times, Is unlimited growth a thing of the past?

The next growth-fueling revolution is brewing in software, metadata and Big Data. It’s a subject I’ve touched on frequently (see for example here and here). And it’s a subject that’s far from exhausted as we try to unravel what’s happening already, and what might yet happen. That’s why I was happy to read Christopher Steiner’s new book, Automate This: How Algorithms Came to Rule our World.

If you think you’re expert in this field, read it. And if you’re not an expert, read it. Steiner is a fluid writer and possesses one particularly admirable skill. He can explain arcane technical things with rare lucidity.

And by way of disclosure, I was far less enthusiastic, to put it diplomatically, about Steiner’s previous book, $20 per Gallon, when I wrote about it in 2009 (Don’t Bet On $800-A-Barrel Oil). But all is forgiven with his new book that focuses on one of the most important structural changes to our world – algorithms for everything.

One delightful aspect of Steiner’s research is the time he takes to illuminate the roots of algorithms – the core conceptual operating logic. You don’t have to be a programmer or mathematician to understand the underlying power of algorithms, as Steiner ably demonstrates.

An irony, speaking of history, and an unsurprising fact for mathematical historians:

- "The word
*algorithm* comes from Abu Abdullah Muhammad ibn Al-Khwarizmi, a Persian mathematician from the ninth century who produced the first known book of algebra."

As they say, I’m just sayin’. And the enabling root for creating encrypted algorithms, a key to communications, dates back to the ancient Greek mathematician, Euclid of Alexandria. Steiner briefly explains that the roots of binary code originate with the great Leibniz (Newton’s contemporary and near equal intellectual giant) and others like Gauss, Fermat and Fibonacci, the latter made familiar to many in the odious Dan Brown book, The Da Vinci Code.

But the central magic that underlies the modern power of algorithms arguably resides with George Boole. Steiner quotes from Boole’s introduction to his 1854 (yes 19th century) book:

- "The design of the following treatise is to investigate the fundamental laws of those operations of the mind by which reasoning is performed."

Boole figured out, gave mathematical expression to, how to make machines, in effect, think. It only took 150 years for engineers to finally build hardware fast enough to employ Boolean logic in universally useful ways.

Trust me, the math ideas matter and Steiner executes explanations more usefully than many I’ve read. But lest you think his book is all about math history, he covers the landscape from Google’s driverless cars to the software that’s killing jobs for lawyers. And even though the math is central, he spends as much time on music and money.

It’s with the money, with stock traders, Wall Street and especially high-frequency traders that Steiner devotes the largest share of his treatise. He begins and ends the book with Wall Street. If you don’t understand the how and why algorithms matter in financial circles, you will after reading Algorithm. It will help make sense of the revelation in that great Jeremy Irons movie, Margin Call. And he will help you understand why it’s likely Congress will eventually decide to intervene in high-frequency trading.

And you learn more cool history too. Steiner traces the pursuit of velocity in markets back to the early 19th century. The guy that started the pursuit of trading speed was one Paul Julius Reuter – a German whose birth name was Israel Beer Josaphat — who learned finance as a young clerk at his uncle’s German bank. Reuter’s (the root of today’s news service) key competitive advantage was getting financial information to markets faster than anyone else. He used pigeons to carry stock exchange closing prices 100 miles beating out both the horse and railroad couriers. Speed mattered then, and still does. Now the competitive advantage is measured in milliseconds.

Steiner doesn’t praise Wall Street. In fact, consider one subtitle: "The Damage Wrought by Wall Street." But he makes a cloud-with-silver-lining point in noting that Wall Street’s collapse has unintentionally encouraged many bright lights in the algorithm communities, both older and recent graduates, to pursue careers in Silicon Valley and Manhattan in non-financial businesses. He believes (and I agree) this will be good for America.

Then there’s music. Yes music too has been invaded by algorithms. We learn about algorithms not just for predicting what will be a top hit in music or movies, but for composing music whether jingles or perfect simulacrums of Bach. And we learn about algorithms that are unraveling mysteries buried in the music of the Beatles. Fascinating. Who knew – well except Beatlemaniacs? Steiner treats us to the work of Canadian professor Jason Brown, who finds and will yet unveil further Beatles’ secrets. (No "spoiler alert" needed here – you want to know the secret, read the book.) The point of course is that if algorithms can not only unravel but even create something so humanly subtle as music, what is that they cannot do? This may be frightening to some, but is nonetheless deeply fascinating and important to understand.

Even though Steiner doesn’t explore the full panoply of what is happening and will happen with algorithms, he does touch on many representative examples. He notes briefly that eLoyalty algorithms found their roots in NASA’s attempt to map personalities that could get along in space missions. He writes about the start-up Narrative Sciences with its algorithms that write clean journalistic text directly from data and spread sheets. This latter I wrote about earlier as well (see Has Apple Peaked? Hardly.), where I noted that such powerful algorithms have many other uses the company is surely keeping proprietary.

The scope of the impact from algorithms reaches far and deep. Let me suggest a couple of other illustrative examples coming out of Northwestern University, just to pick one place in part because it’s Steiner’s alma mater. We see in professor Hani Mahmassani (Transportation Chair), algorithms in development that will allow traffic forecasting similar to how we forecast weather. And then there’s QuesTek Innovations, a Northwestern spin-out and bellwether for the computational manufacturing revolution. QuesTek uses physics-based algorithms to design unique alloys literally from the atom up.

The power of Boolean logic is being unleashed everywhere now because of modern IT hardware; the infrastructure that makes it all possible. As Steiner writes: "Algorithms in our homes have been largely enabled by the wondrous code and telecommunications infrastructure that make up the Web. … The value of algorithms is all in their speed … Speed is largely determined by one thing: hardware."

It’s on the hardware side that Steiner spends the least time. But it is the hardware that has unleashed the power of math and logic, from Euclid to Boole and Shannon, that have been waiting dormant for decades and even centuries. This is quite unlike any previous revolution. The age of electricity wasn’t unleashed by Edison based on some musings of a thinker 200 years earlier. And given the kind of IT hardware capability that is now emerging we should expect to see an acceleration of what Steiner writes about. The stage is set for a brave new world.

Meanwhile, if you want to get a feel for the zeitgeist, read Automate This. Some readers will be alarmed, some excited, but few will be disappointed at what they learn.

*Original Source: http://www.forbes.com/sites/markpmills/2012/10/06/down-the-digital-rabbit-hole-as-we-automate-everything/*