Automate This: How Algorithms Came To Rule Our World - Christopher Steiner (2012)
Have you ever wondered how we got to the point of automaton being a part of every aspect of our interactions with the commercial world? Wonder no longer. In his recent book "Automate This" Christopher Steiner explores the history of selected technology wizards and innovators who developed ways to use hardware and software algorithms to automate and predict human actions. It is in that realm that Steiner explores the massive influx of technology and technical talent into Wall Street and the money machine that drove the innovations of the 80s, 90s and the first decade of the new millennia.
Steiner starts with the iconic story of Thomas Peterffy, whose deterministic style and brilliant mind led him to bring the first streams of technology into the Wall Street world of high finance, commodities, options and stock trading, which eventually led to the consummation of CDOs and other debt instruments that rule the financial world and have contributed to the harried meltdowns we experienced in recent decades. Peterffy's story resurfaces throughout the book as a marker of what algorithms and their creators are all about.
The book revisits the grander history of algorithms from Euclid to Persian mathematician Abu Abdullah Muhammad ibn Musa Al-Khwarizmi to Fibonacci to Newton, Leibniz, Gaus, Pascal, George Boole and others who significantly contributed to the development. The book also spends a chapter exploring automation algorithms in music, from A&R evaluation of songs to writing actual music compositions that match Bach. One chapter detours on the central value of algorithms being their speed of use in automation, and how Daniel Spivey dug a direct "dark fiber" cable from New York to Chicago to ensure he had the pipeline for the fastest speeds of trading decisions to the needed locations- a business (Spread Networks) which became the main pipeline for trading companies wanting ultimate transaction speed for their automation bots handling trading.
Steiner explores the various algorithmic systems from Big Blue to Watson to baseball stats systems, all of which use highly tuned formulas in computers to determine the best ways of winning at the big money of various gaming scenarios. The book becomes very personal, however, as it discusses physician-assisting algorithms that can already handle making diagnostic recommendations, pharmaceutical decisions and even filling the prescriptions via robots. The other well known application of automation he explores is personality evaluations for everything from dating to NASA crew evaluations.
But the book actually comes to rest in a surprising position of recommending that big finance was somewhat of a culprit and that the new world of Silicon Valley is the place all the engineering and technical talent should be focused on. He even brings a call to people to focus on more engineering careers and pursuing computer science in college degrees. His premise lands with the ideas that high finance had previous siphoned off all the high quality technical minds to develop transaction splicing algorithms during the 80s-00s, but that now Silicon Valley needs those minds and talent for real development.
The book is well-written and interesting, though seems rather self-serving, since the author is notably one of those crowd who has defected Wall Street for the glamour of Silicon Valley. The history, back story and prospects of algorithmic work is very interesting and very compelling. Steiner leaves out three of the most important examples of algorithmic influence in companies: Microsoft, Google and Amazon. For some reason, the author decides to ignore these icons, even though it would be hard pressed to find (outside of Facebook) larger success stories based on just the kind of development and algorithms he explores in the book.
Overall the book is definitely worthwhile, as it is a short read (just 250 pages) and very well researched. The style is conversational and non-tech people will not have any problem following the dialog here.
Amazon Link: http://amzn.to/18ZFdOM
Review by Kim Gentes
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