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Automate This: How Algorithms Came to Rule Our World
The rousing story of the last gasp of human agency and how today’s best and brightest minds are endeavoring to put an end to it.
It used to be that to diagnose an illness, interpret legal documents, analyze foreign policy, or write a newspaper article you needed a human being with specific skills—and maybe an advanced degree or two. These days, high-level tasks are increasingly being handled by algorithms that can do precise work not only with speed but also with nuance. These “bots” started with human programming and logic, but now their reach extends beyond what their creators ever expected. In this fascinating, frightening book, Christopher Steiner tells the story of how algorithms took over—and shows why the “bot revolution” is about to spill into every aspect of our lives, often silently, without our knowledge. The May 2010 “Flash Crash” exposed Wall Street’s reliance on trading bots to the tune of a 998-point market drop and $1 trillion in vanished market value. But that was just the beginning. In Automate This, we meet bots that are driving cars, penning haiku, and writing music mistaken for Bach’s. They listen in on our customer service calls and figure out what Iran would do in the event of a nuclear standoff. There are algorithms that can pick out the most cohesive crew of astronauts for a space mission or identify the next Jeremy Lin. Some can even ingest statistics from baseball games and spit out pitch-perfect sports journalism indistinguishable from that produced by humans. The interaction of man and machine can make our lives easier. But what will the world look like when algorithms control our hospitals, our roads, our culture, and our national security? What happens to businesses when we automate judgment and eliminate human instinct? And what role will be left for doctors, lawyers, writers, truck drivers, and many others? Who knows—maybe there’s a bot learning to do your job this minute.
It used to be that to diagnose an illness, interpret legal documents, analyze foreign policy, or write a newspaper article you needed a human being with specific skills—and maybe an advanced degree or two. These days, high-level tasks are increasingly being handled by algorithms that can do precise work not only with speed but also with nuance. These “bots” started with human programming and logic, but now their reach extends beyond what their creators ever expected. In this fascinating, frightening book, Christopher Steiner tells the story of how algorithms took over—and shows why the “bot revolution” is about to spill into every aspect of our lives, often silently, without our knowledge. The May 2010 “Flash Crash” exposed Wall Street’s reliance on trading bots to the tune of a 998-point market drop and $1 trillion in vanished market value. But that was just the beginning. In Automate This, we meet bots that are driving cars, penning haiku, and writing music mistaken for Bach’s. They listen in on our customer service calls and figure out what Iran would do in the event of a nuclear standoff. There are algorithms that can pick out the most cohesive crew of astronauts for a space mission or identify the next Jeremy Lin. Some can even ingest statistics from baseball games and spit out pitch-perfect sports journalism indistinguishable from that produced by humans. The interaction of man and machine can make our lives easier. But what will the world look like when algorithms control our hospitals, our roads, our culture, and our national security? What happens to businesses when we automate judgment and eliminate human instinct? And what role will be left for doctors, lawyers, writers, truck drivers, and many others? Who knows—maybe there’s a bot learning to do your job this minute.
256 pages, Hardcover
First published August 1, 2012
182 people are currently reading
5187 people want to read
About the author
Christopher Steiner
11 books20 followersChristopher is a civil engineer and a staff writer at Forbes magazine. His book, $20 Per Gallon, was released on July 15, 2009 by Grand Central Publishers.
Intrigued by rising gasoline prices in spring 2008, Christopher Steiner conceived of the concept for $20 Per Gallon when he wondered, simply, how will our lives change in a future of higher gas prices? A civil engineer and a staff writer at Forbes who regularly reports on energy, technology and innovative entrepreneurs, Steiner researched the question. His examination roamed from Manhattan tunnels to desert plane graveyards to organic farm fields and manifested in this book, which breaks down our future and its coming changes in terms of dollars per gallon.
Before his first reporting job at the Chicago Tribune, Steiner worked as a civil-environmental engineer in San Francisco and Park City, Utah. He holds degrees from the University of Illinois at Urbana-Champaign and Northwestern University. He lives in Evanston, Illinois, with his wife, Sarah, and his son, Jackson.
Intrigued by rising gasoline prices in spring 2008, Christopher Steiner conceived of the concept for $20 Per Gallon when he wondered, simply, how will our lives change in a future of higher gas prices? A civil engineer and a staff writer at Forbes who regularly reports on energy, technology and innovative entrepreneurs, Steiner researched the question. His examination roamed from Manhattan tunnels to desert plane graveyards to organic farm fields and manifested in this book, which breaks down our future and its coming changes in terms of dollars per gallon.
Before his first reporting job at the Chicago Tribune, Steiner worked as a civil-environmental engineer in San Francisco and Park City, Utah. He holds degrees from the University of Illinois at Urbana-Champaign and Northwestern University. He lives in Evanston, Illinois, with his wife, Sarah, and his son, Jackson.
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Displaying 1 - 30 of 291 reviews
April 3, 2020
Q:
At a 2010 black-tie banquet in Chicago, a spry Jarecki spotted Scholes across the room nursing a cocktail and lightly conversing. Jarecki made his way over to the Nobel laureate. “You know, you still have our Nobel Prize,” Jarecki said to Scholes. The remark elicited a dry grimace. “He was not amused,” Jarecki says. (c)
Q:
The financial industry, as is the case with most high-paying fields, tends to be dominated by men who are wont to hire more men. So when Peterffy hired the tallest, prettiest, most buxom women he could find, the plan was more than a bit novel. The tactic worked miracles for his order flow. Suddenly, the specialists always took his trades. They put their arms around his traders, chitchatted, and recognized the blondes’ orders as fast as they were issued. “The specialists were thinking, ‘These dumb blondes, what do they know, right?’” Peterffy says.
It’s true that the women Peterffy hired didn’t know much about trading, let alone algorithms. But none of his traders at that time were any good out on their own. And none of them were using the sheets for guidance anymore. Peterffy had devised a new system that empowered anybody to make smart trades. (c)
Q:
The key to it all was a dependable flow of pure data that few others had. And data, as so many hot companies of today have demonstrated, can be the difference between domination of an industry and failure. Peterffy’s operation pioneered the automated compilation and employment of vast data stores on Wall Street, where the mining of such things got its start. (c)
Q:
He explained his success: “You gotta be able to calculate doo-boop-be-deeliyaboop—deal! I can do that.” He had learned math, he said, studying astronomy in the Netherlands and in the air force ...
Van Peebles’s story accentuated the success of the most improbable trading squad roaming the pits of New York, perhaps to this day: three blonde women and one highly acclaimed black writer, director, and actor, all of them well-disguised proxies of an algorithm that dwelled inside a machine. (c)
Q:
Technically, a market maker is required to keep both bids and offers up at all times, no matter where the market goes. But Peterffy had been bending the rules, as a lot of market makers did, cherry-picking the trades he wanted according to the instructions of his algorithm. At no point was he maintaining constant bids and offers. (c)
Q:
O’Connor was so secretive about its methods that when it bought two hundred Symbolics computers in the mid-1980s, executives shredded the packaging so Dumpster-diving competitors couldn’t determine what technology the firm used. (c)
Q:
At a 2010 black-tie banquet in Chicago, a spry Jarecki spotted Scholes across the room nursing a cocktail and lightly conversing. Jarecki made his way over to the Nobel laureate. “You know, you still have our Nobel Prize,” Jarecki said to Scholes. The remark elicited a dry grimace. “He was not amused,” Jarecki says. (c)
Q:
The financial industry, as is the case with most high-paying fields, tends to be dominated by men who are wont to hire more men. So when Peterffy hired the tallest, prettiest, most buxom women he could find, the plan was more than a bit novel. The tactic worked miracles for his order flow. Suddenly, the specialists always took his trades. They put their arms around his traders, chitchatted, and recognized the blondes’ orders as fast as they were issued. “The specialists were thinking, ‘These dumb blondes, what do they know, right?’” Peterffy says.
It’s true that the women Peterffy hired didn’t know much about trading, let alone algorithms. But none of his traders at that time were any good out on their own. And none of them were using the sheets for guidance anymore. Peterffy had devised a new system that empowered anybody to make smart trades. (c)
Q:
The key to it all was a dependable flow of pure data that few others had. And data, as so many hot companies of today have demonstrated, can be the difference between domination of an industry and failure. Peterffy’s operation pioneered the automated compilation and employment of vast data stores on Wall Street, where the mining of such things got its start. (c)
Q:
He explained his success: “You gotta be able to calculate doo-boop-be-deeliyaboop—deal! I can do that.” He had learned math, he said, studying astronomy in the Netherlands and in the air force ...
Van Peebles’s story accentuated the success of the most improbable trading squad roaming the pits of New York, perhaps to this day: three blonde women and one highly acclaimed black writer, director, and actor, all of them well-disguised proxies of an algorithm that dwelled inside a machine. (c)
Q:
Technically, a market maker is required to keep both bids and offers up at all times, no matter where the market goes. But Peterffy had been bending the rules, as a lot of market makers did, cherry-picking the trades he wanted according to the instructions of his algorithm. At no point was he maintaining constant bids and offers. (c)
Q:
O’Connor was so secretive about its methods that when it bought two hundred Symbolics computers in the mid-1980s, executives shredded the packaging so Dumpster-diving competitors couldn’t determine what technology the firm used. (c)
Q:
November 26, 2012
Not really a book, more of an extended magazine article, "Automate This" goes on an "awww look, isn't it amazing" tour of some of the cutting edge applications of computers in multiple industries. It's an uneven journey, suffering from the superficial knowledge of the author, who seems an easy mark for the more self-promotional characters in the industries covered.
About half of the book deals with Wall Street, and shows huge blind spots. Steiner is completely focused on high-frequency trading (HFT) which replaced human market-makers on stock and options exchanges. He misses the potentially bigger story of quantitative investment management and statistical arbitrage, sources of much bigger fortunes than HFT and arguably a greater break in the finance paradigm than HFT which does exactly what human market-makers used to do, only faster. Steiner hypes the Flash Crash of 2011, a non-event of interest only to market geeks, and ignores completely the meltdown of stat-arb powerhouse Long-Term Capital Management which almost brought down the US financial system in 1998.
To me, the most interesting parts of the book were those dealing with computer applications outside of Wall Street, which I wasn't familiar with. I wonder, though, if those sections suffer from the same defects as the Wall Street parts...
About half of the book deals with Wall Street, and shows huge blind spots. Steiner is completely focused on high-frequency trading (HFT) which replaced human market-makers on stock and options exchanges. He misses the potentially bigger story of quantitative investment management and statistical arbitrage, sources of much bigger fortunes than HFT and arguably a greater break in the finance paradigm than HFT which does exactly what human market-makers used to do, only faster. Steiner hypes the Flash Crash of 2011, a non-event of interest only to market geeks, and ignores completely the meltdown of stat-arb powerhouse Long-Term Capital Management which almost brought down the US financial system in 1998.
To me, the most interesting parts of the book were those dealing with computer applications outside of Wall Street, which I wasn't familiar with. I wonder, though, if those sections suffer from the same defects as the Wall Street parts...
January 21, 2020
Excellent review on how automation impact all directions of our live (investments, health, dating, education, etc) and how it'll eliminate some professions (such as pharmacist) and replace them with robots. Don't be scared yet, but read the book to find what is waiting us behind the corner. Highly recommended, bought it today on BookOutlet (https://bookoutlet.ca/Store/Details/9...) - for $5.79 you cannot beat the price - planning to read it more times.
November 30, 2012
Christopher Steiner does an excellent job of explaining algorithms, the "bots" that implement them, and the areas they have been applied to.
Based on detailed interviews with people who developed them, he describes the importance they have in areas of:
finance,
speech recognition,
psychological profiling,
news reporting,
medical diagnosis,
musical composition,
intelligence gathering and interpretation,
games,
customer service,
identity theft,
corporate communications.
Automation in the financial markets is one of the major topics of the book. To give one example, his description of Thomas Peterffy's progression from knowing nothing about the financial markets, through building a robot to type orders to buy and sell stocks, to his founding of Interactive Brokers is fascinating.
He documents the diversion of engineers, mathematicians, physicists, and computer scientists first into the financial industry, then out of it. He provides clear evidence that computer automation is affecting social behavior, advertising, commerce, and employment. He makes a strong case for improvement in education -- particularly in areas of mathematics and science.
I am a retired university professor of computer science. During my professional career, I have been involved in some of the areas Mr. Steiner describes, and I continue to write about methods ordinary individuals can use to create their own "bots" to manage their own investment accounts. Christopher Steiner has it right. He has written an excellent, entertaining, and highly readable book. If, as it appears to be the case, the future is Automate Everything, then "Automate This" is a good place to learn what is ahead for us all.
Based on detailed interviews with people who developed them, he describes the importance they have in areas of:
finance,
speech recognition,
psychological profiling,
news reporting,
medical diagnosis,
musical composition,
intelligence gathering and interpretation,
games,
customer service,
identity theft,
corporate communications.
Automation in the financial markets is one of the major topics of the book. To give one example, his description of Thomas Peterffy's progression from knowing nothing about the financial markets, through building a robot to type orders to buy and sell stocks, to his founding of Interactive Brokers is fascinating.
He documents the diversion of engineers, mathematicians, physicists, and computer scientists first into the financial industry, then out of it. He provides clear evidence that computer automation is affecting social behavior, advertising, commerce, and employment. He makes a strong case for improvement in education -- particularly in areas of mathematics and science.
I am a retired university professor of computer science. During my professional career, I have been involved in some of the areas Mr. Steiner describes, and I continue to write about methods ordinary individuals can use to create their own "bots" to manage their own investment accounts. Christopher Steiner has it right. He has written an excellent, entertaining, and highly readable book. If, as it appears to be the case, the future is Automate Everything, then "Automate This" is a good place to learn what is ahead for us all.
October 11, 2018
Summary: Great book with wonderfully curated examples of how automation has come to pass. I don't love the conclusion. I don't think Steiner meant to do it, but it seems a bit negative.
Automate This has wonderful Wall Street, Medical, and Musical examples that draw a person in. I find what he has to say super relevant. My concern is that his conclusion of that the future belongs to algos and that we should teach STEM somewhat misses the point of the automation, which is to augment human life so that we, i.e. people, can do something else. That something else is scary, but it can also be beautiful and not related to STEM, which... quite frankly, are just iterations of itself (Science is the physical application of Math and Engineering and technologies are just off-shoots of applied Science or Math).
Automate This has wonderful Wall Street, Medical, and Musical examples that draw a person in. I find what he has to say super relevant. My concern is that his conclusion of that the future belongs to algos and that we should teach STEM somewhat misses the point of the automation, which is to augment human life so that we, i.e. people, can do something else. That something else is scary, but it can also be beautiful and not related to STEM, which... quite frankly, are just iterations of itself (Science is the physical application of Math and Engineering and technologies are just off-shoots of applied Science or Math).
October 20, 2012
When you hear "This call may be recorded for quality purposes," Steiner says you're often hearing a company warning you that an algorithm (or "bot") is about to listen in on your call to determine what kind of person you are. In 30 seconds the bot characterizes you and may match you with a similar personality type working in customer service.
This has all kinds of implications for medicine, law, accounting, and many other service fields that would seem at first glance to be immune to the powers of quantification. But the takeover of bots is coming, according to Steiner.
Bots have already begun to take over entertainment (Pandora, Netflix, this very site), and they will soon replace pharmacists, some legal functions, and more.
Steiner's book is a fun read, beginning with the rise of algorithms in the world of finance. That part was the most entertaining to me. But the whole book is most engaging and easy to read.
This has all kinds of implications for medicine, law, accounting, and many other service fields that would seem at first glance to be immune to the powers of quantification. But the takeover of bots is coming, according to Steiner.
Bots have already begun to take over entertainment (Pandora, Netflix, this very site), and they will soon replace pharmacists, some legal functions, and more.
Steiner's book is a fun read, beginning with the rise of algorithms in the world of finance. That part was the most entertaining to me. But the whole book is most engaging and easy to read.
September 27, 2012
This book is the nugget of what could have been a much better and is just good enough to make me frustrated that it wasn't better.
The contention of this book is that more and more of our lives are ruled or influenced by algorithms, sets of instructions that provide a somehow optimized outcome based on simple yes or no decisions. The sections outlining the history of alogrithms are quite interesting and involve a tour of Arab mathematics and the work of Bool and Liebniz but the discussion on modern algorithms is disappointing. The author seems to use algorithm almost any time his criterion is met and this can lead to confusion. He calls Chaos Theory an outgrowth of set theory which I consider at best a stretch and confuses objective vs. subjective. Finally, the author seems to refer to just about all math as algorithms which while being technically accurate when applied doesn't mesh with how I think most people use the term.
The opening few chapters are wonderful as it tracks the personal story of a Wall Street wiz but the end where he hammers on about people leaving Wall Street for Silicon Valley seems out of place. His commentary on how the future workforce will be full of the displaced is reasonable but the logic is undeveloped and leaves much to the imagination.
Finally, the book leaves the reader wanting for hard information about how modern algorithm development works and treats them as a black box. I think this is a disservice to the reader and developers of data-intensive applications.
The contention of this book is that more and more of our lives are ruled or influenced by algorithms, sets of instructions that provide a somehow optimized outcome based on simple yes or no decisions. The sections outlining the history of alogrithms are quite interesting and involve a tour of Arab mathematics and the work of Bool and Liebniz but the discussion on modern algorithms is disappointing. The author seems to use algorithm almost any time his criterion is met and this can lead to confusion. He calls Chaos Theory an outgrowth of set theory which I consider at best a stretch and confuses objective vs. subjective. Finally, the author seems to refer to just about all math as algorithms which while being technically accurate when applied doesn't mesh with how I think most people use the term.
The opening few chapters are wonderful as it tracks the personal story of a Wall Street wiz but the end where he hammers on about people leaving Wall Street for Silicon Valley seems out of place. His commentary on how the future workforce will be full of the displaced is reasonable but the logic is undeveloped and leaves much to the imagination.
Finally, the book leaves the reader wanting for hard information about how modern algorithm development works and treats them as a black box. I think this is a disservice to the reader and developers of data-intensive applications.
July 23, 2017
With the exception of the first chapter which deals with Thomas Peterffy and the creation of Interactive Brokers, the book contributed very little useful information to my knowledge. I guess the message is that we've made huge progress in what can be written into an algorithm compared with what people thought is possible a few decades ago, but isn't that kind of obvious? Yes, the ability to use computers in order to solve what seemed to be unsolvable in the past is pretty remarkable. But the book just doesn't go deep enough into the details - it just uses some anecdotal evidence that I guess suppose to create some kind of "wow" effect with the reader. However, if you already knew that algorithms have a big role in our lives nowadays, this book will not expand your knowledge in a meaningful way.
August 13, 2017
Most people when they hear the word automation think of large factories. The factories were the only place where automation was present for a long while, but the author shows us the places where automation has slowly crawled in and even taken over. The most surprising thing for me was the importance of Wall Street in this change. This book was incredibly enlightening for me, not just because this is what I am studying for, but also as a major wake up call.
May 18, 2020
It's not usual for me to give a 5 to a book that is not fictional. But this book is different. I got it late. I mean the book is released at 2012 andI bought it at 2017. I read it at 2020. I could only imagine it would be a life changer to me if I could read it earlier. If you love science, then you must read it. If you like programming, then you must read it. If you want to know about technology, then you must read it. And finally, if you really think you understand how are the things in your life is working, then you definitely must read it. Because, you are WRONG.
It might seem to be a shallow book about certain information of programming. But I assure you. If you look deep, this is a very serious book. It is handful and could guide you to a better future.
It might seem to be a shallow book about certain information of programming. But I assure you. If you look deep, this is a very serious book. It is handful and could guide you to a better future.
June 14, 2015
I should maybe stick to my rule of not rating any tech books here. I am sure I will be very biased and will mostly give it a 4 or 5. I usually have something or the other that I find very interesting in there.
I thoroughly enjoyed each area that the author explored and how algorithms have changed it. From Wall Street trading to the music industry. Well, a lot. I felt small having not done anything big from a tech perspective. But I too have felt ripples of someone losing a job to a code that I put in. Lets not go there.
A very interesting read for a techie. Should be interesting for others as well to understand what is going on.
I thoroughly enjoyed each area that the author explored and how algorithms have changed it. From Wall Street trading to the music industry. Well, a lot. I felt small having not done anything big from a tech perspective. But I too have felt ripples of someone losing a job to a code that I put in. Lets not go there.
A very interesting read for a techie. Should be interesting for others as well to understand what is going on.
May 14, 2019
"If you’re keeping track, algorithms already have control of your money market funds, your stocks, and your retirement accounts. They’ll soon decide who you talk to on phone calls; they will control the music that reaches your radio; they will decide your chances of getting lifesaving organ transplants; and for millions of people, algorithms will make perhaps the largest decision in their life: choosing a spouse. At least they don’t drive"
June 2, 2020
This book seemed a little myopic in its breadth of material covered. I would say half, or perhaps even more than half, of the book was devoted to how algorithms have revolutionized Wall Street. I got the impression early on that the author’s research was weighted in this direction; perhaps this is the world he lives in or the people he interviewed most, and therefore the material he felt most comfortable writing about.
The rest of the book read as surface-level anecdotes where algorithms were put to work doing various things, like making music, optimizing customer service lines, or helping to read medical diagnostic scans.
What left me with a really sour taste in my mouth was a claim that was made near the end of the book. The essence of it was that unless you know how to write algorithms, your job will be replaced by one. While I don’t argue with the general intent of this premise (in the long run), I felt that the book laid very, very shaky groundwork to make that kind of statement.
Like I mentioned, aside from the Wall Street examples, much of the book is anecdotal: how a few companies have implemented or are implementing algorithms to improve things. And the idea that, just because algorithms exist, means that “human versions” of those creations are irrelevant is not based on anything. There’s a chapter on music, for example. Algorithms can create wonderful music, as good as the most fluent of songwriters. Does that mean that the “demand” for singer/songwriters goes away? Maybe, maybe not, but this is not addressed.
AI was also not addressed at all. How can there be a meaningful discussion about automation taking over the world without talk of machine learning? I’ve also read claims that AI will CREATE the algorithms that automate work one day. Wouldn’t that invalidate Steiner’s whole claim that there will always be demand for good quant people?
The bad here is overcome somewhat by a few things: a) I felt the writing style was excellent. The tone was consistent, topics flowed nicely, and explanations were concise. b) I know more about this stuff than I did when I picked up the book. That’s the first thing I look for when I read non-fiction. c) the anecdotes from other chapters, shallow as they may have been, were interesting. I thoroughly enjoyed reading about the quest for a new fiber optic line between Chicago and New York or the way a European musician got his start thanks to a tech startup that analyzed music.
In my opinion, he needed to either leave the last chapter out of the book where the claim is made that algorithms will take over everything OR provide a broader discussion about machine learning, AI, algorithms, and job/trade data to back up that assertion in a more meaningful way.
The rest of the book read as surface-level anecdotes where algorithms were put to work doing various things, like making music, optimizing customer service lines, or helping to read medical diagnostic scans.
What left me with a really sour taste in my mouth was a claim that was made near the end of the book. The essence of it was that unless you know how to write algorithms, your job will be replaced by one. While I don’t argue with the general intent of this premise (in the long run), I felt that the book laid very, very shaky groundwork to make that kind of statement.
Like I mentioned, aside from the Wall Street examples, much of the book is anecdotal: how a few companies have implemented or are implementing algorithms to improve things. And the idea that, just because algorithms exist, means that “human versions” of those creations are irrelevant is not based on anything. There’s a chapter on music, for example. Algorithms can create wonderful music, as good as the most fluent of songwriters. Does that mean that the “demand” for singer/songwriters goes away? Maybe, maybe not, but this is not addressed.
AI was also not addressed at all. How can there be a meaningful discussion about automation taking over the world without talk of machine learning? I’ve also read claims that AI will CREATE the algorithms that automate work one day. Wouldn’t that invalidate Steiner’s whole claim that there will always be demand for good quant people?
The bad here is overcome somewhat by a few things: a) I felt the writing style was excellent. The tone was consistent, topics flowed nicely, and explanations were concise. b) I know more about this stuff than I did when I picked up the book. That’s the first thing I look for when I read non-fiction. c) the anecdotes from other chapters, shallow as they may have been, were interesting. I thoroughly enjoyed reading about the quest for a new fiber optic line between Chicago and New York or the way a European musician got his start thanks to a tech startup that analyzed music.
In my opinion, he needed to either leave the last chapter out of the book where the claim is made that algorithms will take over everything OR provide a broader discussion about machine learning, AI, algorithms, and job/trade data to back up that assertion in a more meaningful way.
June 3, 2022
Як магістр з автоматизації технологічних процесів, скажу, що тут не про класичну автоматизацію. Краще б було назвати книгу "Тотальна алгоритмізація".
Тези:
1) популярність комп'ютерних технологій, як і програмних алгоритмів - хвилеподібна
2) інженер, щоб бути успішним, обов'язково повинен уміти "кодити" алгоритми
3) вже зараз настав час, коли людина не на всі 100 % керує своїм життям, віддаючи частку прийняття рішень алгоритмам
Тези:
1) популярність комп'ютерних технологій, як і програмних алгоритмів - хвилеподібна
2) інженер, щоб бути успішним, обов'язково повинен уміти "кодити" алгоритми
3) вже зараз настав час, коли людина не на всі 100 % керує своїм життям, віддаючи частку прийняття рішень алгоритмам
April 1, 2020
Audiobook: Audio quality: Good, Narration: Good
It was interesting and informative but not always engaging.
It was interesting and informative but not always engaging.
November 15, 2023
Пізнавальна книга, але, на мою думку, забагато фокусу на сфері фінансів, біржах та Волл-стрит.
May 3, 2021
Good, perhaps showing its age a little, 9 years later.
March 24, 2013
Some harsh reviews here on GoodReads - too journalistic, too superficial. Nevertheless, for dummies like me this was an enjoyable discovery of the many, many ways algorithms are influencing our lives. The idea of a "bot" as your doctor is quite attractive given the ever-increasing levels of complexity and change that your average general practitioner must master in order to give -hopefully - an accurate diagnosis of a patient complaint. The inside story of tracking down the exact chords that open The Beatles song "Help," apparently a long held mystery, with algorithms is fascinating. Some of the older Wall Street hacks are interesting and demonstrative of a rebellious entrepreneurial spirit, the guy who hacked the NASDAQ machine is one example or the people who built their own private dark fiber network between New York and Chicago is another. What Chris Steiner does, and this is, I think, the core of the book, is to irrevocably demonstrate what happened when Wall Street set out to rule the world with algorithms. Faster and faster transactions and increasingly bizarre financial instruments (CDOs anyone?) plus a persistent and raucous vacuuming up of the top engineering and computer science talent in the country.
The result of this is exemplifed in the observations of Duke professor Vivek Wadhwa: “As a new faculty member at Duke, Wadhwa watched as many of his brightest students ended up on Wall Street, conjuring up the very instruments that would lead the world to the brink of economic collapse—collateralized debt obligations, the Gaussian copula (a fine formula that was misused by the Street), and trading algorithms that could go wild at any moment.”
In his conclusions Steiner sees a silver lining in the crash of 2008 and the consequent massive layoffs from Wall Street which is the migration of much of that quantitatively oriented brain power to Silicon Valley. This is a changes of focus to using data for ends more social than financial. Steiner is not all apple pie and roses carefully noting some of the inherent problems that a data-driven society must be aware of. A readable tale of changes affecting us all.
By early 2008, automated bots accounted for 60 percent of all U.S. stock market trades, and the financial industry had spent seven years sucking up every deft graduating engineer, physicist, and general Renaissance man who had even a mild attraction to a large starting salary and a bonus big enough to buy most Americans’ homes twice over. Wall Street had grown to become a larger hirer of math, engineering, and science graduates than the semiconductor industry, Big Pharma, or the telecommunications business.
The result of this is exemplifed in the observations of Duke professor Vivek Wadhwa: “As a new faculty member at Duke, Wadhwa watched as many of his brightest students ended up on Wall Street, conjuring up the very instruments that would lead the world to the brink of economic collapse—collateralized debt obligations, the Gaussian copula (a fine formula that was misused by the Street), and trading algorithms that could go wild at any moment.”
In his conclusions Steiner sees a silver lining in the crash of 2008 and the consequent massive layoffs from Wall Street which is the migration of much of that quantitatively oriented brain power to Silicon Valley. This is a changes of focus to using data for ends more social than financial. Steiner is not all apple pie and roses carefully noting some of the inherent problems that a data-driven society must be aware of. A readable tale of changes affecting us all.
August 3, 2016
A fascinating glimpse into the future as well as the open secret world of bots that quietly exists around us today. While I thought I was pretty up on technology, there were still algorithms that I hadn't realize existed, such as ones that compose music, or the ones that match you to similar personalities in a call center. It's amazing, and perhaps a little scary. But as the author says, they aren't going away any time soon, and I believe that they have the capability for a lot of good.
I really got blocked in chapter two when the history of man and math popped up. It was a little much for my english major brain. But after that, the real world examples of what code and algorithms are doing, starting in the stock market and graduating to the future of healthcare, is definitely worth absorbing.
Another great point was the section on NASA astronaut training. I knew they had some serious personality tests going on in there, but reading about how some of the psychs could figure out their personalities and how they might work/clash with others just after ten minutes of conversation made me want to learn more about it too. I may have to look it up. I'd definitely say that I lead with thoughts-based.
I obviously missed my calling. Should have became a quant and earned millions. But that math/science death march got to me in junior college. Guess that's what I get for taking the easy way out.
The end of the book talks about how everyone should take a programming class in school. That's something I'd 100% support for any of my future kids, not to turn them into quants, mind you, but to give them a greater understanding of this new world they would be born into that is going to rely on algorithms to do the heavy lifting.
I really got blocked in chapter two when the history of man and math popped up. It was a little much for my english major brain. But after that, the real world examples of what code and algorithms are doing, starting in the stock market and graduating to the future of healthcare, is definitely worth absorbing.
Another great point was the section on NASA astronaut training. I knew they had some serious personality tests going on in there, but reading about how some of the psychs could figure out their personalities and how they might work/clash with others just after ten minutes of conversation made me want to learn more about it too. I may have to look it up. I'd definitely say that I lead with thoughts-based.
I obviously missed my calling. Should have became a quant and earned millions. But that math/science death march got to me in junior college. Guess that's what I get for taking the easy way out.
The end of the book talks about how everyone should take a programming class in school. That's something I'd 100% support for any of my future kids, not to turn them into quants, mind you, but to give them a greater understanding of this new world they would be born into that is going to rely on algorithms to do the heavy lifting.
January 13, 2015
As a number of the other Goodreads reviewers have mentioned, this is like an extended magazine article, albeit a rather enjoyable one I reckon. The book is light reading and doesn't go into the technical side of algorithms but I thought the author told the stories relatively well (in a typical Malcolm Gladwell way, a style that seems to dominate popular science books these days).
I picked up in this book because bots are getting increasing better at making decisions and it's interesting to learn examples when computers are being used - either to do jobs that humans were never able to do or to replace the ones that we used to do. We often think of computers as doing non-creative, repetitive calculations but the algorithms that engineers have been developing are really quite incredible. From composing music (which people aren't able to distinguish from human compositions) to listening into our phone calls so that they can match us up with a call centre agent who is better suited our personality. The latter may need more work from my experience :)
Understanding how people make decisions feeds into machine learning but also the opposite is also true. By crunching the data on millions of decisions made, computers are able show patterns of our behaviour and show up what people actually do not what they say they intend to do. We can even monitor, analyse and record our own individual choices so that we can more honestly assess and improve our decisions. Well, until the machines completely take over our lives that is!
All in all, it's a fun book especially if you are relatively new to this topic.
I picked up in this book because bots are getting increasing better at making decisions and it's interesting to learn examples when computers are being used - either to do jobs that humans were never able to do or to replace the ones that we used to do. We often think of computers as doing non-creative, repetitive calculations but the algorithms that engineers have been developing are really quite incredible. From composing music (which people aren't able to distinguish from human compositions) to listening into our phone calls so that they can match us up with a call centre agent who is better suited our personality. The latter may need more work from my experience :)
Understanding how people make decisions feeds into machine learning but also the opposite is also true. By crunching the data on millions of decisions made, computers are able show patterns of our behaviour and show up what people actually do not what they say they intend to do. We can even monitor, analyse and record our own individual choices so that we can more honestly assess and improve our decisions. Well, until the machines completely take over our lives that is!
All in all, it's a fun book especially if you are relatively new to this topic.
November 21, 2019
Wow! An amazing read, the author is a master storyteller. In a story about automation, the author found a way to keep the audience engaged, throughout the book, I was hooked.
The author begins with the incredible story of a Hungarian Immigrant hacking the Wall Street protocols to build an automaton that could trade. It then goes from one place to another in a sequence, it goes to match making for kidney transplants, goes on to, Health Care and Prescriptions, also touches on Paralegals, it also moves to the Silicon Valley and then goes back to the Wall Street again in quick succession. The Author delves into the history of automation, and of algorithms from the first person who created an algorithm, to the woman who wrote the concept of the first software and then flash forwards to the pioneers of various algorithms that changed the world. The story about saving 4 milli seconds between the NSE and Chicago, could only be described as a "Rabbit Hole in the Wall Street". The story about a scientist trying to build a music making machine, in a quest to decipher the mystery of the beetles first string, could only be described as "Searching for a String in a haystack of Musical Noises".
Before reading the book, I was of the opinion that automation hasn't reached the doorsteps of intellectuals. I also had a few qualms that a few industries can never be touched by algorithms, due to the very creative nature of these jobs. But, the author made it extremely clear that nobody is safe from algorithms, no career is an exception, everybody can be automated, except may be the people building those automatons. So the only career that is worth pursuing is CODING!
But that is not the best takeaway from this book, Yes, there is something much better that the author has dealt with in the penultimate chapter.
He talked about the great concept of "USING PHDs to do Janitors Work!"
Even Better "Converting The most productive and creative people in the nation into parasites and debt slaves"
Much Better "Using the best Engineering Talent in the country to count Beans"
HE TALKED ABOUT THE TREND OF THE BEST MINDS IN THE COUNTRY SOLD OFF TO WALL STREET FOR A MILLION DOLLAR SALARIES
Let me explain this vicious loop to my future self - in case I might forget this great concept.
1. The Best minds of the country graduate from premier institutes, left to their own means they would pursue their passions and some of them eventually would strive to convert their passions into profits i.e. become entrepreneurs, this has always been the case with smart people!
2. During this process, they create new ventures, companies and organizations that employ millions of people, create new industries and drive the engine of growth forward in a country. Eventually creating tax revenue generating BEHEMOTHS, say General Motors, Facebook, General Electric, Ford. The Entire Industrial prowess of USA lies in this VIRTUOUS CYCLE!
3. Where ever there is growth, there are PARASITES, i.e. MIDDLEMEN who do little or no work, but start taking their cuts. FINANCE is one of the most vicious parasites, second to none is a FLYBOT PARASITE -RENT - The FIRE sector is general is the parasites that eats away most of the growth in an economy, even before it can reach the hands of the growth drivers and growth creators. There are other parasites, like corruption etc... but let us limit the discussion to FIRE parasites, since the author discussed them at length.
4. The FIRE parasite then starts preying on everything in the economy, which causes the costs of every transaction to rise, i.e. the price of studying in college also skyrocket, as the prices increase, so will the stress of the graduating class, whose only though after graduation is "LOAN ON MY HEAD"
5. In an attempt to clear their loans faster, they take up the best paying jobs, the well paying jobs, often are in PARASITE SECTORS and INDUSTRIES - Why? It pays well to be able to take money without actually building anything! Yes, because they found a way to take a cut without producing anything of value! SO THEY ARE ABLE TO PAY MORE TO GRADUATING STUDENTS.
6. These Graduating students are then employed in the PARASITE SECTORS, to improve the efficiency of these parasites, i.e. how to suck more blood and juice out of the system. There is a very beautiful term to describe this "FINANCIAL ENGINEERING", how do you engineer tools, such that you can take more money and more money, for the same goods and services. Such the last ounce of blood from the caracasses of the consumer, thereby the economy, which means that these graduates increase the efficiency of parasites, which further increase the prices i.e. the prices of the degree they obtain.
7. There is a two pronged loss at play here 1. The best minds in the country are turned into parasites, hungry for money. 2. They are stolen from the otherwise CORE engineering INDUSTRIES that would have employed them to drive growth in the economy. Thus, with one stone called - STUDENT LOAN, you hit both the eyes of the bird (economy/country) and make it blind ! The opportunity cost of employing the best minds in the country away from building great companies and pushing them to become bean counters and build ever more complicated financial tools, i.e. various permutations and combinations of futures, forwards, options, swaps and other derivatives and selling them across various markets to save pennies for their money hungry masters! is extremely huge.
8. The PARASITE sectors forget that they can only suck the blood of the economy which has "GROWTH" - Deprived of the great minds that drive growth, the economy starts to falter, but attenuating this wound are the very great minds, which have now become parasites and started searching all over the economy for ways to suck the LAST BLOOD from it. Eventually the economy become strained by a tug of war between these two factors, of no growth coupled with parasites drawing blood - eventually leading to a complete collapse i.e. the ECONOMIC CRISIS OF 2008
9. Which then release these great minds from the clutches of the failed PARASITE companies, and lets' them choose their real professions. i.e. engineering and driving real growth in the economy.
This is the vicious loop of TOP GRADUATES GOING TO WALL STREET AND NOT TO MAIN STREET OR THE SILICON VALLEY
The author captured this in a beautiful way! That is why I love this book, so much.
The author begins with the incredible story of a Hungarian Immigrant hacking the Wall Street protocols to build an automaton that could trade. It then goes from one place to another in a sequence, it goes to match making for kidney transplants, goes on to, Health Care and Prescriptions, also touches on Paralegals, it also moves to the Silicon Valley and then goes back to the Wall Street again in quick succession. The Author delves into the history of automation, and of algorithms from the first person who created an algorithm, to the woman who wrote the concept of the first software and then flash forwards to the pioneers of various algorithms that changed the world. The story about saving 4 milli seconds between the NSE and Chicago, could only be described as a "Rabbit Hole in the Wall Street". The story about a scientist trying to build a music making machine, in a quest to decipher the mystery of the beetles first string, could only be described as "Searching for a String in a haystack of Musical Noises".
Before reading the book, I was of the opinion that automation hasn't reached the doorsteps of intellectuals. I also had a few qualms that a few industries can never be touched by algorithms, due to the very creative nature of these jobs. But, the author made it extremely clear that nobody is safe from algorithms, no career is an exception, everybody can be automated, except may be the people building those automatons. So the only career that is worth pursuing is CODING!
But that is not the best takeaway from this book, Yes, there is something much better that the author has dealt with in the penultimate chapter.
He talked about the great concept of "USING PHDs to do Janitors Work!"
Even Better "Converting The most productive and creative people in the nation into parasites and debt slaves"
Much Better "Using the best Engineering Talent in the country to count Beans"
HE TALKED ABOUT THE TREND OF THE BEST MINDS IN THE COUNTRY SOLD OFF TO WALL STREET FOR A MILLION DOLLAR SALARIES
Let me explain this vicious loop to my future self - in case I might forget this great concept.
1. The Best minds of the country graduate from premier institutes, left to their own means they would pursue their passions and some of them eventually would strive to convert their passions into profits i.e. become entrepreneurs, this has always been the case with smart people!
2. During this process, they create new ventures, companies and organizations that employ millions of people, create new industries and drive the engine of growth forward in a country. Eventually creating tax revenue generating BEHEMOTHS, say General Motors, Facebook, General Electric, Ford. The Entire Industrial prowess of USA lies in this VIRTUOUS CYCLE!
3. Where ever there is growth, there are PARASITES, i.e. MIDDLEMEN who do little or no work, but start taking their cuts. FINANCE is one of the most vicious parasites, second to none is a FLYBOT PARASITE -RENT - The FIRE sector is general is the parasites that eats away most of the growth in an economy, even before it can reach the hands of the growth drivers and growth creators. There are other parasites, like corruption etc... but let us limit the discussion to FIRE parasites, since the author discussed them at length.
4. The FIRE parasite then starts preying on everything in the economy, which causes the costs of every transaction to rise, i.e. the price of studying in college also skyrocket, as the prices increase, so will the stress of the graduating class, whose only though after graduation is "LOAN ON MY HEAD"
5. In an attempt to clear their loans faster, they take up the best paying jobs, the well paying jobs, often are in PARASITE SECTORS and INDUSTRIES - Why? It pays well to be able to take money without actually building anything! Yes, because they found a way to take a cut without producing anything of value! SO THEY ARE ABLE TO PAY MORE TO GRADUATING STUDENTS.
6. These Graduating students are then employed in the PARASITE SECTORS, to improve the efficiency of these parasites, i.e. how to suck more blood and juice out of the system. There is a very beautiful term to describe this "FINANCIAL ENGINEERING", how do you engineer tools, such that you can take more money and more money, for the same goods and services. Such the last ounce of blood from the caracasses of the consumer, thereby the economy, which means that these graduates increase the efficiency of parasites, which further increase the prices i.e. the prices of the degree they obtain.
7. There is a two pronged loss at play here 1. The best minds in the country are turned into parasites, hungry for money. 2. They are stolen from the otherwise CORE engineering INDUSTRIES that would have employed them to drive growth in the economy. Thus, with one stone called - STUDENT LOAN, you hit both the eyes of the bird (economy/country) and make it blind ! The opportunity cost of employing the best minds in the country away from building great companies and pushing them to become bean counters and build ever more complicated financial tools, i.e. various permutations and combinations of futures, forwards, options, swaps and other derivatives and selling them across various markets to save pennies for their money hungry masters! is extremely huge.
8. The PARASITE sectors forget that they can only suck the blood of the economy which has "GROWTH" - Deprived of the great minds that drive growth, the economy starts to falter, but attenuating this wound are the very great minds, which have now become parasites and started searching all over the economy for ways to suck the LAST BLOOD from it. Eventually the economy become strained by a tug of war between these two factors, of no growth coupled with parasites drawing blood - eventually leading to a complete collapse i.e. the ECONOMIC CRISIS OF 2008
9. Which then release these great minds from the clutches of the failed PARASITE companies, and lets' them choose their real professions. i.e. engineering and driving real growth in the economy.
This is the vicious loop of TOP GRADUATES GOING TO WALL STREET AND NOT TO MAIN STREET OR THE SILICON VALLEY
The author captured this in a beautiful way! That is why I love this book, so much.
October 5, 2013
This was an excellent book of explaining how our modern world is perishing with ways to become rich, as computers and programming are taking our jobs. It starts off explaining the life of Petterfy who was ahead of his time with knowing computers and programming before it was known by only the biggest businesses in the sixties. It wasn't till later that he showed the stock market that you did not have to be there to control it. The book continued with explaining other cool examples. Beatles Algorithm: Person could tell from first few cords if song was written by John or Paul. Online dating algorithm explains the real odds is once the relationship starts, not how you meet or what you have in common. Hammerbacher was last character mentioned, went to school as an English major and changed to Math at Harvard, needed to be stimulated with the top information as he was hired by sucker berg during early developments of facebook, but got bored. He even talks about baseball and its algoritms, but I can leave that to you to read. Great read. Anything is better than Infinite Jest and talking about canadians, bostonians, and tennis all day.
February 19, 2015
Really thought-provoking book about how mathematical algorithms, coupled with any given current technology at a time in history, has led to massive efficiencies and gains - starting with the algorithm's pioneer(s) and eventually spreading to everyone. The key areas the author focuses on: Wall Street and Finance, Hollywood, the music industry, customer service call centers, and of course social media. The author also devotes a small chunk of the book to giving credit to key mathematicians throughout history who have contributed either directly to the study of algorithms or indirectly by way of key mathematical concepts/advancements.
Although the material is hardly "light reading", the author does a very good job of conveying heavy mathematical and technological concepts through examples, and also by way of leaving out unnecessary, confusing details that only small groups of people would even begin to understand.
Although the material is hardly "light reading", the author does a very good job of conveying heavy mathematical and technological concepts through examples, and also by way of leaving out unnecessary, confusing details that only small groups of people would even begin to understand.
June 1, 2014
This is a much better book than I had originally expected it would be. Although it is not technical at all, the Author did manage to present the brief history behind algorithms and its various applications in our daily life in an engaging manner. I really liked parts of the book where Author mentions how Algorithms have come to play an important role for Wall Street and people who have worked for them. There are lot of interesting people mentioned in the book - Thomas Peterffy, Nathan Mayer Rothschild, Vivek Wadhwa, Andrew McAfee with lot of other interesting stories.
Perhaps the major drawback of the book as has been pointed here by multiple reviewers is the lack of in-depth analysis of various problems for which we depend on Algorithms now. Other than that, I think this is a good one time read.
Perhaps the major drawback of the book as has been pointed here by multiple reviewers is the lack of in-depth analysis of various problems for which we depend on Algorithms now. Other than that, I think this is a good one time read.
September 30, 2020
I liked it. I was expecting more details over job loss overall; but I enjoyed its focus on financial sector. Some of the best parts in my opinion was around Wall Street directly, how the programming started transforming finance industry (and the really early days was interesting to read). There are take aways as well but this isn’t really a future-telling book, it basically points at what has been and what is. Very briefly touch bases with what will be.
It was also nice to read about programmers who quit their jobs in banks, investment companies to get something in the valley.
It was also nice to read about programmers who quit their jobs in banks, investment companies to get something in the valley.
August 5, 2022
Steiner shares many stories of early innovators that used computers and algorithms before most people even believed computers would make a difference. Many of the innovators turned out to be computer 'hackers' alongside their current profession or knew how to bring hackers in to their companies. Ultimately, Steiner suggests that possibly the most useful skill to have now and in the future is the ability to write computer programs and design algorithms.
October 30, 2014
The author notes how Wall Street brought algorithms into the mainstream, how when Wall Street crashed that other fields had a sudden influx of quantitative talent, and how algorithms will soon take over everything. Put another way, many lovely anecdotes and much good information, but the history is all quite recent and somehow connected to Wall Street.
September 9, 2014
Automate this is an insight in how much algorithms influence your life and how they've gotten there.
I read the book because I got interested in algorithms through several wall street books, where those books focus on recent events (2008 till present), "Automate This" shows you the major players in its history and shows areas where they're being used which I wasn't aware.
I read the book because I got interested in algorithms through several wall street books, where those books focus on recent events (2008 till present), "Automate This" shows you the major players in its history and shows areas where they're being used which I wasn't aware.
October 25, 2012
A lot of motherhood and apple pie for anyone who follows the state of the art in computer learning and decision making. Lot's of great anecdotes and history, though.
October 31, 2012
Just received my pre-order :)
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