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The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies
In recent years, Google’s autonomous cars have logged thousands of miles on American highways and IBM’s Watson trounced the best human Jeopardy! players. Digital technologies—with hardware, software, and networks at their core—will in the near future diagnose diseases more accurately than doctors can, apply enormous data sets to transform retailing, and accomplish many tasks once considered uniquely human.
In The Second Machine Age MIT’s Erik Brynjolfsson and Andrew McAfee—two thinkers at the forefront of their field—reveal the forces driving the reinvention of our lives and our economy. As the full impact of digital technologies is felt, we will realize immense bounty in the form of dazzling personal technology, advanced infrastructure, and near-boundless access to the cultural items that enrich our lives.
Amid this bounty will also be wrenching change. Professions of all kinds—from lawyers to truck drivers—will be forever upended. Companies will be forced to transform or die. Recent economic indicators reflect this shift: fewer people are working, and wages are falling even as productivity and profits soar.
Drawing on years of research and up-to-the-minute trends, Brynjolfsson and McAfee identify the best strategies for survival and offer a new path to prosperity. These include revamping education so that it prepares people for the next economy instead of the last one, designing new collaborations that pair brute processing power with human ingenuity, and embracing policies that make sense in a radically transformed landscape.
A fundamentally optimistic book, The Second Machine Age alters how we think about issues of technological, societal, and economic progress.
In The Second Machine Age MIT’s Erik Brynjolfsson and Andrew McAfee—two thinkers at the forefront of their field—reveal the forces driving the reinvention of our lives and our economy. As the full impact of digital technologies is felt, we will realize immense bounty in the form of dazzling personal technology, advanced infrastructure, and near-boundless access to the cultural items that enrich our lives.
Amid this bounty will also be wrenching change. Professions of all kinds—from lawyers to truck drivers—will be forever upended. Companies will be forced to transform or die. Recent economic indicators reflect this shift: fewer people are working, and wages are falling even as productivity and profits soar.
Drawing on years of research and up-to-the-minute trends, Brynjolfsson and McAfee identify the best strategies for survival and offer a new path to prosperity. These include revamping education so that it prepares people for the next economy instead of the last one, designing new collaborations that pair brute processing power with human ingenuity, and embracing policies that make sense in a radically transformed landscape.
A fundamentally optimistic book, The Second Machine Age alters how we think about issues of technological, societal, and economic progress.
336 pages, Paperback
First published January 20, 2014
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April 5, 2014
The first part of this book reviews the incredible boom in technologies that are driving much of our economy. After that, the remainder of the book is about "bounty and spread". Bounty is the increased level of prosperity that some--but not all--of the population enjoys, as productivity increases. Spread is the growth of inequality, as much of the increased prosperity goes to the top economic levels, and little gets distributed to the lower economic levels. Thus, there ia a growing "spread" of income levels, what we normally would call "inequality".
The authors show that real, inflation-adjusted wages have grown since 1963 for people who have graduated from college or graduate school. High school graduates have not had real wage increases, and high school dropouts have had wage decreases. The authors note that some increases in "prosperity" cannot be measured; who in 1963 had a cell phone, a tablet computer, or cable TV? These consumer items were not available at any prices, and Moore's law has allowed these electronic inventions advance spectacularly in power in recent decades. However, these consumer items are not fully indicative of prosperity, since real estate, food, and transportation have not kept up with Moore's law. These are necessities, not luxuries, and thus the overall prosperity of most people has not increased with time.
The authors conclude with a set of policies that would help increase the prosperity of even the lower-level economic class; overhaul the education system, encourage entrepreneurship, encourage better match-ups between skills and jobs, increase support for science, upgrade infrastructure, reform patent law and reform taxes.
This is a well-written, basic-level book dealing with economics. It's interesting, but the recommendations a bit bland. There is little discussion about how to surmount the political hurdles. There is not much here that isn't also discussed elsewhere.
The authors show that real, inflation-adjusted wages have grown since 1963 for people who have graduated from college or graduate school. High school graduates have not had real wage increases, and high school dropouts have had wage decreases. The authors note that some increases in "prosperity" cannot be measured; who in 1963 had a cell phone, a tablet computer, or cable TV? These consumer items were not available at any prices, and Moore's law has allowed these electronic inventions advance spectacularly in power in recent decades. However, these consumer items are not fully indicative of prosperity, since real estate, food, and transportation have not kept up with Moore's law. These are necessities, not luxuries, and thus the overall prosperity of most people has not increased with time.
The authors conclude with a set of policies that would help increase the prosperity of even the lower-level economic class; overhaul the education system, encourage entrepreneurship, encourage better match-ups between skills and jobs, increase support for science, upgrade infrastructure, reform patent law and reform taxes.
This is a well-written, basic-level book dealing with economics. It's interesting, but the recommendations a bit bland. There is little discussion about how to surmount the political hurdles. There is not much here that isn't also discussed elsewhere.
May 7, 2018
I’m going to do a more detailed review of another book by these two authors called ‘Race Against the Machine’, which, if you were interested in a quick version of this book, that is the book to read. And this review isn’t really going to cover all of the themes in this book either – as I’m going to try to do that in the other review. What I want to talk about here are some of the ideas the authors have on GDP and how this is being impacted by technology.
GDP has long been a problematic concept. The problem is that so many things that are completely necessary for the functioning of society simply aren’t counted in the gross domestic product – not least, and ironically enough, domestic labour itself. This has generally meant that feminists in particular have been critical of how this is calculated as women’s work overwhelmingly isn’t counted and it often isn’t clear how society would continue to function without it. And as feminists rightly say, what isn’t counted generally ‘doesn’t count’.
The point the authors makes is that a lot of the value that comes from products in the digital economy similarly are worth much more to us than we pay. In fact, in part they argue that the value of digital products is often reduced to the marginal price of those goods and services – and, since digital means being able to reproduce something at effectively zero additional cost, this often means that the price of any digital product goes through a process where it has an infinite price right up until it had zero price. The example given here (I think, I’ve read three books by these guys in quick succession, so I need to guess which book they say particular stuff in now) is films. There was a time in living memory (for me at least) where to see a film involved needing to go to the cinema or to wait until it was shown on television. Then there came a time when you could eventually hire films from your local video library – if they were available. Buying them was expensive and only available a long time after they were released. What wasn’t available, at any price, was to be at home and to think, ‘God, I would like to watch blah’ and to then to just watch that film. Today, that little trick is available and at very little cost from companies that give you access to lots and lots of films for a fixed fee per month.
The other example they give is an encyclopedia, and this one is really interesting – there was a time when buying an encyclopedia was a way of presenting yourself as a particular type of person – one keen to be seen as knowledgeable about the whole range of human intellectual endeavour. People would effectively borrow lots of money so as to possess an encyclopedia. I was in a second-hand bookshop over the weekend and there was an encyclopedia on sale there for $10. Really, I can’t imagine someone buying a hardcopy encyclopedia today. The problem is that knowledge is accumulating so quickly and changing so fast it isn’t clear which pages of such a multi-volume book will be (or already are) no longer current (or even accurate). The internet has effectively killed off the encyclopedia business. But not just in sales, also increasingly in the writing of entries too. People complain about the inaccuracy of Wikipedia, but then there was that Nature article from some time ago that compared it to Britannica and found it to be even more accurate and covered more stuff.
I’m making two points here, and neither one all that clearly. The first is that encyclopedias used to cost a fortune, now they cost basically nothing at all. And even so, they are likely to be much more accurate and up to date than the old print versions ever were. To buy a completely up to date print version of an encyclopedia was always impossible, at any cost. That is, up until the internet the cost of such a thing was effectively infinity. Now it is effectively zero.
But the other bit of this that is important to keep in mind is that buying encyclopedias used to contribute to the nation’s GDP and was counted as such. Today, Wikipedia doesn’t do that in anything like the same way. The authors of the articles are not paid for their labour, no one literally buys Wikipedia, and most likely wouldn’t do so even if the option was available. And so, none of this use of the encyclopedia is counted as part of GDP either. And yet, access to Wikipedia is, I should think, much more valuable than what we had previously been able to buy – and so the notion of ‘value’ that exists in the digital world doesn’t seem to match the idea of ‘value’ that is captured in the calculation of the GDP.
The authors suggest various ways that this might be overcome, or at least accounted for – but I’ve a feeling all of this might prove about as difficult as feminism has found it to change GDP to take into account unpaid female work.
That said, these authors are remarkably positive about the changes occurring in the economy and the likelihood that these will prove beneficial. They repeatedly say that these changes won’t impact on capitalism in ways that might undermine it as ‘the best of a bad lot’ of ways of organising an economy. It isn’t totally clear to me what they base this confidence on – as they say repeatedly here, we are experiencing exponential change in relation to the digital revolution, which is merely pretty much a direct restatement of Moore’s Law that computing capacity doubles every 18 months or so. They also say that it is possible we have ‘entered the second half of the chessboard’ – an allusion to the myth that the person who invented chess wanted to be paid for it by a grain of rice on the first square of the chessboard, then 2 on the second square, 4 on the next – soon enough this will bankrupt the society of the ruler who wanted to reward the inventor. But this is mostly true on the second half of the board.
If change is going to accelerate it isn’t all that clear which jobs are about to disappear or even if any jobs are going to be left at all – the authors make the point that soon before Google started displaying their driverless car everyone thought such cars were impossible and that occupations like ‘truck driver’ were safe from technology. To then to say capitalism will remain the obvious means of organising an economy seems anything but clear to me. With growing inequality (something else they document in this book) it isn’t clear how large sections of society will be able to meet the demands of even going on living, never mind living the kinds of lives the future seems to promise.
In part, this book reminded me of ‘Drive’ by Dan Pink – mostly because it seems to imply that the jobs people ought to do in the future should be the sorts of things that allow people to self-actualise. The desire for such work is pretty clear from the fact of Wikipedia, for instance (or here on Goodreads, even) where people spend lots of time contributing to the common good, and expecting nothing in return. But expecting and receiving nothing in return isn’t the most obvious way to run an economy – even though when you look at this site, or Facebook, or Google, that is effectively what happens. These companies do not produce any content of their own, in effect they are profiting off the unpaid labour of others – now, I’m not suggesting people should get paid for providing that content, but on the other hand, if work disappears (that is, we all end up out of a day job), it isn’t clear to me how people will be able to continue to provide free content for remarkably wealthy corporations while they have no other source of income. It also isn’t clear to me how that content can continue to not be counted as GDP – I presume you come to this site, for instance, for the content provided on it, rather than for a chance to see the ads Amazon provides (even though those are counted as part of GDP).
I really don’t know nearly enough about economics, but that said, it isn’t at all clear to me that the digital future of capitalism – a future based on information and where the main cost of providing that information and information systems is borne up front and then the marginal cost of each additional and perfect copy is effectively zero – how that vision of capitalism will be able to remain the same as that of the previous one where goods were produced, could only be used once by one purchaser before needing to be reproduced and where consumers often had to settle for second or third best. You see, in the digital world ‘availability’ stops being a determiner – the fact of you buying the best word processor software does not stop me from buying it too. That then means that ‘the best take the most’, which again plays havoc with notions of competition, presumably another key feature of classical capitalism.
I don’t know the answer to any of these questions, by the way, I am just not all that confident that the answer will automatically be ‘more of the same’.
This reminds me of Americas and their odd relationship with their constitution. It isn’t clear to me why something that was written so long ago should be impossible to change or to even question today. The world has moved on a bit since the eighteenth century. I can’t help feeling that deciding beforehand that no change in the economy is every going to be enough to make capitalism a problem might, itself, be a problem.
GDP has long been a problematic concept. The problem is that so many things that are completely necessary for the functioning of society simply aren’t counted in the gross domestic product – not least, and ironically enough, domestic labour itself. This has generally meant that feminists in particular have been critical of how this is calculated as women’s work overwhelmingly isn’t counted and it often isn’t clear how society would continue to function without it. And as feminists rightly say, what isn’t counted generally ‘doesn’t count’.
The point the authors makes is that a lot of the value that comes from products in the digital economy similarly are worth much more to us than we pay. In fact, in part they argue that the value of digital products is often reduced to the marginal price of those goods and services – and, since digital means being able to reproduce something at effectively zero additional cost, this often means that the price of any digital product goes through a process where it has an infinite price right up until it had zero price. The example given here (I think, I’ve read three books by these guys in quick succession, so I need to guess which book they say particular stuff in now) is films. There was a time in living memory (for me at least) where to see a film involved needing to go to the cinema or to wait until it was shown on television. Then there came a time when you could eventually hire films from your local video library – if they were available. Buying them was expensive and only available a long time after they were released. What wasn’t available, at any price, was to be at home and to think, ‘God, I would like to watch blah’ and to then to just watch that film. Today, that little trick is available and at very little cost from companies that give you access to lots and lots of films for a fixed fee per month.
The other example they give is an encyclopedia, and this one is really interesting – there was a time when buying an encyclopedia was a way of presenting yourself as a particular type of person – one keen to be seen as knowledgeable about the whole range of human intellectual endeavour. People would effectively borrow lots of money so as to possess an encyclopedia. I was in a second-hand bookshop over the weekend and there was an encyclopedia on sale there for $10. Really, I can’t imagine someone buying a hardcopy encyclopedia today. The problem is that knowledge is accumulating so quickly and changing so fast it isn’t clear which pages of such a multi-volume book will be (or already are) no longer current (or even accurate). The internet has effectively killed off the encyclopedia business. But not just in sales, also increasingly in the writing of entries too. People complain about the inaccuracy of Wikipedia, but then there was that Nature article from some time ago that compared it to Britannica and found it to be even more accurate and covered more stuff.
I’m making two points here, and neither one all that clearly. The first is that encyclopedias used to cost a fortune, now they cost basically nothing at all. And even so, they are likely to be much more accurate and up to date than the old print versions ever were. To buy a completely up to date print version of an encyclopedia was always impossible, at any cost. That is, up until the internet the cost of such a thing was effectively infinity. Now it is effectively zero.
But the other bit of this that is important to keep in mind is that buying encyclopedias used to contribute to the nation’s GDP and was counted as such. Today, Wikipedia doesn’t do that in anything like the same way. The authors of the articles are not paid for their labour, no one literally buys Wikipedia, and most likely wouldn’t do so even if the option was available. And so, none of this use of the encyclopedia is counted as part of GDP either. And yet, access to Wikipedia is, I should think, much more valuable than what we had previously been able to buy – and so the notion of ‘value’ that exists in the digital world doesn’t seem to match the idea of ‘value’ that is captured in the calculation of the GDP.
The authors suggest various ways that this might be overcome, or at least accounted for – but I’ve a feeling all of this might prove about as difficult as feminism has found it to change GDP to take into account unpaid female work.
That said, these authors are remarkably positive about the changes occurring in the economy and the likelihood that these will prove beneficial. They repeatedly say that these changes won’t impact on capitalism in ways that might undermine it as ‘the best of a bad lot’ of ways of organising an economy. It isn’t totally clear to me what they base this confidence on – as they say repeatedly here, we are experiencing exponential change in relation to the digital revolution, which is merely pretty much a direct restatement of Moore’s Law that computing capacity doubles every 18 months or so. They also say that it is possible we have ‘entered the second half of the chessboard’ – an allusion to the myth that the person who invented chess wanted to be paid for it by a grain of rice on the first square of the chessboard, then 2 on the second square, 4 on the next – soon enough this will bankrupt the society of the ruler who wanted to reward the inventor. But this is mostly true on the second half of the board.
If change is going to accelerate it isn’t all that clear which jobs are about to disappear or even if any jobs are going to be left at all – the authors make the point that soon before Google started displaying their driverless car everyone thought such cars were impossible and that occupations like ‘truck driver’ were safe from technology. To then to say capitalism will remain the obvious means of organising an economy seems anything but clear to me. With growing inequality (something else they document in this book) it isn’t clear how large sections of society will be able to meet the demands of even going on living, never mind living the kinds of lives the future seems to promise.
In part, this book reminded me of ‘Drive’ by Dan Pink – mostly because it seems to imply that the jobs people ought to do in the future should be the sorts of things that allow people to self-actualise. The desire for such work is pretty clear from the fact of Wikipedia, for instance (or here on Goodreads, even) where people spend lots of time contributing to the common good, and expecting nothing in return. But expecting and receiving nothing in return isn’t the most obvious way to run an economy – even though when you look at this site, or Facebook, or Google, that is effectively what happens. These companies do not produce any content of their own, in effect they are profiting off the unpaid labour of others – now, I’m not suggesting people should get paid for providing that content, but on the other hand, if work disappears (that is, we all end up out of a day job), it isn’t clear to me how people will be able to continue to provide free content for remarkably wealthy corporations while they have no other source of income. It also isn’t clear to me how that content can continue to not be counted as GDP – I presume you come to this site, for instance, for the content provided on it, rather than for a chance to see the ads Amazon provides (even though those are counted as part of GDP).
I really don’t know nearly enough about economics, but that said, it isn’t at all clear to me that the digital future of capitalism – a future based on information and where the main cost of providing that information and information systems is borne up front and then the marginal cost of each additional and perfect copy is effectively zero – how that vision of capitalism will be able to remain the same as that of the previous one where goods were produced, could only be used once by one purchaser before needing to be reproduced and where consumers often had to settle for second or third best. You see, in the digital world ‘availability’ stops being a determiner – the fact of you buying the best word processor software does not stop me from buying it too. That then means that ‘the best take the most’, which again plays havoc with notions of competition, presumably another key feature of classical capitalism.
I don’t know the answer to any of these questions, by the way, I am just not all that confident that the answer will automatically be ‘more of the same’.
This reminds me of Americas and their odd relationship with their constitution. It isn’t clear to me why something that was written so long ago should be impossible to change or to even question today. The world has moved on a bit since the eighteenth century. I can’t help feeling that deciding beforehand that no change in the economy is every going to be enough to make capitalism a problem might, itself, be a problem.
September 13, 2016
This book's mission is fairly straightforward: It seeks to convince the reader, by analyzing various economic data, that today's technology is something that is far more marvelous than most of us realize. The argument is that we're in the middle of a second era of unprecedented innovation, much like the first machine age, when population exploded, as did quality of life, earnings, and a number of other life metrics.
Though its mission is vast, the actual pieces of the book are digestible. The opening chapter is about how close we are to a driverless car -- something that even a few years ago seemed impossible. There's a chapter on measuring the cost of the digital economy, most of which is "free," even though it offers us incredible value (for example, I use this website to track my reading and review books -- something I find incredibly valuable, but it comes to me for free). And a look at what's really behind the so-called technology skills mismatch.
Much of these chapters won't be surprising to economists, or even regular listeners of NPR's Planet Money podcast, but it really does combine all of these threads into one big narrative about the meaning of technology in our lives today. Though they aren't complete optimists: they do point out that there's a real problem with inequality in today's advanced world, but they do make the case that overall we're much better off with technology -- and that those advances are happening even faster than we can really think logically about.
Once we understand that, it becomes less absurd to contemplate how our economy will change with a fully autonomous android workforce. It's frighteningly within reach.
Though its mission is vast, the actual pieces of the book are digestible. The opening chapter is about how close we are to a driverless car -- something that even a few years ago seemed impossible. There's a chapter on measuring the cost of the digital economy, most of which is "free," even though it offers us incredible value (for example, I use this website to track my reading and review books -- something I find incredibly valuable, but it comes to me for free). And a look at what's really behind the so-called technology skills mismatch.
Much of these chapters won't be surprising to economists, or even regular listeners of NPR's Planet Money podcast, but it really does combine all of these threads into one big narrative about the meaning of technology in our lives today. Though they aren't complete optimists: they do point out that there's a real problem with inequality in today's advanced world, but they do make the case that overall we're much better off with technology -- and that those advances are happening even faster than we can really think logically about.
Once we understand that, it becomes less absurd to contemplate how our economy will change with a fully autonomous android workforce. It's frighteningly within reach.
June 10, 2018
The first half & even beyond didn't hold much new to me, but it was nicely put together & leads into their premise that times are changing more rapidly than any other time in history. As the book progressed, the authors delved more into economics & what the machine age means for people in general. I don't know much about economics, so I found their views really interesting, especially since they often balanced opposing viewpoints before saying which side they preferred. Sometimes neither, but a mix.
They pulled in some pretty surprising statistics especially about the widening divide between capital & labor, the 1% & the rest of us - bounty & spread. I was surprised they didn't include corporations as entities, beyond pointing out some of the most egregious flaws in copyright briefly.
They also addressed many of the benefits we'll reap. I'm fairly well acquainted with computers, but even I was surprised by the progress we've made & how it has overturned things.
We're striving toward an age where machines do all the work & humans reap the bounty. It's long been a dream of our race. The word 'robot' originated in R.U.R. a play with just that premise. The authors take that seriously, but discount the idea of a Terminator-like scenario & focus more on the current changes.
They also quote Voltaire's wonderful point that Work saves us from three great evils: boredom, vice and need. For all our love of free time, without work we tend to get bored, lose our sense of worth, & fall prey to vices. They have statistics on impoverished areas & how they break down when too many are unemployed. Poor workers can be a pillar of society, but unemployed are not. They didn't mention criminally employed, though.
Machines are taking many of repetitive jobs. As expensive as they are, they're often far cheaper than a human. In one example, the robot cost $4/hour, a wage no person in the U.S. will work for. Education & creativity are super important now since machines can do many things better. Great example of computers beating chess masters, but even a mediocre human & computer can beat the best computer. When we work with them, the results are amazing. They stuck firmly to the prosaic & never even mentioned cyborgs, though. We need to change our education system. Teaching to the test isn't going to cut it.
This was written in 2013 & is dated in some ways. They discuss automated cars a lot which have come a long way since then. That helps make their point, that we're in another age of unprecedented innovation akin to the Industrial Revolution, even better than all their fine examples.
They come up with some general ideas on solutions to get through this time of flux which make a lot of sense. I hope our leaders read this. Highly recommended.
Table of Contents:
The big stories
The skills of the new machines : technology races ahead
Moore's law and the second half of the chessboard
The digitization of just about everything
Innovation : declining or recombining?
Artificial and human intelligence in the second machine age
Computing bounty
Beyond GDP
The spread
The biggest winners : stars and superstars
Implications of the bounty and the spread
Learning to race with machines : recommendations for individuals
Policy recommendations
Long-term recommendations
Technology and the future (which is very different from "technology is the future").
They pulled in some pretty surprising statistics especially about the widening divide between capital & labor, the 1% & the rest of us - bounty & spread. I was surprised they didn't include corporations as entities, beyond pointing out some of the most egregious flaws in copyright briefly.
They also addressed many of the benefits we'll reap. I'm fairly well acquainted with computers, but even I was surprised by the progress we've made & how it has overturned things.
We're striving toward an age where machines do all the work & humans reap the bounty. It's long been a dream of our race. The word 'robot' originated in R.U.R. a play with just that premise. The authors take that seriously, but discount the idea of a Terminator-like scenario & focus more on the current changes.
They also quote Voltaire's wonderful point that Work saves us from three great evils: boredom, vice and need. For all our love of free time, without work we tend to get bored, lose our sense of worth, & fall prey to vices. They have statistics on impoverished areas & how they break down when too many are unemployed. Poor workers can be a pillar of society, but unemployed are not. They didn't mention criminally employed, though.
Machines are taking many of repetitive jobs. As expensive as they are, they're often far cheaper than a human. In one example, the robot cost $4/hour, a wage no person in the U.S. will work for. Education & creativity are super important now since machines can do many things better. Great example of computers beating chess masters, but even a mediocre human & computer can beat the best computer. When we work with them, the results are amazing. They stuck firmly to the prosaic & never even mentioned cyborgs, though. We need to change our education system. Teaching to the test isn't going to cut it.
This was written in 2013 & is dated in some ways. They discuss automated cars a lot which have come a long way since then. That helps make their point, that we're in another age of unprecedented innovation akin to the Industrial Revolution, even better than all their fine examples.
They come up with some general ideas on solutions to get through this time of flux which make a lot of sense. I hope our leaders read this. Highly recommended.
Table of Contents:
The big stories
The skills of the new machines : technology races ahead
Moore's law and the second half of the chessboard
The digitization of just about everything
Innovation : declining or recombining?
Artificial and human intelligence in the second machine age
Computing bounty
Beyond GDP
The spread
The biggest winners : stars and superstars
Implications of the bounty and the spread
Learning to race with machines : recommendations for individuals
Policy recommendations
Long-term recommendations
Technology and the future (which is very different from "technology is the future").
January 30, 2015
I wrote an essay published in Public Books reviewing The Second Machine Age for those interested in a more extensive analysis: http://www.publicbooks.org/nonfiction...
When the robots take our jobs, what color is your parachute? In their book The Second Machine Age, MIT researchers Brynjolfsson and McAfee point to machines that are getting better at pattern recognition and real time processing of complex situations. Machines can now (sometimes) drive cars, (sometimes) beat chessmasters, and (sometimes) win at Jeopardy. Humans need to figure out what their competitive advantage is and the line keeps moving. Why should a manager hire a living, learning person when they could have a robot that works quickly, quietly, and without breaks, demands, or opinions? Even FoxConn, the x-million worker strong factory that produces iPhones, is replacing some of its workers with robots. For B and M, what robots are clean replacements for humans – they simply produce the same things but more efficiently.
It is the abstraction of The Second Machine Age that makes my head spin. The book zooms in and out among evidence to support its basic arguments: that digital technology unlocks innovation, that innovation unleashes labor automation as well as digital information abundance, and that these two trends explaining growing income inequality in the United States. To support these arguments, the authors offer anecdotes of digital wonders, predictions of that the singularity (exponential densities of processing power and networking) is near, and findings from economics research usually contextualized with markers of institutional prestige rather than a critical appraisal of assumptions. Early on, they ask that readers just trust them: “things get weird…most of us have trouble keeping up” (p.47). The second machine age is presented as a fait accompli; the march of artificial intelligence will only speed up. This rhetorical form does not invite workers, scholars, citizens, refugees, or others anywhere near the debate. Rather, it offers a guided tour of a future already largely explored and decided at Google and MIT but without detailed attention to how existing digital systems have already transformed the insides of most workplaces.
When the robots take our jobs, what color is your parachute? In their book The Second Machine Age, MIT researchers Brynjolfsson and McAfee point to machines that are getting better at pattern recognition and real time processing of complex situations. Machines can now (sometimes) drive cars, (sometimes) beat chessmasters, and (sometimes) win at Jeopardy. Humans need to figure out what their competitive advantage is and the line keeps moving. Why should a manager hire a living, learning person when they could have a robot that works quickly, quietly, and without breaks, demands, or opinions? Even FoxConn, the x-million worker strong factory that produces iPhones, is replacing some of its workers with robots. For B and M, what robots are clean replacements for humans – they simply produce the same things but more efficiently.
It is the abstraction of The Second Machine Age that makes my head spin. The book zooms in and out among evidence to support its basic arguments: that digital technology unlocks innovation, that innovation unleashes labor automation as well as digital information abundance, and that these two trends explaining growing income inequality in the United States. To support these arguments, the authors offer anecdotes of digital wonders, predictions of that the singularity (exponential densities of processing power and networking) is near, and findings from economics research usually contextualized with markers of institutional prestige rather than a critical appraisal of assumptions. Early on, they ask that readers just trust them: “things get weird…most of us have trouble keeping up” (p.47). The second machine age is presented as a fait accompli; the march of artificial intelligence will only speed up. This rhetorical form does not invite workers, scholars, citizens, refugees, or others anywhere near the debate. Rather, it offers a guided tour of a future already largely explored and decided at Google and MIT but without detailed attention to how existing digital systems have already transformed the insides of most workplaces.
October 14, 2014
Solid and entertaining overview of high tech robotics, bit of ai and very interesting examples. Not spectacularly innovative maybe, but I founf myself using many examples in conversations with friends.
December 21, 2018
Well-researched and very interesting--it's a nice counterpoint to Robert Gordon and other techno-pessimists. The most striking insight was their defense of Moore's law and their case for measuring growth by hours saved . The more researchers proposing alternatives to GDP, the better.
However, I don't think I agree with their optimism in the end of the book. They lay out the case well for inequality, but they seem convinced that a UBI can fix it (in fact, I have yet to read a techno-utopian treatise that does not end with UBI). I think we're going to need much more than that. Still, this book is the best explanation of the trends toward inequality that robotics and AI will exacerbate
However, I don't think I agree with their optimism in the end of the book. They lay out the case well for inequality, but they seem convinced that a UBI can fix it (in fact, I have yet to read a techno-utopian treatise that does not end with UBI). I think we're going to need much more than that. Still, this book is the best explanation of the trends toward inequality that robotics and AI will exacerbate
May 3, 2015
Excelente livro. Descreve muito bem a situação de mídia e emprego corrente, mudanças tecnológicas e de ensino, bem como perspectivas futuras. Recomendo a qualquer um que trabalhe com algo que esteja mudando com tecnologias recentes. E professores.
February 12, 2014
With the proper amounts of bombast and self-promotion, prophecy can be an extremely lucrative field. A lot of books about the future of American economic growth fall into either Stagnation or Singularity camps, trying to show that America's future potential is dismal due to the misguided economic philosophies of the ideological villains of your choice (see the New York Times or the Wall Street Journal's op-ed pages) or simple exhaustion of easy ways to generate sustained growth (see Robert Gordon or Tyler Cowen), or is actually spectacular due to the magical properties of game-changing innovation X, Y, or Z (see Ray Kurzweil). In contrast, Brynjolfsson and McAfee's earlier book Race Against the Machine was a sober, data-driven overview of what they thought the likely effects of increased automation on the labor force would be, with interesting case studies and plenty of good data. Its major flaw, in my view, was an ending solutions chapter that spent more time on perennial Silicon Valley wishlist items like reforming the patent system or allowing for more H1-B visas than on engaging with the political process. While those wishlist items haven't gone away, this sequel not only offers a greatly expanded take on their earlier analysis of technological progress, but a broader and more carefully thought-out list of possible solutions to problems that automation will cause for many workers even as the economy as a whole benefits greatly.
The first section of the book is devoted to the three characteristics of modern technological progress: exponential growth, large amounts of digitized information, and constant remixing of old ideas into new ones. From Google's self-driving cars, to Apple's Siri voice recognition system, to IBM's GeoFluent translation software, to IBM's Jeopardy!-beater Watson, and more, it's obvious that while artificial intelligence might have had limited progress for a long time, it's come very far, and further progress seems like it will come much more rapidly. This is the "second half of the chessboard" metaphor from their first book, taken from an Indian story about the inventor of chess, who asked for a seemingly-simple reward for his game from the emperor: one grain of rice on the first square of a chessboard, two on the second, four on the third, eight on the fourth, and so on. The emperor agreed, not realizing that while the amount of rice he'd have to hand out would be fairly manageable for the first half of the chessboard, by the second half he would be in real trouble. A classic example of this is Moore's Law, but in addition to semiconductor density, other measures like energy efficiency, hard drive cost per MB, and supercomputer speed also follow exponential growth patterns.
This allows for truly immense amounts of data to be processed, which enables all sorts of useful stuff that wasn't possible before. An example is Waze, a now Google-owned company which, thanks to large amounts of real-time input from its rapidly growing userbase, shows you the best route around traffic and makes traffic forecasts obsolete. The combination of network effects, lots of data, and the near-zero cost of reproducing or transferring that data, not only ensures that data scientists/analysts looking for hidden insights will have plenty to do, it also means there are plenty of opportunities to go back to old ideas and do something new with them. While plenty of modern innovations seem easy to scoff at - with Waze, for example, surely an app that speeds up my commute by 5 minutes can't really compare to the invention of the internal combustion engine - scientific fields are expanding so quickly that there are plenty of opportunities for many people to make small improvements that eventually add up to large rises in our standard of living.
The second section of the book explores bounty, their word for the value of goods and services this new Revolution has given us, and spread, their term for the distribution of that bounty. For a long time there's been a controversy over the seemingly-negligible part the IT revolution has played in the official measurement of official productivity and other economic statistics - individuals and firms have spent a lot of money on hardware and software, yet that investment, as measured by GDP growth or other measures of output growth per unit of input, has been unimpressive. Brynjolfsson and McAfee are firmly in the camp that holds that technology has improved life, it's just that official measures don't capture that very accurately. They compare the adoption rates of electricity to IT and find interesting similarities in how long it's taken for each to start showing up in the numbers, and also quote the famous Robert F Kennedy line about GDP, that it "measures everything, in short, except that which makes life worthwhile." They list four types of intangibles that won't show up in national accounting statistics: intellectual property, organizational capital, user-generated content, and human capital, and note that all of these have been exploding recently. To take one example, Wikipedia has been a death sentence for traditional encyclopedia makers, yet it's a non-profit website. In conventional GDP statistics, it has destroyed millions, perhaps billions of dollars, and yet it's been an enormous boon to everyone who wants to look something up quickly. Email has been bad for the post office. Skype is bad for phone companies. Music publishers hated Napster. And so forth.
All this consumer surplus is great, but it has consequences for where profits flow. We all enjoy bounty to some degree, but it's not spread very evenly. They use an example from the field of photography:
"While digitization has obviously increased the quantity and convenience of photography, it has also profoundly changed the economics of photography production and distribution. A team of just fifteen people at Instagram created a simple app that over 130 million customers use to share some sixteen billion photos (and counting). Within fifteen months of its founding, the company was sold for over $1 billion to Facebook. In turn, Facebook itself reached one billion users in 2012. It had about 4,600 employees including barely 1,000 engineers.
Contrast these figures with pre-digital behemoth Kodak, which also helped customers share billions of photos. Kodak employed 145,300 people at one point, one-third of them in Rochester, New York, while indirectly employing thousands more via the extensive supply chain and retail distribution channels required by companies in the first machine age. Kodak made its founder, George Eastman, a rich man, but it also provided middle-class jobs for generations of people and created a substantial share of the wealth created in the city of Rochester after company’s founding in 1880. But 132 years later, a few months before Instagram was sold to Facebook, Kodak filed for bankruptcy."
In other words, rather than benefit large numbers of people in many communities through plentiful jobs, profits are flowing increasingly to a few people in a few places like Silicon Valley. Anyone who paid any attention to the 2012 Presidential election is familiar with the notion that median wages have been stagnant or declining for many groups for quite a while, and net wealth has taken a shocking decrease since the Recession in particular:
"Between 1983 and 2009, Americans became vastly wealthier overall as the total value of their assets increased. However, as noted by economists Ed Wolff and Sylvia Allegretto, the bottom 80 percent of the income distribution actually saw a net decrease in their wealth. Taken as a group, the top 20 percent got not 100 percent of the increase, but more than 100 percent. Their gains included not only the trillions of dollars of wealth newly created in the economy but also some additional wealth that was shifted in their direction from the bottom 80 percent. The distribution was also highly skewed even among relatively wealthy people. The top 5 percent got 80 percent of the nation's wealth increase; the top 1 percent got over half of that, and so on for ever-finer subdivisions of the wealth distribution. In an oft-cited example, by 2010 the six heirs of Sam Walton’s fortune, earned when he created Walmart, had more net wealth than the bottom 40 percent of the income distribution in America. In part, this reflects the fact that thirteen million families had a negative net worth."
In English, that means all those Occupy Wall Street slogans about the 99% are more correct than their detractors would like to believe, but the overall picture is (slightly) more complex than "the 1% are stealing everything". Even beyond the decoupling of wages and productivity, there's been a global fall in the labor share of GDP, meaning that wealth is flowing more to owners of capital. In many sectors we now have a superstar economy, where there's enormous demand for a few popular things at the expense of many less-popular things. This entails a shift from returns for absolute performance (meaning that performing at 90% of the level of the best gets you 90% of the return) to returns for relative performance (meaning that no one wants the tenth-best app in whatever field, so you get nothing). This can be partially counteracted by long tail-type economies, which make it possible for relative low-performers to scrape by, but they're not very lucrative because of the power of network effects and technological lock-in. Even if Windows Phone is on paper basically just as good as iOS or Android, no one cares, and though everyone derives some benefit from the ubiquity of smartphones, profits in the industry flow to very few firms, and within those firms, even fewer people.
This shift from normal/Gaussian distributions of wealth and power to 80-20/power-law distributions is profound; Brynjolfsson and McAfee cite Acemoglu and Robinson's work in Why Nations Fail on the relationship between political institutions and economic distributions, and how exclusive political systems that are set up for the convenience of a small elite not only don't grow very fast but are also terrible places to live for the masses. I would have liked to see them address Paul Krugman's points in The Conscience of a Liberal about how political movements can drive and encourage this re-peasantization process, though I can understand their desire to avoid seeming too strongly partisan or ideological. Tyler Cowen's recent Average Is Over was a good example of how to be too ideological in the wrong direction about these same concerns, arguing that this return to the Gilded Age will be much more pleasant than the original Gilded Age. Sure, large numbers of people will be permanently excluded from labor markets and won't be able to meaningfully participate in the political process, but all the cool new technology means that that won't be so bad, or at least not bad enough to get too upset about.
Unfortunately, Brynjolfsson and McAfee's take on the question of what happens when automation starts to put significant numbers of people permanently out of work is more pessimistic. Even though people have scoffed at this vision of technological unemployment for hundreds of years (see the history of the Luddites and the "lump of labor" fallacy), this time could be different. There are three possible mechanisms for destroying jobs in this way: inelastic demand for goods (this could actually be good, as people would be able to voluntarily choose to work less while still producing the same amount of output), too-rapid change (it might simply take too long to re-skill certain types of workers), and severe skill inequality (some people will just never be able to produce value greater than what a machine could do). This new permanent underclass will be subject to the sorts of social pathologies that got people transported to Australia in past eras, but options in the future will obviously be somewhat more limited. Ironically, the kinds of jobs easiest to automate are also the kinds easiest to offshore, so America might get a breather from offshoring and be able to watch and learn from what happens as large-scale automation in companies like Foxconn gets field-tested overseas before coming here. Of course, Freestyle chess, where humans and computers collaborate to accomplish goals, could be a model for the economy as a whole, but it seems more likely that many people will simply be automated out of a job and left to their own devices.
In the third section they have two groups of solutions, of which the first recapitulates much from Race Against the Machine. In the short-term:
1. Teach the children well
- Use MOOCs, which are both cheaper and provide more opportunities for data-driven feedback
- Raise teacher salaries in exchange for more accountability, coupled with longer school days and a longer school year
2. Restart startups
- Startups provide most new net jobs, but the rate of new startup formation is dropping quickly. "Regulations" might be to blame
3. Make more matches
- Do a better job of matching workers to prospective jobs to reduce frictional unemployment as much as possible
4. Support our scientists
- Reform intellectual property laws by lessening absurdly long copyright terms
- Offer more prizes for research goals, to bring in people who don't fit into the regular grant process mold
5. Upgrade infrastructure/human capital
- There's lots of externalities to improving our terrible infrastructure, even beyond arguments about Keynesian stimulus
- Welcome more high-skill immigrants who are currently going to other countries, and also reform the byzantine/broken immigration process
6. Tax wisely
- More Pigovian taxes that tax bad things, like congestion or pollution taxes
- Consider a land tax or a VAT to fund social programs instead of relying on labor taxes
- More taxes on being a superstar, like higher tax brackets
The second group is new, and to my mind more adequate to the scale of the issues raised previously in the book. In the long-term:
- Build on capitalism and unlimited technological progress without abandoning or attempting to fundamentally restrain either
- Consider a Universal Basic Income, to prevent Voltaire's social ills of "boredom, vice, and want"
- Alternatively, consider a Negative Income Tax like a greatly expanded EITC to encourage work
- Find better ways to use the strengths of humans and machines together, as in Amazon's Mechanical Turk
- Bring marginal people into the labor force via the peer economy, e.g. TaskRabbit, Airbnb, Lyft
- Encourage new ideas (a national mutual fund, designate some jobs "human-only", institute "made by people" labeling similar to that for organic foods, use massive federal hiring a la the Civilian Conservation Corps)
Unfortunately they don't offer much in the way of suggestions on how to move these ideas though Washington. Hey, they're nerds, not lobbyists! Well, any book that attempts to grapple with the consequences of something as world-changing as artificial intelligence on a large scale should certainly be able to offer some pointers on how to get the Republican Party to start offering real solutions to problems that don't boil down to tax cuts for the rich. This kind of naivete is unsurprising, yet still disappointing coming from such smart guys. The additional analysis in the first two sections and the broader range of solutions in the third means that this is a much more complete and useful book than its predecessor was, and while I certainly wouldn't say that this is the final word on the possibilities and pitfalls of large-scale automation, it's as good a starting point as you're likely to find for a while.
The first section of the book is devoted to the three characteristics of modern technological progress: exponential growth, large amounts of digitized information, and constant remixing of old ideas into new ones. From Google's self-driving cars, to Apple's Siri voice recognition system, to IBM's GeoFluent translation software, to IBM's Jeopardy!-beater Watson, and more, it's obvious that while artificial intelligence might have had limited progress for a long time, it's come very far, and further progress seems like it will come much more rapidly. This is the "second half of the chessboard" metaphor from their first book, taken from an Indian story about the inventor of chess, who asked for a seemingly-simple reward for his game from the emperor: one grain of rice on the first square of a chessboard, two on the second, four on the third, eight on the fourth, and so on. The emperor agreed, not realizing that while the amount of rice he'd have to hand out would be fairly manageable for the first half of the chessboard, by the second half he would be in real trouble. A classic example of this is Moore's Law, but in addition to semiconductor density, other measures like energy efficiency, hard drive cost per MB, and supercomputer speed also follow exponential growth patterns.
This allows for truly immense amounts of data to be processed, which enables all sorts of useful stuff that wasn't possible before. An example is Waze, a now Google-owned company which, thanks to large amounts of real-time input from its rapidly growing userbase, shows you the best route around traffic and makes traffic forecasts obsolete. The combination of network effects, lots of data, and the near-zero cost of reproducing or transferring that data, not only ensures that data scientists/analysts looking for hidden insights will have plenty to do, it also means there are plenty of opportunities to go back to old ideas and do something new with them. While plenty of modern innovations seem easy to scoff at - with Waze, for example, surely an app that speeds up my commute by 5 minutes can't really compare to the invention of the internal combustion engine - scientific fields are expanding so quickly that there are plenty of opportunities for many people to make small improvements that eventually add up to large rises in our standard of living.
The second section of the book explores bounty, their word for the value of goods and services this new Revolution has given us, and spread, their term for the distribution of that bounty. For a long time there's been a controversy over the seemingly-negligible part the IT revolution has played in the official measurement of official productivity and other economic statistics - individuals and firms have spent a lot of money on hardware and software, yet that investment, as measured by GDP growth or other measures of output growth per unit of input, has been unimpressive. Brynjolfsson and McAfee are firmly in the camp that holds that technology has improved life, it's just that official measures don't capture that very accurately. They compare the adoption rates of electricity to IT and find interesting similarities in how long it's taken for each to start showing up in the numbers, and also quote the famous Robert F Kennedy line about GDP, that it "measures everything, in short, except that which makes life worthwhile." They list four types of intangibles that won't show up in national accounting statistics: intellectual property, organizational capital, user-generated content, and human capital, and note that all of these have been exploding recently. To take one example, Wikipedia has been a death sentence for traditional encyclopedia makers, yet it's a non-profit website. In conventional GDP statistics, it has destroyed millions, perhaps billions of dollars, and yet it's been an enormous boon to everyone who wants to look something up quickly. Email has been bad for the post office. Skype is bad for phone companies. Music publishers hated Napster. And so forth.
All this consumer surplus is great, but it has consequences for where profits flow. We all enjoy bounty to some degree, but it's not spread very evenly. They use an example from the field of photography:
"While digitization has obviously increased the quantity and convenience of photography, it has also profoundly changed the economics of photography production and distribution. A team of just fifteen people at Instagram created a simple app that over 130 million customers use to share some sixteen billion photos (and counting). Within fifteen months of its founding, the company was sold for over $1 billion to Facebook. In turn, Facebook itself reached one billion users in 2012. It had about 4,600 employees including barely 1,000 engineers.
Contrast these figures with pre-digital behemoth Kodak, which also helped customers share billions of photos. Kodak employed 145,300 people at one point, one-third of them in Rochester, New York, while indirectly employing thousands more via the extensive supply chain and retail distribution channels required by companies in the first machine age. Kodak made its founder, George Eastman, a rich man, but it also provided middle-class jobs for generations of people and created a substantial share of the wealth created in the city of Rochester after company’s founding in 1880. But 132 years later, a few months before Instagram was sold to Facebook, Kodak filed for bankruptcy."
In other words, rather than benefit large numbers of people in many communities through plentiful jobs, profits are flowing increasingly to a few people in a few places like Silicon Valley. Anyone who paid any attention to the 2012 Presidential election is familiar with the notion that median wages have been stagnant or declining for many groups for quite a while, and net wealth has taken a shocking decrease since the Recession in particular:
"Between 1983 and 2009, Americans became vastly wealthier overall as the total value of their assets increased. However, as noted by economists Ed Wolff and Sylvia Allegretto, the bottom 80 percent of the income distribution actually saw a net decrease in their wealth. Taken as a group, the top 20 percent got not 100 percent of the increase, but more than 100 percent. Their gains included not only the trillions of dollars of wealth newly created in the economy but also some additional wealth that was shifted in their direction from the bottom 80 percent. The distribution was also highly skewed even among relatively wealthy people. The top 5 percent got 80 percent of the nation's wealth increase; the top 1 percent got over half of that, and so on for ever-finer subdivisions of the wealth distribution. In an oft-cited example, by 2010 the six heirs of Sam Walton’s fortune, earned when he created Walmart, had more net wealth than the bottom 40 percent of the income distribution in America. In part, this reflects the fact that thirteen million families had a negative net worth."
In English, that means all those Occupy Wall Street slogans about the 99% are more correct than their detractors would like to believe, but the overall picture is (slightly) more complex than "the 1% are stealing everything". Even beyond the decoupling of wages and productivity, there's been a global fall in the labor share of GDP, meaning that wealth is flowing more to owners of capital. In many sectors we now have a superstar economy, where there's enormous demand for a few popular things at the expense of many less-popular things. This entails a shift from returns for absolute performance (meaning that performing at 90% of the level of the best gets you 90% of the return) to returns for relative performance (meaning that no one wants the tenth-best app in whatever field, so you get nothing). This can be partially counteracted by long tail-type economies, which make it possible for relative low-performers to scrape by, but they're not very lucrative because of the power of network effects and technological lock-in. Even if Windows Phone is on paper basically just as good as iOS or Android, no one cares, and though everyone derives some benefit from the ubiquity of smartphones, profits in the industry flow to very few firms, and within those firms, even fewer people.
This shift from normal/Gaussian distributions of wealth and power to 80-20/power-law distributions is profound; Brynjolfsson and McAfee cite Acemoglu and Robinson's work in Why Nations Fail on the relationship between political institutions and economic distributions, and how exclusive political systems that are set up for the convenience of a small elite not only don't grow very fast but are also terrible places to live for the masses. I would have liked to see them address Paul Krugman's points in The Conscience of a Liberal about how political movements can drive and encourage this re-peasantization process, though I can understand their desire to avoid seeming too strongly partisan or ideological. Tyler Cowen's recent Average Is Over was a good example of how to be too ideological in the wrong direction about these same concerns, arguing that this return to the Gilded Age will be much more pleasant than the original Gilded Age. Sure, large numbers of people will be permanently excluded from labor markets and won't be able to meaningfully participate in the political process, but all the cool new technology means that that won't be so bad, or at least not bad enough to get too upset about.
Unfortunately, Brynjolfsson and McAfee's take on the question of what happens when automation starts to put significant numbers of people permanently out of work is more pessimistic. Even though people have scoffed at this vision of technological unemployment for hundreds of years (see the history of the Luddites and the "lump of labor" fallacy), this time could be different. There are three possible mechanisms for destroying jobs in this way: inelastic demand for goods (this could actually be good, as people would be able to voluntarily choose to work less while still producing the same amount of output), too-rapid change (it might simply take too long to re-skill certain types of workers), and severe skill inequality (some people will just never be able to produce value greater than what a machine could do). This new permanent underclass will be subject to the sorts of social pathologies that got people transported to Australia in past eras, but options in the future will obviously be somewhat more limited. Ironically, the kinds of jobs easiest to automate are also the kinds easiest to offshore, so America might get a breather from offshoring and be able to watch and learn from what happens as large-scale automation in companies like Foxconn gets field-tested overseas before coming here. Of course, Freestyle chess, where humans and computers collaborate to accomplish goals, could be a model for the economy as a whole, but it seems more likely that many people will simply be automated out of a job and left to their own devices.
In the third section they have two groups of solutions, of which the first recapitulates much from Race Against the Machine. In the short-term:
1. Teach the children well
- Use MOOCs, which are both cheaper and provide more opportunities for data-driven feedback
- Raise teacher salaries in exchange for more accountability, coupled with longer school days and a longer school year
2. Restart startups
- Startups provide most new net jobs, but the rate of new startup formation is dropping quickly. "Regulations" might be to blame
3. Make more matches
- Do a better job of matching workers to prospective jobs to reduce frictional unemployment as much as possible
4. Support our scientists
- Reform intellectual property laws by lessening absurdly long copyright terms
- Offer more prizes for research goals, to bring in people who don't fit into the regular grant process mold
5. Upgrade infrastructure/human capital
- There's lots of externalities to improving our terrible infrastructure, even beyond arguments about Keynesian stimulus
- Welcome more high-skill immigrants who are currently going to other countries, and also reform the byzantine/broken immigration process
6. Tax wisely
- More Pigovian taxes that tax bad things, like congestion or pollution taxes
- Consider a land tax or a VAT to fund social programs instead of relying on labor taxes
- More taxes on being a superstar, like higher tax brackets
The second group is new, and to my mind more adequate to the scale of the issues raised previously in the book. In the long-term:
- Build on capitalism and unlimited technological progress without abandoning or attempting to fundamentally restrain either
- Consider a Universal Basic Income, to prevent Voltaire's social ills of "boredom, vice, and want"
- Alternatively, consider a Negative Income Tax like a greatly expanded EITC to encourage work
- Find better ways to use the strengths of humans and machines together, as in Amazon's Mechanical Turk
- Bring marginal people into the labor force via the peer economy, e.g. TaskRabbit, Airbnb, Lyft
- Encourage new ideas (a national mutual fund, designate some jobs "human-only", institute "made by people" labeling similar to that for organic foods, use massive federal hiring a la the Civilian Conservation Corps)
Unfortunately they don't offer much in the way of suggestions on how to move these ideas though Washington. Hey, they're nerds, not lobbyists! Well, any book that attempts to grapple with the consequences of something as world-changing as artificial intelligence on a large scale should certainly be able to offer some pointers on how to get the Republican Party to start offering real solutions to problems that don't boil down to tax cuts for the rich. This kind of naivete is unsurprising, yet still disappointing coming from such smart guys. The additional analysis in the first two sections and the broader range of solutions in the third means that this is a much more complete and useful book than its predecessor was, and while I certainly wouldn't say that this is the final word on the possibilities and pitfalls of large-scale automation, it's as good a starting point as you're likely to find for a while.
December 1, 2014
This book was came up during a discussion of Capital In The 21st Century, and I definitely see the broad similarities, especially in (1) its attempts to show how the 1% is pulling away from the 99% (and .1% pulling away from the rest of the 1%) and (2) its recommendation of using socialism as lube so that the whole capitalist machine doesn’t overheat and explode.
But where Dr. Piketty dismisses technology as a major driving force, Drs. Brynjolfsson and McAfee are all about the technology. They couldn’t be more excited about self-driving cars and human-beating chess computers. (This book is also focused on the US and a lot less Marx-y.)
This book is divided into three parts.
Part 1 is about how great technology is. Lately, it’s even greater than you realize, you dummies. They talk about Google’s controversial Eugenics program, and how IBM’s Watson is bored with watching Jeopardy and now spends its days watching Here Comes Honey Boo Boo and the later seasons of Bridezillas.
Also celebrated in Part 1 is how humanity has progressed from civil disobedience that helped end the Vietnam War to reporting speed traps on Waze.
I was least interested in this part of the book, so I may have gotten some of this wrong.
Part 2 gets more interesting when it discusses the economics of all this groovy technology. Key concepts are the “bounty" — the way technology is improving quality of life, maybe in ways that GDP doesn’t measure — and the “spread” — the way technology is creating winner-take-all economies.
All sorts of ominous graphs are included: (1) showing GDP per capita pulling away from median income per capita, (2) wages moving in lock step independent of education until 1982 then breaking apart like a prism, and (3) labor productivity and the private employment rate diverging around 2002 after being highly correlated.
Some interesting hints are dropped that parts of the economy are moving away from a normal distribution and towards a power law distribution. I would have liked to have seen more data backing this up because two interesting properties of this distribution are that it is scale independent and has a long tail.
Part 3 is a set of recommendations for individuals and society at large.
Some of the ideas floated — like a negative income tax that guarantees a minimum income regardless of working — would make my Facebook feed blow up worse than a iPhone case designed to hold EBT cards. Personally, I’d like to see something like a limit on working hours like 35 to 40 per week across the board.
Other advice is more practical, like if you’re young go to Montessori school, and if you���re old take some MOOCs. And don’t be afraid to team up with computers. After all they are just tools, at least until they figure out how to do your job.
Long term we need to upgrade our infrastructure (which is falling apart), support basic research (funding for which is being gutted), discourage rent seeking behavior with taxes (so no one can retire then?), and improve education (sigh).
So with Congress dithering and our generation's finest minds figuring out how to cash out of their startups, the rest of us will just have to dink around on our smartphones, cashing government checks until AI finally becomes self-aware and puts humanity to its final use.
Recommended, if only to skim Part 1 and then read about the possible economic implications of technology combined with other changes like globalization.
But where Dr. Piketty dismisses technology as a major driving force, Drs. Brynjolfsson and McAfee are all about the technology. They couldn’t be more excited about self-driving cars and human-beating chess computers. (This book is also focused on the US and a lot less Marx-y.)
This book is divided into three parts.
Part 1 is about how great technology is. Lately, it’s even greater than you realize, you dummies. They talk about Google’s controversial Eugenics program, and how IBM’s Watson is bored with watching Jeopardy and now spends its days watching Here Comes Honey Boo Boo and the later seasons of Bridezillas.
Also celebrated in Part 1 is how humanity has progressed from civil disobedience that helped end the Vietnam War to reporting speed traps on Waze.
I was least interested in this part of the book, so I may have gotten some of this wrong.
Part 2 gets more interesting when it discusses the economics of all this groovy technology. Key concepts are the “bounty" — the way technology is improving quality of life, maybe in ways that GDP doesn’t measure — and the “spread” — the way technology is creating winner-take-all economies.
All sorts of ominous graphs are included: (1) showing GDP per capita pulling away from median income per capita, (2) wages moving in lock step independent of education until 1982 then breaking apart like a prism, and (3) labor productivity and the private employment rate diverging around 2002 after being highly correlated.
Some interesting hints are dropped that parts of the economy are moving away from a normal distribution and towards a power law distribution. I would have liked to have seen more data backing this up because two interesting properties of this distribution are that it is scale independent and has a long tail.
Part 3 is a set of recommendations for individuals and society at large.
Some of the ideas floated — like a negative income tax that guarantees a minimum income regardless of working — would make my Facebook feed blow up worse than a iPhone case designed to hold EBT cards. Personally, I’d like to see something like a limit on working hours like 35 to 40 per week across the board.
Other advice is more practical, like if you’re young go to Montessori school, and if you���re old take some MOOCs. And don’t be afraid to team up with computers. After all they are just tools, at least until they figure out how to do your job.
Long term we need to upgrade our infrastructure (which is falling apart), support basic research (funding for which is being gutted), discourage rent seeking behavior with taxes (so no one can retire then?), and improve education (sigh).
So with Congress dithering and our generation's finest minds figuring out how to cash out of their startups, the rest of us will just have to dink around on our smartphones, cashing government checks until AI finally becomes self-aware and puts humanity to its final use.
Recommended, if only to skim Part 1 and then read about the possible economic implications of technology combined with other changes like globalization.
May 22, 2017
Great insights, but...
This starts with a bang, esp on network effects and geometric growth effects. Humming along, until the book tried to recommend govt policy. Then and only then, the rate of insights dwindled.
This starts with a bang, esp on network effects and geometric growth effects. Humming along, until the book tried to recommend govt policy. Then and only then, the rate of insights dwindled.
November 18, 2016
Wow, this book is terrible: a completely uncritical, technodeterministic paean to cornucopian progress. First of all, it's a paradigmatic example of a business press article that gets puffed up steroidally into a book by adding anecdotes, but without any additional analytic content.
Second, while it does contain some useful insights - for example, that what determines whether a job is subject technological obsolescence via automation is not the cognitive/manual distinction, but the routine/nonroutine distinction: tax preparers are at far more risk, for example, than hairdressers - these are obscured by some truly ridiculous arguments about the value of innovation. For example, McAfee & Brynjolfsson argue (with justice) that the social value of free goods is not captured by GDP statistics, but they follow with the ridiculous assertion that a better way to capture value is by measuring how much attention people "pay." Thus, according to M&B, the fact that Americans doubled the amount of time they spend on the internet between 2000 and 2011 means "they valued it more than the other ways they could spend their time." Following this logic, I presume B&M would also conclude that the fact that American opiate use rose nearly tenfold during that same period means that Americans "value" opiates more now, and indeed that the opiate economy must have been even more innovative and valuable than the Internet economy in the early 21st century. (Similar idiocies follow whenever economists uncritically assume the sovereignty of consumer choices. Meeting people's "revealed preferences" doesn't necessarily correspond to socially optimal outcomes, as anyone who has ever parented a child should know.)
Finally, M&B are profoundly blind about the fact that the distributional consequences of innovation are not determined by technology, but rather by the policy and political choices made about how to deploy the technologies and share the rewards of improved productivity. Note to the authors: there is nothing inherent about the technology of the Internet that mandates that marginal tax rates should be low, or that the economic benefits of the productivity gains of the last 40 years should have been captured entirely by the 1%. That is a policy choice, not a technological necessity. But the closest they come to acknowledging this is with the oblique observation that, "In some cases, cultural barriers to very large pay packages have fallen." Cultural barriers!
This book is ultimately less useful for its insights into social or technological reality than as a symptom of the sort of stupidities that pervades the techno-libertarian movement of our current mal du siècle.
Second, while it does contain some useful insights - for example, that what determines whether a job is subject technological obsolescence via automation is not the cognitive/manual distinction, but the routine/nonroutine distinction: tax preparers are at far more risk, for example, than hairdressers - these are obscured by some truly ridiculous arguments about the value of innovation. For example, McAfee & Brynjolfsson argue (with justice) that the social value of free goods is not captured by GDP statistics, but they follow with the ridiculous assertion that a better way to capture value is by measuring how much attention people "pay." Thus, according to M&B, the fact that Americans doubled the amount of time they spend on the internet between 2000 and 2011 means "they valued it more than the other ways they could spend their time." Following this logic, I presume B&M would also conclude that the fact that American opiate use rose nearly tenfold during that same period means that Americans "value" opiates more now, and indeed that the opiate economy must have been even more innovative and valuable than the Internet economy in the early 21st century. (Similar idiocies follow whenever economists uncritically assume the sovereignty of consumer choices. Meeting people's "revealed preferences" doesn't necessarily correspond to socially optimal outcomes, as anyone who has ever parented a child should know.)
Finally, M&B are profoundly blind about the fact that the distributional consequences of innovation are not determined by technology, but rather by the policy and political choices made about how to deploy the technologies and share the rewards of improved productivity. Note to the authors: there is nothing inherent about the technology of the Internet that mandates that marginal tax rates should be low, or that the economic benefits of the productivity gains of the last 40 years should have been captured entirely by the 1%. That is a policy choice, not a technological necessity. But the closest they come to acknowledging this is with the oblique observation that, "In some cases, cultural barriers to very large pay packages have fallen." Cultural barriers!
This book is ultimately less useful for its insights into social or technological reality than as a symptom of the sort of stupidities that pervades the techno-libertarian movement of our current mal du siècle.
December 29, 2015
Having watched Andrew McAfee's presentation at a manager's conference, I wanted to read more of his assumptions: Digitalization capabilities raise exponentially and while we didn't notice much of that explosion previously, right now we are the start of the "second half of the chessboard" where everything can happen and we have to act quickly to not be overrun by the development. One of his main examples wascomputer Watson winning Jeopardy.
It is only now that digitalization and automation will turn the society similarly to the first Industrial revolution, and these topics fit very well to Siemens's positioning (only leaving out electrification).
I was especially interested to read more about a statement in his discussion where he emphasized platforms as a key factor to further development. Alas, the book didn't bring much further to that element.
The book is a nice, easily readable introductory work. It doesn't get too technical or too economical but reflects and extends his talk.
The only thing that I don't understand is his reluctance concerning singularity (when artificial intelligences will be smarter than humans). He stated that it is so far away that it is similar to "caring about overpopulation on Mars". At the same time, he warns that we cannot understand the technical explosion on the second half of the chessboard anymore. That doesn't fit together in my opinion.
The book is introductory in the way that it only presents the situation but doesn't provide good approaches besides trivial ones (as: let your children get a higher education). Also, it doesn't consider anything outside U.S. context, which I miss as an European reader.
I fully recommend the book with a warning to raise expectations too high.
It is only now that digitalization and automation will turn the society similarly to the first Industrial revolution, and these topics fit very well to Siemens's positioning (only leaving out electrification).
I was especially interested to read more about a statement in his discussion where he emphasized platforms as a key factor to further development. Alas, the book didn't bring much further to that element.
The book is a nice, easily readable introductory work. It doesn't get too technical or too economical but reflects and extends his talk.
The only thing that I don't understand is his reluctance concerning singularity (when artificial intelligences will be smarter than humans). He stated that it is so far away that it is similar to "caring about overpopulation on Mars". At the same time, he warns that we cannot understand the technical explosion on the second half of the chessboard anymore. That doesn't fit together in my opinion.
The book is introductory in the way that it only presents the situation but doesn't provide good approaches besides trivial ones (as: let your children get a higher education). Also, it doesn't consider anything outside U.S. context, which I miss as an European reader.
I fully recommend the book with a warning to raise expectations too high.
April 28, 2014
I should start saying I am a real fan of Andrew McAfee and Erik Brynjolfsson and the book has a lot of good content, I guess I was just a little disappointed because I was expecting more than what was already covered in Race Against The Machine. This expands upon that a bit, but it appears to have been hastily put together. But put that aside for the moment.
The book covers the most important trend of our time: machines, together with information technology, are becoming capable enough to handle many things which to date have only been able to be done by humans. Robots are in a very real way replacing humans in the workplace. This is compared with other technological trends, most importantly a lot of time is spend on the nature of exponential trends, and how counter intuitive they are.
When you digitize things, distribution of digitized things becomes essentially free, and some very odd twists occur from the rules that underlie our culture. Things are never moved, actually they are copied instead. Copying has no cost in the digital realm. More important free distribution causes a distinctly "winner takes all" pattern. The network effect causes one or two instances of a genre to overwhelm the rest and take the lions share. No longer is there a broad set of varying choices, but things seem to narrow to a very small number of winners, and everyone else losing. Facebook is huge and essentially nothing in second place. Instant, free distribution of product means that the winner can dominate surprisingly quickly.
We see this happening in the social network space, but they present information technology as a "General Purpose Technology" that will eventually effect everything. This may have a profound effect on the GDP.
The most interesting chapter was one that attempts to tie the problem to income disparity to this second machine age. Some of the arguments were weak, however there is a compelling connection. There is however without a doubt a disrupting effect on the economy as people attempt to live the old patterns in a world that no longer operates on those principles.
The Luddite question: Will the increase in automation on the whole leave us fewer human jobs? Two lines of argument:
1. Economic theory
CON: National Academy of Science argues that demand is elastic enough that when price drops, demand picks up and sustains the labor need. Jevons paradox is that lightbulbs that use less power can actually cause an increase in power consumption as people use more lights.
PRO: Keynes and Leontief argue that (a) demand can be saturated so not desire to purchase more, (b) technology may be changing faster that people can possibly learning, leaving people permanently out, (c) value of labor might drop to the point where people stop working
2. History
CON: 100 years show the Luddites to be simply alarmists
PRO: the last 15 years we see economic growth without job growth which might indicate that this time is different.
They briefly touch on how globalization might be the cause of US labor loss, however, even China is seeing labor replaced with machine. Their position is that humans and machine are more powerful than either alone, best summarized by this quote: "as long as there are unmet needs and wants in the world, unemployment is a loud warning that we simply aren't thinking hard enough about what needs doing." This makes sense.
Finally they make recommendations, both for individuals and for policy makers. They are sound, common sense recommendations. It appears that humans together with machines still beat machines easily, and so we need to look at new ways to leverage the power of machines, together with the power of humans. Specifically:
1) radical overhaul of the education system which was designed at a time when humans needed to be more like robots. Education should instead be about the things that robots can not do.
2) focus on new startups
3) helping workers to be more mobile
4) support scientists
5) Focus on infrastructure
6) Tax wisely
In the longer term they suggest we rethink the way we tax altogether to match the realities of a digitized economy. They point out that America is the only one of thirty four nations in the OECD without a value-added tax.
We summarize the book with the following quote: "If the first machine age helped unlock the forces of energy trapped in chemical bonds to reshape the physical world, the real promise of the second machine age is to help unleash the power of human ingenuity"
The book covers the most important trend of our time: machines, together with information technology, are becoming capable enough to handle many things which to date have only been able to be done by humans. Robots are in a very real way replacing humans in the workplace. This is compared with other technological trends, most importantly a lot of time is spend on the nature of exponential trends, and how counter intuitive they are.
When you digitize things, distribution of digitized things becomes essentially free, and some very odd twists occur from the rules that underlie our culture. Things are never moved, actually they are copied instead. Copying has no cost in the digital realm. More important free distribution causes a distinctly "winner takes all" pattern. The network effect causes one or two instances of a genre to overwhelm the rest and take the lions share. No longer is there a broad set of varying choices, but things seem to narrow to a very small number of winners, and everyone else losing. Facebook is huge and essentially nothing in second place. Instant, free distribution of product means that the winner can dominate surprisingly quickly.
We see this happening in the social network space, but they present information technology as a "General Purpose Technology" that will eventually effect everything. This may have a profound effect on the GDP.
The most interesting chapter was one that attempts to tie the problem to income disparity to this second machine age. Some of the arguments were weak, however there is a compelling connection. There is however without a doubt a disrupting effect on the economy as people attempt to live the old patterns in a world that no longer operates on those principles.
The Luddite question: Will the increase in automation on the whole leave us fewer human jobs? Two lines of argument:
1. Economic theory
CON: National Academy of Science argues that demand is elastic enough that when price drops, demand picks up and sustains the labor need. Jevons paradox is that lightbulbs that use less power can actually cause an increase in power consumption as people use more lights.
PRO: Keynes and Leontief argue that (a) demand can be saturated so not desire to purchase more, (b) technology may be changing faster that people can possibly learning, leaving people permanently out, (c) value of labor might drop to the point where people stop working
2. History
CON: 100 years show the Luddites to be simply alarmists
PRO: the last 15 years we see economic growth without job growth which might indicate that this time is different.
They briefly touch on how globalization might be the cause of US labor loss, however, even China is seeing labor replaced with machine. Their position is that humans and machine are more powerful than either alone, best summarized by this quote: "as long as there are unmet needs and wants in the world, unemployment is a loud warning that we simply aren't thinking hard enough about what needs doing." This makes sense.
Finally they make recommendations, both for individuals and for policy makers. They are sound, common sense recommendations. It appears that humans together with machines still beat machines easily, and so we need to look at new ways to leverage the power of machines, together with the power of humans. Specifically:
1) radical overhaul of the education system which was designed at a time when humans needed to be more like robots. Education should instead be about the things that robots can not do.
2) focus on new startups
3) helping workers to be more mobile
4) support scientists
5) Focus on infrastructure
6) Tax wisely
In the longer term they suggest we rethink the way we tax altogether to match the realities of a digitized economy. They point out that America is the only one of thirty four nations in the OECD without a value-added tax.
We summarize the book with the following quote: "If the first machine age helped unlock the forces of energy trapped in chemical bonds to reshape the physical world, the real promise of the second machine age is to help unleash the power of human ingenuity"
February 3, 2016
Ze začátku je ta kniha výborná a čitvá, ale postupen času se stane dost nudnou a řekl bych, že to je ve fázi, kdy autoři začnou polemizovat nad ekonomicko-sociálním dopadem druhého věku strojů. Konec už mi vyloženě přišel jako utopie založená na spekulací k vy. Přestože jsem měl problém knihu dočíst, oceňuji na ní to, že je v ní dost zajímavých myšlenek.
November 30, 2018
Дуже корисна книга в часи розвитку машинного інтелекту. В книзі автор намагається дати відповідь на такі запитання: що робити далі з роботами, які напрямки обрати для навчання і розвитку людині, щоб не залишитись без роботи. Читати було дуже цікаво.
Книга - суперключ для розвитку мозку. Тренуй Свій Мозок разом з Readlax
Книга - суперключ для розвитку мозку. Тренуй Свій Мозок разом з Readlax
December 17, 2021
Die Technologie beschleunigt die Entwicklung und Ängste entstehen. Ein Weg hier raus ist es seine Kreativität wieder zuerkennen. Warum? Maschinen können (erstmal) nicht kreativ Denken im Gegensatz zu uns.
March 13, 2014
Exponential advancement, digitization and recombination are the keystone considerations in The Second Machine Age's evaluation of our prospects in the next decade and beyond. The authors are reserved optimists, and if I had to guess I suspect that they subscribe to the view that an optimistic prediction is more likely to lead to an optimistic outcome. I sort of lean that way myself as long as there’s a sharp demarcation between optimism and hype—which the authors aren't confused by.
That said, for all the optimism, what's really at the heart of The Second Machine Age is technological unemployment. I believe the term was addressed only once directly a good two-thirds of the way into the book and with good reason: If we're trying to frame technological progress as a net benefit with a few perils that we must rationally explore, technological unemployment is really a wretched way to put it to the person on the street—technology is the thing that is going to make you unemployed. And to a savvier audience's ear it's the undead Malthus rearing again.
The authors are a couple of MIT economists, and the meat of the book tracks a growing tension between what they term the bounty (total payout, GDP) and the spread (disbursement of the bounty). It's fairly uncontested that the bounty is growing, but they highlight troubling trends that indicate the spread increasingly ends up in the hands of fewer and fewer people—often “superstars”. Nothing nefarious is going on; largely this is just the logistics of the digital economy. Technological development has always been equated to a rising tide that lifts all boats, but Brynjolfsson's and McAffee's analysis calls that into question. Falling wages are not a problem if new technological efficiencies force prices down even faster. We can hope that this will be true. But what happens if technological efficiencies hasten not falling wages but unemployment? A wage can only fall so far. It can be hard to extricate yourself from these kinds of this-time-is-different arguments when you’re right in the thick of them. A nice little excerpt from Gregory Clark’s A Farewell to Alms encapsulates the worry:
“There was a type of employee at the beginning of the Industrial Revolution whose job and livelihood largely vanished in the early twentieth century. This was the horse. The population of working horses actually peaked in England long after the Industrial Revolution, in 1901, when 3.25 million were at work. Though they had been replaced by rail for long-distance haulage and by steam engines for driving machinery, they still plowed fields, hauled wagons and carriages short distances, pulled boats on the canals, toiled in the pits, and carried armies to battle. But the arrival of the internal combustion engine in the late nineteenth century rapidly displaced these workers, so that by 1924 there were fewer than two million. There was always a wage at which all these horses could have remained employed. But that wage was so low that it did not pay for their feed.”
Brynjolfsson and McAffee address these concerns with a list of policy recommendations. In the short term we should be focused on improving education with a STEM focus (simple and straightforward enough, right?), promoting startups (immigration reform, reducing regulatory burden), better employee-employer matching tools, sustaining academic research funding (especially with the uses of contests and prizes), IP reform with an eye towards softening protection, upgrading infrastructure and taxing “wisely” (Pigovian taxes on pollution, traffic congestion and such; consider higher taxes on top earners). Long term—2020s and beyond—we should be considering a guaranteed basic income—although they prefer promoting work—a negative income tax and not stifling the budding peer economy with regulation.
The problem is that the book's policy recommendations in most cases don't amount to much more than a list. Analysis of individual recommendations remains fairly vague with implementation nuances nearly absent. For example, “[W]e see two pieces of good news here [regarding benefits of keeping people employed]. The first is that economists have developed interventions that encourage and reward work in ways that a basic income guarantee alone does not. The second is that innovators and entrepreneurs have developed technologies not only to substitute for human labor but also to complement it.” And these are? Well, it turns out that’s the extent of it.
To be fair, almost never are they as vague as that, and it is after all a broad survey kind of book that's more focused on getting people into a mindset where they're looking for the impacts of exponential leaps in tech development rather than linear. More troubling, though—and especially in light of the message of increasing complexity—is that despite numerous modest caveats (“[N]one of our predictions and recommendations here should be treated as gospel”) it's a book about predictions that points out the shortcomings of past predictions but does nothing to address how this time really is different. In the beginning they highlight 2004's The New Division of Labor by Frank Levy and Richard Murnane that, although very compelling at the time of publication, predicted that we would not see self-driving cars any time soon. The reference functions more as a so-don’t-blame-us-if-we’re-wrong hedge than as an inroad to how they’ve triumphed over past analysis. So then how valuable is any of the forthcoming prediction going to be?
Their caveats frame the book as a sort of current best effort for prediction, but given the track record (not the authors' predictions, but technologists' in general), it’s hard to know what to make of The Second Machine Age's predictions, and it won’t make the audience at all confident that the examples they bring are the same slim few trotted out and recycled throughout other similar books and a swarm of TED talks (Watson, Google’s self-driving car, etc.). And the premise of their gung-ho effort to reframe this ongoing technological unemployment issue as a race with not against machines, rests on worryingly tentative ground, precisely one such example that proponents in all these books love to point to: We all know how IBM's Deep Blue supercomputer beat Gary Kasparov in 1997, but in a new kind of chess tournament where any combination of computer and human can team up against each other it turns out that computer-human teams are beating the best computers when they are unassisted by humans.
Now we have IBM reconfiguring Watson as Dr. Watson and it's going to be able to assist medical doctors with diagnoses. From the chess example we’re supposed to extrapolate that this doctor-computer combo is poised as the new dynamic duo, better than a computer or a doctor alone, but what about the 2004 advice that we won't be seeing self-driving cars any time soon? The point is not that this is all bullshit or something and that we're deluded to try to compete—more precisely, to collaborate—but really to look at any book about prediction without meta-prediction with a degree of suspicion commensurate to the heavy burden of proof that truly rests on the predictor.
The authors' apparent desire that their audience welcome the future and not be too hastily organize into Luddite factions seems to have ignored the more chaotic possibilities of change. (Nothing stylistically offensive or otherwise unscrupulous here. I don't want to leave the impression that they’re being at all duplicitous, saccharine, patronizing or whatever…) The Second Machine Age shies away from words like disintermediation and disruption which seems to be an oversight for a book addressing technological change. If you’re an intermediary you should maybe begin considering the possibility of being disintermediarried. It'd be pretty naive to make staunch predictions about new forms of social and organizational upheavals (guessing at the next Twitter, Craigslist, etc.), but how complete is a look forward that doesn't on the other hand make room for these as at least a vague inevitable. At best Brynjolfsson and McAfee issue the recommendation not to stifle the growing peer economy. Technologies that decentralize and democratize are those which are going to more favorably augment that troubling relationship between bounty and spread, and that aspect is not addressed. We have the influx of sensors, diagnostics and health tracking modalities starting to subject healthcare to Moore’s law while shifting things towards the preventative side—the vastly cheaper side—of the healthcare spectrum. Cryptocurrency and block chain technology, sometimes called the internet of money, and the applications like decentralized autonomous organizations (DAOs/DACs) that will be built on top of them have the possibility to completely reconfigure the financial sector and international payments, and that’s just the beginning. Perhaps we should also be curious and hopeful about mesh networks.
Ultimately a spin in the Google autonomous car didn't change the fact that Brynjolfsson and McAfee are policy guys. (I point this out without any maliciousness. I've been paying attention to the two since the ebook that was the inspiration for this book, and both are as knowledgeable as they are likable.) The solutions they offer are all policy solutions, not technological solutions. In playing to their strengths they missed a huge piece of the terrain.
And as a policy oriented guide the narrative is necessarily calibrated to the nation state level (specifically the US, but it's general enough to extrapolate), and a whole fascinating international dynamic is thoroughly omitted.
Apart from the solid economic analysis, the book is most laudable in its effort to drill in the mindset that the exponential leap has taken the mantle from the linear. On this ground I’m tempted to rate it five stars to drive up the appeal to the person who only typically reads business guru books and the economist that doesn't have time to keep up on technological trends. A wider audience really needs to be getting acquainted with the exponential, and rather than a perceived crackpot inventor like Ray Kurzweil maybe a couple of credible econ profs from MIT are just the right people to outline it. If that all seems like old hat in the technological realm, well, it is. Maybe just skim to the economic analysis in the middle.
That said, for all the optimism, what's really at the heart of The Second Machine Age is technological unemployment. I believe the term was addressed only once directly a good two-thirds of the way into the book and with good reason: If we're trying to frame technological progress as a net benefit with a few perils that we must rationally explore, technological unemployment is really a wretched way to put it to the person on the street—technology is the thing that is going to make you unemployed. And to a savvier audience's ear it's the undead Malthus rearing again.
The authors are a couple of MIT economists, and the meat of the book tracks a growing tension between what they term the bounty (total payout, GDP) and the spread (disbursement of the bounty). It's fairly uncontested that the bounty is growing, but they highlight troubling trends that indicate the spread increasingly ends up in the hands of fewer and fewer people—often “superstars”. Nothing nefarious is going on; largely this is just the logistics of the digital economy. Technological development has always been equated to a rising tide that lifts all boats, but Brynjolfsson's and McAffee's analysis calls that into question. Falling wages are not a problem if new technological efficiencies force prices down even faster. We can hope that this will be true. But what happens if technological efficiencies hasten not falling wages but unemployment? A wage can only fall so far. It can be hard to extricate yourself from these kinds of this-time-is-different arguments when you’re right in the thick of them. A nice little excerpt from Gregory Clark’s A Farewell to Alms encapsulates the worry:
“There was a type of employee at the beginning of the Industrial Revolution whose job and livelihood largely vanished in the early twentieth century. This was the horse. The population of working horses actually peaked in England long after the Industrial Revolution, in 1901, when 3.25 million were at work. Though they had been replaced by rail for long-distance haulage and by steam engines for driving machinery, they still plowed fields, hauled wagons and carriages short distances, pulled boats on the canals, toiled in the pits, and carried armies to battle. But the arrival of the internal combustion engine in the late nineteenth century rapidly displaced these workers, so that by 1924 there were fewer than two million. There was always a wage at which all these horses could have remained employed. But that wage was so low that it did not pay for their feed.”
Brynjolfsson and McAffee address these concerns with a list of policy recommendations. In the short term we should be focused on improving education with a STEM focus (simple and straightforward enough, right?), promoting startups (immigration reform, reducing regulatory burden), better employee-employer matching tools, sustaining academic research funding (especially with the uses of contests and prizes), IP reform with an eye towards softening protection, upgrading infrastructure and taxing “wisely” (Pigovian taxes on pollution, traffic congestion and such; consider higher taxes on top earners). Long term—2020s and beyond—we should be considering a guaranteed basic income—although they prefer promoting work—a negative income tax and not stifling the budding peer economy with regulation.
The problem is that the book's policy recommendations in most cases don't amount to much more than a list. Analysis of individual recommendations remains fairly vague with implementation nuances nearly absent. For example, “[W]e see two pieces of good news here [regarding benefits of keeping people employed]. The first is that economists have developed interventions that encourage and reward work in ways that a basic income guarantee alone does not. The second is that innovators and entrepreneurs have developed technologies not only to substitute for human labor but also to complement it.” And these are? Well, it turns out that’s the extent of it.
To be fair, almost never are they as vague as that, and it is after all a broad survey kind of book that's more focused on getting people into a mindset where they're looking for the impacts of exponential leaps in tech development rather than linear. More troubling, though—and especially in light of the message of increasing complexity—is that despite numerous modest caveats (“[N]one of our predictions and recommendations here should be treated as gospel”) it's a book about predictions that points out the shortcomings of past predictions but does nothing to address how this time really is different. In the beginning they highlight 2004's The New Division of Labor by Frank Levy and Richard Murnane that, although very compelling at the time of publication, predicted that we would not see self-driving cars any time soon. The reference functions more as a so-don’t-blame-us-if-we’re-wrong hedge than as an inroad to how they’ve triumphed over past analysis. So then how valuable is any of the forthcoming prediction going to be?
Their caveats frame the book as a sort of current best effort for prediction, but given the track record (not the authors' predictions, but technologists' in general), it’s hard to know what to make of The Second Machine Age's predictions, and it won’t make the audience at all confident that the examples they bring are the same slim few trotted out and recycled throughout other similar books and a swarm of TED talks (Watson, Google’s self-driving car, etc.). And the premise of their gung-ho effort to reframe this ongoing technological unemployment issue as a race with not against machines, rests on worryingly tentative ground, precisely one such example that proponents in all these books love to point to: We all know how IBM's Deep Blue supercomputer beat Gary Kasparov in 1997, but in a new kind of chess tournament where any combination of computer and human can team up against each other it turns out that computer-human teams are beating the best computers when they are unassisted by humans.
Now we have IBM reconfiguring Watson as Dr. Watson and it's going to be able to assist medical doctors with diagnoses. From the chess example we’re supposed to extrapolate that this doctor-computer combo is poised as the new dynamic duo, better than a computer or a doctor alone, but what about the 2004 advice that we won't be seeing self-driving cars any time soon? The point is not that this is all bullshit or something and that we're deluded to try to compete—more precisely, to collaborate—but really to look at any book about prediction without meta-prediction with a degree of suspicion commensurate to the heavy burden of proof that truly rests on the predictor.
The authors' apparent desire that their audience welcome the future and not be too hastily organize into Luddite factions seems to have ignored the more chaotic possibilities of change. (Nothing stylistically offensive or otherwise unscrupulous here. I don't want to leave the impression that they’re being at all duplicitous, saccharine, patronizing or whatever…) The Second Machine Age shies away from words like disintermediation and disruption which seems to be an oversight for a book addressing technological change. If you’re an intermediary you should maybe begin considering the possibility of being disintermediarried. It'd be pretty naive to make staunch predictions about new forms of social and organizational upheavals (guessing at the next Twitter, Craigslist, etc.), but how complete is a look forward that doesn't on the other hand make room for these as at least a vague inevitable. At best Brynjolfsson and McAfee issue the recommendation not to stifle the growing peer economy. Technologies that decentralize and democratize are those which are going to more favorably augment that troubling relationship between bounty and spread, and that aspect is not addressed. We have the influx of sensors, diagnostics and health tracking modalities starting to subject healthcare to Moore’s law while shifting things towards the preventative side—the vastly cheaper side—of the healthcare spectrum. Cryptocurrency and block chain technology, sometimes called the internet of money, and the applications like decentralized autonomous organizations (DAOs/DACs) that will be built on top of them have the possibility to completely reconfigure the financial sector and international payments, and that’s just the beginning. Perhaps we should also be curious and hopeful about mesh networks.
Ultimately a spin in the Google autonomous car didn't change the fact that Brynjolfsson and McAfee are policy guys. (I point this out without any maliciousness. I've been paying attention to the two since the ebook that was the inspiration for this book, and both are as knowledgeable as they are likable.) The solutions they offer are all policy solutions, not technological solutions. In playing to their strengths they missed a huge piece of the terrain.
And as a policy oriented guide the narrative is necessarily calibrated to the nation state level (specifically the US, but it's general enough to extrapolate), and a whole fascinating international dynamic is thoroughly omitted.
Apart from the solid economic analysis, the book is most laudable in its effort to drill in the mindset that the exponential leap has taken the mantle from the linear. On this ground I’m tempted to rate it five stars to drive up the appeal to the person who only typically reads business guru books and the economist that doesn't have time to keep up on technological trends. A wider audience really needs to be getting acquainted with the exponential, and rather than a perceived crackpot inventor like Ray Kurzweil maybe a couple of credible econ profs from MIT are just the right people to outline it. If that all seems like old hat in the technological realm, well, it is. Maybe just skim to the economic analysis in the middle.
November 17, 2019
This was a rather readable book on the impact of technology on people.
I was a little annoyed that the book talks about Kaggle's 2012 competition about the grading of student essays which were sponsored by the Hewlett foundation, and says that "the top three individual finishes were from, respectively, the United States, Slovenia, and Singapore." The finisher from Singapore was born in France and working in Singapore - I'm not sure if I would really say that he was from Singapore.
The start of the book talks about machine capability - improvements in production and capability, especially due to increased implementation worldwide.
I rather liked the point that during recessions, companies slowed down and cut back hiring - but took the opportunity to implement technological solutions, resulting in lower income workers not being hired as the economy moved back out of recession. This would worsen income inequality. The book also talks about other aspects of how income inequality would be magnified by technology - for example, movement towards a "winner takes all" mentality - you wouldn't use the second-best software when you could use the best software. In short, the economic pie has been growing - but:
A related issue to labour is the need for continuous upskilling / reskilling - "as technology eliminates one type of job, ... workers will have to develop new skills and find new jobs. Of course, that can take time, and in the meantime they may be unemployed." Of course, there are also the workers who resist developing new skills -a point is obliquely touched upon with the reference to Luddites, and college students who "today spend only 9 percent of their time studying (compared to 51 percent on "socialising, recreating, and other"), much less than in previous decades, and that only 42 percent reported having taken a class the previous semester that required them to read at least forty pages a week and write at least twenty pages total."
Another interesting point was that the rise of free services would not be reflected in GDP:
At the same time, this could have an uneven effect:
A very thought-provoking book.
4.5/5 stars
I was a little annoyed that the book talks about Kaggle's 2012 competition about the grading of student essays which were sponsored by the Hewlett foundation, and says that "the top three individual finishes were from, respectively, the United States, Slovenia, and Singapore." The finisher from Singapore was born in France and working in Singapore - I'm not sure if I would really say that he was from Singapore.
The start of the book talks about machine capability - improvements in production and capability, especially due to increased implementation worldwide.
I rather liked the point that during recessions, companies slowed down and cut back hiring - but took the opportunity to implement technological solutions, resulting in lower income workers not being hired as the economy moved back out of recession. This would worsen income inequality. The book also talks about other aspects of how income inequality would be magnified by technology - for example, movement towards a "winner takes all" mentality - you wouldn't use the second-best software when you could use the best software. In short, the economic pie has been growing - but:
As a result, not everyone's share of the economic pie is growing. The first two sets of winners are those who have accumulated significant quantities of the right capital assets. These can be either nonhuman capital (such as equipment, structures, intellectual property, or financial assets), or human capital (such as training, education, experience, and skills). Like other forms of capital, human capital is an asset that can generate a stream of income.
A related issue to labour is the need for continuous upskilling / reskilling - "as technology eliminates one type of job, ... workers will have to develop new skills and find new jobs. Of course, that can take time, and in the meantime they may be unemployed." Of course, there are also the workers who resist developing new skills -a point is obliquely touched upon with the reference to Luddites, and college students who "today spend only 9 percent of their time studying (compared to 51 percent on "socialising, recreating, and other"), much less than in previous decades, and that only 42 percent reported having taken a class the previous semester that required them to read at least forty pages a week and write at least twenty pages total."
Another interesting point was that the rise of free services would not be reflected in GDP:
If you would happily pay one dollar to read the morning newspaper but instead you get it for free, then you've just gained one dollar of consumer surplus. However, as noted above, replacing a paid newspaper with an equivalent free new service would decrease GDP even though it increased consumer surplus. In this case, consumer surplus would be a better measure of our economic well-being. Yet as appealing as consumer surplus is as a concept, it is also extremely difficult to measure.
At the same time, this could have an uneven effect:
But we're also realistic about how new educational technologies are being used in practice. Highly motivated self-starters are the ones who take the greatest advantage of the abundance of online educational resources now available. We know twelve- and fourteen-year-olds who are taking college courses to which they previously would never have had access. Meanwhile, their peers don't participate. Consequently what had been a small gap in their knowledge has become a much larger one. The lesson here is that unless we make real efforts to broaden its impact, the digitization of education won't automatically reduce the spread.
A very thought-provoking book.
4.5/5 stars
Read
February 22, 2017I guess a lot of people made a big deal out of this when it came out a few years ago? That's cool, I guess. Here are some things I found interesting:
Income inequality is a natural outcome of mechanical advantage and technological innovation: the more technology replaces labor, the more wealth accrues to those who control technology, and the less to former human laborers
This is basic Marxism, right? I am not an economist (clearly) so I have no idea how true that is, and I'm not convinced they really proved it in the book, but it's an interesting counterargument to the usual "rich people are assholes" line of reasoning, which, of course, is not a mutually exclusive hypothesis.
Universal basic income is not going to work
I think I actually found out about this book while reading an article about UBI, everyone's favorite idea of late. UBI is kind of an awesome fantasy, but I think I side with the authors (and Matthew B. Crawford, and Wendell Berry) in thinking that the non-monetary value of work is too high to dispose of, as well as the corollary notion that most people will not create value for society or the world (or themselves) based purely on self- or social motivation. I was frankly kind of amazed how down they were on the idea! I felt like the entire book was leading up to a painfully predictable UBI finale. Got me!
Stop complaining about free trade because globalized job displacement won't last. When machines replace workers, *all* those jobs will be gone, not displaced
What is the populist counterargument to this? Smash the looms? Here's one: the human labor rarely really goes away, it just gets hidden and compensated less. If we could keep manual labor within national boundaries and subject to equitable labor standards, at least they'd be good jobs instead if Mechanical Turk-like jobs.
There were also some *fairly* problematic bits, starting at the beginning with their godawful "most of history was boring" bit, where the boring parts were when humans weren't pillaging the environment, reproducing like bacteria, or killing each other on ever grander scales. Peace, balance, satisfaction: totally boring. No reason to read Ian Morris, apparently.
They also laud the sharing economy as a wonderful new source of jobs, where jobs are basically ways to keep people busy, glossing over the whole issue of reduced income and more importantly reduced security (gigs are unreliable, no gig platform gives you insurance). The thrust of the book as a whole is to temper the techno-optimism (income inequality is real and will kill us if we don't address it, no matter how fancy our tech), but this seemed like a pretty glaring oversight for 2014.
Their long-term recommendations for surviving our robotic future are... kind of dumb. The first third of the book is all about how machines are starting to do the things we thought were uniquely human, so if that's true, why turn around and recommend that we'll all be ok focusing on what remains in the human domain? In the short term, sure, learn to complement machine powers with your meaty wit and discretion, but what about 100 years out when our phones will, in fact, be both funnier and wiser than we are?
And while this is mostly a book about technology and the economy, it seemed myopic that they failed to address the many "externalities" that could torpedo all of their analyses. What about climate change? What about reactionary political movements? What about the real physical limits of our planet like potable water and the gravity well?
On the whole, while I was often pleasantly provoked while reading, and I really did appreciate the middle bits where they picked apart the strong technological optimism of their peers, the authors' dogged commitment to a sunny outlook probably hamstrung their efforts to make predictions. I mean, no one can make real predictions about the future, but it would have been nice to hear more about the downsides of these "brilliant" technologies. Inspiration is great, but so are contingency plans.
If you've suffered through this entire "review," allow me to recommend these two others, both infinitely more cogent and insightful than anything I've written here:
https://newrepublic.com/article/11832...
http://www.publicbooks.org/nonfiction...
Income inequality is a natural outcome of mechanical advantage and technological innovation: the more technology replaces labor, the more wealth accrues to those who control technology, and the less to former human laborers
This is basic Marxism, right? I am not an economist (clearly) so I have no idea how true that is, and I'm not convinced they really proved it in the book, but it's an interesting counterargument to the usual "rich people are assholes" line of reasoning, which, of course, is not a mutually exclusive hypothesis.
Universal basic income is not going to work
I think I actually found out about this book while reading an article about UBI, everyone's favorite idea of late. UBI is kind of an awesome fantasy, but I think I side with the authors (and Matthew B. Crawford, and Wendell Berry) in thinking that the non-monetary value of work is too high to dispose of, as well as the corollary notion that most people will not create value for society or the world (or themselves) based purely on self- or social motivation. I was frankly kind of amazed how down they were on the idea! I felt like the entire book was leading up to a painfully predictable UBI finale. Got me!
Stop complaining about free trade because globalized job displacement won't last. When machines replace workers, *all* those jobs will be gone, not displaced
What is the populist counterargument to this? Smash the looms? Here's one: the human labor rarely really goes away, it just gets hidden and compensated less. If we could keep manual labor within national boundaries and subject to equitable labor standards, at least they'd be good jobs instead if Mechanical Turk-like jobs.
There were also some *fairly* problematic bits, starting at the beginning with their godawful "most of history was boring" bit, where the boring parts were when humans weren't pillaging the environment, reproducing like bacteria, or killing each other on ever grander scales. Peace, balance, satisfaction: totally boring. No reason to read Ian Morris, apparently.
They also laud the sharing economy as a wonderful new source of jobs, where jobs are basically ways to keep people busy, glossing over the whole issue of reduced income and more importantly reduced security (gigs are unreliable, no gig platform gives you insurance). The thrust of the book as a whole is to temper the techno-optimism (income inequality is real and will kill us if we don't address it, no matter how fancy our tech), but this seemed like a pretty glaring oversight for 2014.
Their long-term recommendations for surviving our robotic future are... kind of dumb. The first third of the book is all about how machines are starting to do the things we thought were uniquely human, so if that's true, why turn around and recommend that we'll all be ok focusing on what remains in the human domain? In the short term, sure, learn to complement machine powers with your meaty wit and discretion, but what about 100 years out when our phones will, in fact, be both funnier and wiser than we are?
And while this is mostly a book about technology and the economy, it seemed myopic that they failed to address the many "externalities" that could torpedo all of their analyses. What about climate change? What about reactionary political movements? What about the real physical limits of our planet like potable water and the gravity well?
On the whole, while I was often pleasantly provoked while reading, and I really did appreciate the middle bits where they picked apart the strong technological optimism of their peers, the authors' dogged commitment to a sunny outlook probably hamstrung their efforts to make predictions. I mean, no one can make real predictions about the future, but it would have been nice to hear more about the downsides of these "brilliant" technologies. Inspiration is great, but so are contingency plans.
If you've suffered through this entire "review," allow me to recommend these two others, both infinitely more cogent and insightful than anything I've written here:
https://newrepublic.com/article/11832...
http://www.publicbooks.org/nonfiction...
September 29, 2016
There was a time when tractors replaced huge amounts of human labor. There were people who gained, and in some cases, technological innovations including farming machinery, ultimately created more jobs then they destroyed. However, with the advent of digital machines, this is no longer true. A single machine that eliminates thousands of humans, doesn't create ten jobs in that place.
More importantly, in a country like India, where it hasn't been so big a factor in employment, the possible influence of computers as replacement to human labor has been grossly underestimated.
This book is an excellent primer for someone who wants to understand why services companies are hiring less entry level engineers, and why there will be a net decay of employment growth in sectors that can utilize computers and machines.
We start with a tracing of human innovation vs population size. We are swiftly taken through an array of problems that have been conquered by the machines, which was once thought impossible. Moracev paradox is introduced, and the authors even try to make us understand the power of an exponential curve.
From there, there are discussions of progress made, effects of them. There is also an attempt to quantify and assign value to labor in the form of tagging Facebook photos and such misc takes that we perform online.
Employment, it's relation to social and individual welfare and eloquently put across, and the book mentions a variety of suggestions to combat this second machine age. From universal basic income to "Made by humans" label, there is no dearth for plausible and simple ideas.
It could've been more internationalized. It was too focused on America and while that is not a deal breaker, a better version would be to see the world as a whole.
Recommended read.
More importantly, in a country like India, where it hasn't been so big a factor in employment, the possible influence of computers as replacement to human labor has been grossly underestimated.
This book is an excellent primer for someone who wants to understand why services companies are hiring less entry level engineers, and why there will be a net decay of employment growth in sectors that can utilize computers and machines.
We start with a tracing of human innovation vs population size. We are swiftly taken through an array of problems that have been conquered by the machines, which was once thought impossible. Moracev paradox is introduced, and the authors even try to make us understand the power of an exponential curve.
From there, there are discussions of progress made, effects of them. There is also an attempt to quantify and assign value to labor in the form of tagging Facebook photos and such misc takes that we perform online.
Employment, it's relation to social and individual welfare and eloquently put across, and the book mentions a variety of suggestions to combat this second machine age. From universal basic income to "Made by humans" label, there is no dearth for plausible and simple ideas.
It could've been more internationalized. It was too focused on America and while that is not a deal breaker, a better version would be to see the world as a whole.
Recommended read.
July 31, 2020
I honestly could not get through this book to save my life, It's as if someone took all the shitty articles about how technology will save us, wrapped in some centrist-liberal daydream from WSJ, The Economist and Forbes and bundled into a book and presented it as a serious work that explains the relationship between technology and humanity's progress in various social, economic and (less so) political domains.
It's an extremely boring hodge-podge of uncritical anecdotal references, that often glorify THE GREAT INNOVATORS of Google, IBM or whatever company the authors see fit to hold up in their techno-worship, Sillicon Valley fraternal bromance. The yuppiness of this book makes my skin crawl, partially because of its prolongued adulation of ''corporate innovators'' but also because its insultingly uncritical approach and unwillingness to tie technology to social and political systems or for that matter thinking outside of the box of capitalist modes of production and consumption.
I often found myself either very bored, angry or just reading through the pages without any sense of engagement, arguments tend to be repetitive, follow the same formula and i struggled to find any kind of pertinent arguments that would raise challenges and questions, other than say how the GDP is in general a bad way of assessing value or wealth.
It's an extremely boring hodge-podge of uncritical anecdotal references, that often glorify THE GREAT INNOVATORS of Google, IBM or whatever company the authors see fit to hold up in their techno-worship, Sillicon Valley fraternal bromance. The yuppiness of this book makes my skin crawl, partially because of its prolongued adulation of ''corporate innovators'' but also because its insultingly uncritical approach and unwillingness to tie technology to social and political systems or for that matter thinking outside of the box of capitalist modes of production and consumption.
I often found myself either very bored, angry or just reading through the pages without any sense of engagement, arguments tend to be repetitive, follow the same formula and i struggled to find any kind of pertinent arguments that would raise challenges and questions, other than say how the GDP is in general a bad way of assessing value or wealth.
November 7, 2020
Lugesin, sest pmts igas tõsisemas tekstis, mis käsitleb tehnoloogia mõju tööturule, viidatakse “The Second Machine Age’ile”. Kahjuks väga pealiskaudne raamat. Suur osa sellest on lihtsalt protsessorite kasvava võimsuse ja teiste lahedate vidinate üle simpimine. Kui lõpuks põhiteemani jõutakse, taandub kogu analüüs Business Insideri artikli tasemele. “Jaa, mõned jäävad tööst ilma, aga innovatsioon loob ka uusi töökohti ning langetab tarbekaupade hinda, seega miks te isegi muretsete?” Autorite arust lahendav kõiki automatiseerimisega kaasnevaid kõrvalnähte lihtsalt parem keskkond iduettevõtetele ja tasuta MOOCid.
Carl Benedikt Frey “The Technology Trap” jätkuvalt parim raamat tehnoloogia ja tööturu vahekorrast, mida seni lugenud olen. “The Second Machine Age” lihtsalt ei suuda võistelda.
Carl Benedikt Frey “The Technology Trap” jätkuvalt parim raamat tehnoloogia ja tööturu vahekorrast, mida seni lugenud olen. “The Second Machine Age” lihtsalt ei suuda võistelda.
January 19, 2018
Primeiro livro terminado em 2018. Excelente, leitura obrigatória para quem gosta e quer entender de tecnologia, seus avanços, suas possibilidades, seus impactos sociais e econômicos. Baseado em pesquisas de campo, o livro é principalmente baseado em dados coletados pelos próprios autores, e em bons artigos e bons livros consultados e lidos pelos autores. É um livro para estudo, para entender todo o contexto atual. Mudou minha maneira de enxergar alguns aspectos do avanço tecnológico, acrescentou ao contexto do que eu já tinha conhecimento. Recomendo sem restrições, um livro para ler e pensar muito.
May 17, 2017
Overall a quite interesting read, but I was a bit disappointed by the policy recommendations chapter, which is the topic I was most interested in.
It's ironic how some parts of the book already feel a bit outdated despite it not being old at all. Ah, technology...
It's ironic how some parts of the book already feel a bit outdated despite it not being old at all. Ah, technology...
March 1, 2014
Read this book if you’re trying to understand what the economics of the future will look like. It doesn’t have all the answers, but the authors do a great job in the exposition. Tyler Cowen’s Average Is Over: Powering America Beyond the Age of the Great Stagnation is very similar.
Brynjolfsson and McAfee’s newest book follows in the footsteps of their last - explaining how advances in computers and robots are putting an increasing strain our society and challenging conventional economics about work and economics. They (correctly) overturn Tyler Cowen’s ridiculous The Great Stagnation: How America Ate All The Low-Hanging Fruit of Modern History, Got Sick, and Will (Eventually) Feel Better argument and lay out what they think are the drivers of the Second Machine Age: “sustained exponential improvement in most aspects of computing, extraordinarily large amounts of digitized information, and recombinant innovation.”
One of the best points in the book was something that I hadn’t really thought of before: “In addition to powerful and useful AI, the other recent development that promises to further accelerate the second machine age is the digital interconnection of the planet’s people. There is no better resource for improving the world and bettering the state of humanity than the world’s humans—all 7.1 billion of us.” I had gotten too hung up on the technical angle. It’s exciting (and depressing) to think of how many “Einsteins” humanity has lost out on because they were in some rural village disconnected from the rest of the world… but we can change that now.
But the same dynamics that help “lost Einsteins” reach their potential also widen the gap between them and everyone else - thanks in part to the “winner take all” dynamics of global markets. As the authors point out, “Today’s information technologies favor more-skilled over less-skilled workers, increase the returns to capital owners over labor, and increase the advantages that superstars have over everybody else.”
Brynjolfsson emphasizes the Importance of education for helping future workers adapt - but he also recognizes that there will likely come a point when technology changes so fast that most people can’t keep up. He’s also concerned about a massive future disruption for developing nations dependent on labor. He tries to assuage some of these concerns by pointing out that human labor will be in great surplus and that supply/demand dynamics will allocate that labor to new and efficient uses… but I’m skeptical.
The final part of his book is the most interesting but least satisfying. He tries to answer the question… what will humans do if they don’t have to work? What would that system look like? He touches on ideas like a guaranteed basic income and raises the right question - how will people find meaning in their lives if they don’t have to work? (Although this may be a more typically American problem, as we live with the legacy of the famous Protestant ethic). Brynjolfsson and McAfee could have gone farther, but perhaps the politics become a bit too fiery and radical for their taste.
Also… all of these guys (Brynjolfsson & McAfee, Tyler Cowen, etc.) are getting all jazzed up about “Freestyle Chess” (where you can use computers to help you win). They are trying to say that the future is about “racing with the machine” rather than “racing against the machine” - but I’m not sure the metaphor holds. The best freestyle chess players have a tremendously deep understanding of how the programs are working… and it seems highly unlikely that we’re going to be able to train the overwhelming majority of the human population to become PhD computer scientists. I don’t buy it.
Some of the best quotes below:
###
And we can be even more precise about which technology was most important. It was the steam engine or, to be more precise, one developed and improved by James Watt and his colleagues in the second half of the eighteenth century.
Now comes the second machine age. Computers and other digital advances are doing for mental power—the ability to use our brains to understand and shape our environments—what the steam engine and its descendants did for muscle power.
Among economic historians there’s wide agreement that, as Martin Weitzman puts it, “the long-term growth of an advanced economy is dominated by the behavior of technical progress.”
As the roboticist Hans Moravec has observed, “It is comparatively easy to make computers exhibit adult-level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.” This situation has come to be known as Moravec’s paradox.
As the cognitive scientist Steven Pinker puts it, “The main lesson of thirty-five years of AI research is that the hard problems are easy and the easy problems are hard. . . . As the new generation of intelligent devices appears, it will be the stock analysts and petrochemical engineers and parole board members who are in danger of being replaced by machines. The gardeners, receptionists, and cooks are secure in their jobs for decades to come.”
One of the main reasons we cite digitization as a main force shaping the second machine age is that digitization increases understanding. It does this by making huge amounts of data readily accessible, and data are the lifeblood of science.
Paul Krugman speaks for many, if not most, economists when he says, “Productivity isn’t everything, but in the long run it is almost everything.” Why? Because, he explains, “A country’s ability to improve its standard of living over time depends almost entirely on its ability to raise its output per worker”—in other words, the number of hours of labor it takes to produce everything, from automobiles to zippers, that we produce... the only viable way for societies to become wealthier—to improve the standard of living available to its people—is for their companies and workers to keep getting more output from the same number of inputs, in other words more goods and services from the same number of people.
Most in the profession would agree with Joseph Schumpeter, the topic’s great scholar, who wrote that, “Innovation is the outstanding fact in the economic history of capitalist society . . . and also it is largely responsible for most of what we would at first sight attribute to other factors.”
But if there’s a big gap between major innovations, economic growth will eventually peter out. We’ll call this the ‘innovation-as-fruit’ view of things, in honor of Tyler Cowen’s imagery of all the low-hanging fruit being picked. In this perspective, coming up with an innovation is like growing fruit, and exploiting an innovation is like eating the fruit over time. Another school of thought, though, holds that the true work of innovation is not coming up with something big and new, but instead recombining things that already exist. And the more closely we look at how major steps forward in our knowledge and ability to accomplish things have actually occurred, the more this recombinant view makes sense.
...and Cowen are world-class economists, but they’re not giving digital technologies their due. The next great meta-idea, invoked by Romer, has already been found: it can be seen in the new communities of minds and machines made possible by networked digital devices running an astonishing variety of software.
If this recombinant view of innovation is correct, then a problem looms: as the number of building blocks explodes, the main difficulty is knowing which combinations of them will be valuable… This model has a fascinating result: because combinatorial possibilities explode so quickly there is soon a virtually infinite number of potentially valuable recombinations of the existing knowledge pieces. The constraint on the economy’s growth then becomes its ability to go through all these potential recombinations to find the truly valuable ones
Because the exponential, digital, and recombinant powers of the second machine age have made it possible for humanity to create two of the most important one-time events in our history: the emergence of real, useful artificial intelligence (AI) and the connection of most of the people on the planet via a common digital network. Either of these advances alone would fundamentally change our growth prospects. When combined, they’re more important than anything since the Industrial Revolution, which forever transformed how physical work was done.
“Most economic fallacies derive from the tendency to assume that there is a fixed pie, that one party can gain only at the expense of another.” —Milton Friedman
However, unlike the steam engine or electricity, second machine age technologies continue to improve at a remarkably rapid exponential pace, replicating their power with digital perfection and creating even more opportunities for combinatorial innovation.
When a business traveler calls home to talk to her children via Skype, that may add zero to GDP, but it’s hardly worthless. Even the wealthiest robber baron would have been unable to buy this service. How do we measure the benefits of free goods or services that were unavailable at any price in previous eras? ...Despite all the attention it gets from economists, pundits, journalist, and politicians, GDP, even if it were perfectly measured, does not quantify our welfare.
“An imbalance between rich and poor is the oldest and most fatal ailment of all republics.” —Plutarch
Rapid advances in our digital tools are creating unprecedented wealth, but there is no economic law that says all workers, or even a majority of workers, will benefit from these advances. For almost two hundred years, wages did increase alongside productivity. This created a sense of inevitability that technology helped (almost) everyone. But more recently, median wages have stopped tracking productivity, underscoring the fact that such a decoupling is not only a theoretical possibility but also an empirical fact in our current economy.
IN SHORT, median income has increased very little since 1979, and it has actually fallen since 1999. But that’s not because growth of overall income or productivity in America has stagnated; as we saw in chapter 7, GDP and productivity have been on impressive trajectories. Instead, the trend reflects a significant reallocation of who is capturing the benefits of this growth, and who isn’t.
To capture these distinctions, work by our MIT colleagues Daron Acemoglu and David Autor suggests that work can be divided into a two-by-two matrix: cognitive versus manual and routine versus nonroutine. They found that the demand for work has been falling most dramatically for routine tasks, regardless of whether they are cognitive or manual. This leads to job polarization: a collapse in demand for middle-income jobs, while nonroutine cognitive jobs (such as financial analysis) and nonroutine manual jobs (like hairdressing) have held up relatively well.
one CEO, and he explained that he knew for over a decade that advances in information technology had rendered many routine information-processing jobs superfluous. At the same time, when profits and revenues are on the rise, it can be hard to eliminate jobs. When the recession came, business as usual obviously was not sustainable, which made it easier to implement a round of painful streamlining and layoffs. As the recession ended and profits and demand returned, the jobs doing routine work were not restored. Like so many other companies in recent years, his organization found it could use technology to scale up without these workers.
“One machine can do the work of fifty ordinary men. No machine can do the work of one extraordinary man.” —Elbert Hubbard
Why are winner-take-all markets more common now? Shifts in the technology for production and distribution, particularly these three changes: a) the digitization of more and more information, goods, and services, b) the vast improvements in telecommunications and, to a lesser extent, transportation, and c) the increased importance of networks and standards.
Even as the technology destroys geography—a barrier that used to protect authors from worldwide competition—it opens up specialization as a source of differentiation. Instead of being the thousandth-best children’s book author in the world, it may be more profitable to be the number-one author in Science-Based Advice for Ecological Entrepreneurs, or Football Clock Management.
Using one-generation measures of social mobility—how much a father’s relative income influences that of his adult son—America does half as well as Nordic countries, and about the same as Britain and Italy, Europe’s least-mobile places.” So the spread is not only large, but also self-perpetuating. Too often, people at the bottom and middle stay where they are over their careers, and families stay locked in across generations. This is not healthy for an economy or society.
First, the theory. There are three economic mechanisms that are candidates for explaining technological unemployment: inelastic demand, rapid change, and severe inequality.
KEYNES DISAGREED. He thought that in the long run, demand would not be perfectly inelastic. That is, ever lower (quality-adjusted) prices would not necessarily mean we would consume ever more goods and services. Instead, we would become satiated and choose to consume less. He predicted that this would lead to a dramatic reduction in working hours to as few as fifteen per week as less and less labor was needed to produce all the goods and services that people demanded.
As Arthur C. Clarke is purported to have put it, “The goal of the future is full unemployment, so we can play.”
Keynes was more concerned with short-term “maladjustments,” which brings us to the second, more serious argument for technological unemployment: the inability of our skills, organizations, and institutions to keep pace with technical change. When technology eliminates one type of job, or even the need for a whole category of skills, those workers will have to develop new skills and find new jobs. Of course, that can take time, and in the meantime they may be unemployed. The optimistic argument maintains that this is temporary. Eventually, the economy will find a new equilibrium and full employment will be restored as entrepreneurs invent new businesses and the workforce adapts its human capital. But what if this process takes a decade? And what if, by then, technology has changed again? This is the possibility that Wassily Leontief had in mind his 1983 article when he speculated that many workers could end up permanently unemployed, like horses unable to adjust to the invention of the tractors.
When engineers work to amplify these differences, building on the areas where machines are strong and humans are weak, then the machines are more likely to complement humans rather than substitute for them. Effective production is more likely to require both human and machine inputs, and the value of the human inputs will grow, not shrink, as the power of machines increases. A second lesson of economics and business strategy is that it’s great to be a complement to something that’s increasingly plentiful.
Thus in a very real sense, as long as there are unmet needs and wants in the world, unemployment is a loud warning that we simply aren’t thinking hard enough about what needs doing. We aren’t being creative enough about solving the problems we have using the freed-up time and energy of the people whose old jobs were automated away.
In the long run, the biggest effect of automation is likely to be on workers not in America and other developed nations, but rather in developing nations that currently rely on low-cost labor for their competitive advantage. If you take most of the costs of labor out of the equation by installing robots and other types of automation, then the competitive advantage of low wages largely disappears. This is already beginning to happen. Terry Guo of Foxconn has been aggressively installing hundreds of thousands of robots to replace an equivalent number of human workers…. In other words, offshoring is often only a way station on the road to automation.
an excellent education is the best way to not be left behind as technology races ahead. The discouraging news is that today many students seem to be squandering at least some of their educational opportunities. The good news, though, is that technology is now providing more of these opportunities than ever before.
The United States was the clear leader in primary education in the first half of the twentieth century, having realized that inequality was a “race between education and technology,” to use a phrase coined by Jan Tinbergen (winner of the first Nobel Prize in Economic Sciences) and used by the economists Claudia Goldin and Lawrence Katz as the title of their influential 2010 book. When technology advances too quickly for education to keep up, inequality generally rises.
It seems sensible, then, for educational reforms in the United States to include renewed efforts to attract and retain well-qualified people in the teaching profession, and to remove or retrain consistent low performers. Part of the bargain should also be longer school hours, longer school years, more after-school activities and more opportunities for preschool education.
Basic income is not part of mainstream policy discussions today, but it has a surprisingly long history and came remarkably close to reality in twentieth-century America. One of its early proponents was the English-American political activist Thomas Paine, who advocated in his 1797 pamphlet Agrarian Justice that everyone should be given a lump sum of money upon reaching adulthood to compensate for the unjust fact that some people were born into landowning families while others were not. Later advocates included philosopher Bertrand Russell and civil rights leader Martin Luther King, Jr.
And just about all the research and evidence we’ve looked at has convinced us that Voltaire was right. It’s tremendously important for people to work not just because that’s how they get their money, but also because it’s one of the principal ways they get many other important things: self-worth, community, engagement, healthy values, structure, and dignity, to name just a few.
In his book Drive, Daniel Pink summarizes the three key motivations from the research literature: mastery, autonomy, and purpose.
But in the long run, the real questions will go beyond economic growth. As more and more work is done by machines, people can spend more time on other activities. Not just leisure and amusements, but also the deeper satisfactions that come from invention and exploration, from creativity and building, and from love, friendship, and community. We don’t have a lot of formal metrics for those kinds of value, and perhaps we never will, but they will nonetheless grow in importance as we satisfy our more basic economic needs. If the first machine age helped unlock the forces of energy trapped in chemical bonds to reshape the physical world, the real promise of the second machine age is to help unleash the power of human ingenuity.
Brynjolfsson and McAfee’s newest book follows in the footsteps of their last - explaining how advances in computers and robots are putting an increasing strain our society and challenging conventional economics about work and economics. They (correctly) overturn Tyler Cowen’s ridiculous The Great Stagnation: How America Ate All The Low-Hanging Fruit of Modern History, Got Sick, and Will (Eventually) Feel Better argument and lay out what they think are the drivers of the Second Machine Age: “sustained exponential improvement in most aspects of computing, extraordinarily large amounts of digitized information, and recombinant innovation.”
One of the best points in the book was something that I hadn’t really thought of before: “In addition to powerful and useful AI, the other recent development that promises to further accelerate the second machine age is the digital interconnection of the planet’s people. There is no better resource for improving the world and bettering the state of humanity than the world’s humans—all 7.1 billion of us.” I had gotten too hung up on the technical angle. It’s exciting (and depressing) to think of how many “Einsteins” humanity has lost out on because they were in some rural village disconnected from the rest of the world… but we can change that now.
But the same dynamics that help “lost Einsteins” reach their potential also widen the gap between them and everyone else - thanks in part to the “winner take all” dynamics of global markets. As the authors point out, “Today’s information technologies favor more-skilled over less-skilled workers, increase the returns to capital owners over labor, and increase the advantages that superstars have over everybody else.”
Brynjolfsson emphasizes the Importance of education for helping future workers adapt - but he also recognizes that there will likely come a point when technology changes so fast that most people can’t keep up. He’s also concerned about a massive future disruption for developing nations dependent on labor. He tries to assuage some of these concerns by pointing out that human labor will be in great surplus and that supply/demand dynamics will allocate that labor to new and efficient uses… but I’m skeptical.
The final part of his book is the most interesting but least satisfying. He tries to answer the question… what will humans do if they don’t have to work? What would that system look like? He touches on ideas like a guaranteed basic income and raises the right question - how will people find meaning in their lives if they don’t have to work? (Although this may be a more typically American problem, as we live with the legacy of the famous Protestant ethic). Brynjolfsson and McAfee could have gone farther, but perhaps the politics become a bit too fiery and radical for their taste.
Also… all of these guys (Brynjolfsson & McAfee, Tyler Cowen, etc.) are getting all jazzed up about “Freestyle Chess” (where you can use computers to help you win). They are trying to say that the future is about “racing with the machine” rather than “racing against the machine” - but I’m not sure the metaphor holds. The best freestyle chess players have a tremendously deep understanding of how the programs are working… and it seems highly unlikely that we’re going to be able to train the overwhelming majority of the human population to become PhD computer scientists. I don’t buy it.
Some of the best quotes below:
###
And we can be even more precise about which technology was most important. It was the steam engine or, to be more precise, one developed and improved by James Watt and his colleagues in the second half of the eighteenth century.
Now comes the second machine age. Computers and other digital advances are doing for mental power—the ability to use our brains to understand and shape our environments—what the steam engine and its descendants did for muscle power.
Among economic historians there’s wide agreement that, as Martin Weitzman puts it, “the long-term growth of an advanced economy is dominated by the behavior of technical progress.”
As the roboticist Hans Moravec has observed, “It is comparatively easy to make computers exhibit adult-level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.” This situation has come to be known as Moravec’s paradox.
As the cognitive scientist Steven Pinker puts it, “The main lesson of thirty-five years of AI research is that the hard problems are easy and the easy problems are hard. . . . As the new generation of intelligent devices appears, it will be the stock analysts and petrochemical engineers and parole board members who are in danger of being replaced by machines. The gardeners, receptionists, and cooks are secure in their jobs for decades to come.”
One of the main reasons we cite digitization as a main force shaping the second machine age is that digitization increases understanding. It does this by making huge amounts of data readily accessible, and data are the lifeblood of science.
Paul Krugman speaks for many, if not most, economists when he says, “Productivity isn’t everything, but in the long run it is almost everything.” Why? Because, he explains, “A country’s ability to improve its standard of living over time depends almost entirely on its ability to raise its output per worker”—in other words, the number of hours of labor it takes to produce everything, from automobiles to zippers, that we produce... the only viable way for societies to become wealthier—to improve the standard of living available to its people—is for their companies and workers to keep getting more output from the same number of inputs, in other words more goods and services from the same number of people.
Most in the profession would agree with Joseph Schumpeter, the topic’s great scholar, who wrote that, “Innovation is the outstanding fact in the economic history of capitalist society . . . and also it is largely responsible for most of what we would at first sight attribute to other factors.”
But if there’s a big gap between major innovations, economic growth will eventually peter out. We’ll call this the ‘innovation-as-fruit’ view of things, in honor of Tyler Cowen’s imagery of all the low-hanging fruit being picked. In this perspective, coming up with an innovation is like growing fruit, and exploiting an innovation is like eating the fruit over time. Another school of thought, though, holds that the true work of innovation is not coming up with something big and new, but instead recombining things that already exist. And the more closely we look at how major steps forward in our knowledge and ability to accomplish things have actually occurred, the more this recombinant view makes sense.
...and Cowen are world-class economists, but they’re not giving digital technologies their due. The next great meta-idea, invoked by Romer, has already been found: it can be seen in the new communities of minds and machines made possible by networked digital devices running an astonishing variety of software.
If this recombinant view of innovation is correct, then a problem looms: as the number of building blocks explodes, the main difficulty is knowing which combinations of them will be valuable… This model has a fascinating result: because combinatorial possibilities explode so quickly there is soon a virtually infinite number of potentially valuable recombinations of the existing knowledge pieces. The constraint on the economy’s growth then becomes its ability to go through all these potential recombinations to find the truly valuable ones
Because the exponential, digital, and recombinant powers of the second machine age have made it possible for humanity to create two of the most important one-time events in our history: the emergence of real, useful artificial intelligence (AI) and the connection of most of the people on the planet via a common digital network. Either of these advances alone would fundamentally change our growth prospects. When combined, they’re more important than anything since the Industrial Revolution, which forever transformed how physical work was done.
“Most economic fallacies derive from the tendency to assume that there is a fixed pie, that one party can gain only at the expense of another.” —Milton Friedman
However, unlike the steam engine or electricity, second machine age technologies continue to improve at a remarkably rapid exponential pace, replicating their power with digital perfection and creating even more opportunities for combinatorial innovation.
When a business traveler calls home to talk to her children via Skype, that may add zero to GDP, but it’s hardly worthless. Even the wealthiest robber baron would have been unable to buy this service. How do we measure the benefits of free goods or services that were unavailable at any price in previous eras? ...Despite all the attention it gets from economists, pundits, journalist, and politicians, GDP, even if it were perfectly measured, does not quantify our welfare.
“An imbalance between rich and poor is the oldest and most fatal ailment of all republics.” —Plutarch
Rapid advances in our digital tools are creating unprecedented wealth, but there is no economic law that says all workers, or even a majority of workers, will benefit from these advances. For almost two hundred years, wages did increase alongside productivity. This created a sense of inevitability that technology helped (almost) everyone. But more recently, median wages have stopped tracking productivity, underscoring the fact that such a decoupling is not only a theoretical possibility but also an empirical fact in our current economy.
IN SHORT, median income has increased very little since 1979, and it has actually fallen since 1999. But that’s not because growth of overall income or productivity in America has stagnated; as we saw in chapter 7, GDP and productivity have been on impressive trajectories. Instead, the trend reflects a significant reallocation of who is capturing the benefits of this growth, and who isn’t.
To capture these distinctions, work by our MIT colleagues Daron Acemoglu and David Autor suggests that work can be divided into a two-by-two matrix: cognitive versus manual and routine versus nonroutine. They found that the demand for work has been falling most dramatically for routine tasks, regardless of whether they are cognitive or manual. This leads to job polarization: a collapse in demand for middle-income jobs, while nonroutine cognitive jobs (such as financial analysis) and nonroutine manual jobs (like hairdressing) have held up relatively well.
one CEO, and he explained that he knew for over a decade that advances in information technology had rendered many routine information-processing jobs superfluous. At the same time, when profits and revenues are on the rise, it can be hard to eliminate jobs. When the recession came, business as usual obviously was not sustainable, which made it easier to implement a round of painful streamlining and layoffs. As the recession ended and profits and demand returned, the jobs doing routine work were not restored. Like so many other companies in recent years, his organization found it could use technology to scale up without these workers.
“One machine can do the work of fifty ordinary men. No machine can do the work of one extraordinary man.” —Elbert Hubbard
Why are winner-take-all markets more common now? Shifts in the technology for production and distribution, particularly these three changes: a) the digitization of more and more information, goods, and services, b) the vast improvements in telecommunications and, to a lesser extent, transportation, and c) the increased importance of networks and standards.
Even as the technology destroys geography—a barrier that used to protect authors from worldwide competition—it opens up specialization as a source of differentiation. Instead of being the thousandth-best children’s book author in the world, it may be more profitable to be the number-one author in Science-Based Advice for Ecological Entrepreneurs, or Football Clock Management.
Using one-generation measures of social mobility—how much a father’s relative income influences that of his adult son—America does half as well as Nordic countries, and about the same as Britain and Italy, Europe’s least-mobile places.” So the spread is not only large, but also self-perpetuating. Too often, people at the bottom and middle stay where they are over their careers, and families stay locked in across generations. This is not healthy for an economy or society.
First, the theory. There are three economic mechanisms that are candidates for explaining technological unemployment: inelastic demand, rapid change, and severe inequality.
KEYNES DISAGREED. He thought that in the long run, demand would not be perfectly inelastic. That is, ever lower (quality-adjusted) prices would not necessarily mean we would consume ever more goods and services. Instead, we would become satiated and choose to consume less. He predicted that this would lead to a dramatic reduction in working hours to as few as fifteen per week as less and less labor was needed to produce all the goods and services that people demanded.
As Arthur C. Clarke is purported to have put it, “The goal of the future is full unemployment, so we can play.”
Keynes was more concerned with short-term “maladjustments,” which brings us to the second, more serious argument for technological unemployment: the inability of our skills, organizations, and institutions to keep pace with technical change. When technology eliminates one type of job, or even the need for a whole category of skills, those workers will have to develop new skills and find new jobs. Of course, that can take time, and in the meantime they may be unemployed. The optimistic argument maintains that this is temporary. Eventually, the economy will find a new equilibrium and full employment will be restored as entrepreneurs invent new businesses and the workforce adapts its human capital. But what if this process takes a decade? And what if, by then, technology has changed again? This is the possibility that Wassily Leontief had in mind his 1983 article when he speculated that many workers could end up permanently unemployed, like horses unable to adjust to the invention of the tractors.
When engineers work to amplify these differences, building on the areas where machines are strong and humans are weak, then the machines are more likely to complement humans rather than substitute for them. Effective production is more likely to require both human and machine inputs, and the value of the human inputs will grow, not shrink, as the power of machines increases. A second lesson of economics and business strategy is that it’s great to be a complement to something that’s increasingly plentiful.
Thus in a very real sense, as long as there are unmet needs and wants in the world, unemployment is a loud warning that we simply aren’t thinking hard enough about what needs doing. We aren’t being creative enough about solving the problems we have using the freed-up time and energy of the people whose old jobs were automated away.
In the long run, the biggest effect of automation is likely to be on workers not in America and other developed nations, but rather in developing nations that currently rely on low-cost labor for their competitive advantage. If you take most of the costs of labor out of the equation by installing robots and other types of automation, then the competitive advantage of low wages largely disappears. This is already beginning to happen. Terry Guo of Foxconn has been aggressively installing hundreds of thousands of robots to replace an equivalent number of human workers…. In other words, offshoring is often only a way station on the road to automation.
an excellent education is the best way to not be left behind as technology races ahead. The discouraging news is that today many students seem to be squandering at least some of their educational opportunities. The good news, though, is that technology is now providing more of these opportunities than ever before.
The United States was the clear leader in primary education in the first half of the twentieth century, having realized that inequality was a “race between education and technology,” to use a phrase coined by Jan Tinbergen (winner of the first Nobel Prize in Economic Sciences) and used by the economists Claudia Goldin and Lawrence Katz as the title of their influential 2010 book. When technology advances too quickly for education to keep up, inequality generally rises.
It seems sensible, then, for educational reforms in the United States to include renewed efforts to attract and retain well-qualified people in the teaching profession, and to remove or retrain consistent low performers. Part of the bargain should also be longer school hours, longer school years, more after-school activities and more opportunities for preschool education.
Basic income is not part of mainstream policy discussions today, but it has a surprisingly long history and came remarkably close to reality in twentieth-century America. One of its early proponents was the English-American political activist Thomas Paine, who advocated in his 1797 pamphlet Agrarian Justice that everyone should be given a lump sum of money upon reaching adulthood to compensate for the unjust fact that some people were born into landowning families while others were not. Later advocates included philosopher Bertrand Russell and civil rights leader Martin Luther King, Jr.
And just about all the research and evidence we’ve looked at has convinced us that Voltaire was right. It’s tremendously important for people to work not just because that’s how they get their money, but also because it’s one of the principal ways they get many other important things: self-worth, community, engagement, healthy values, structure, and dignity, to name just a few.
In his book Drive, Daniel Pink summarizes the three key motivations from the research literature: mastery, autonomy, and purpose.
But in the long run, the real questions will go beyond economic growth. As more and more work is done by machines, people can spend more time on other activities. Not just leisure and amusements, but also the deeper satisfactions that come from invention and exploration, from creativity and building, and from love, friendship, and community. We don’t have a lot of formal metrics for those kinds of value, and perhaps we never will, but they will nonetheless grow in importance as we satisfy our more basic economic needs. If the first machine age helped unlock the forces of energy trapped in chemical bonds to reshape the physical world, the real promise of the second machine age is to help unleash the power of human ingenuity.
March 13, 2017
Worth reading. A good book on the topic - well written and constructed and the arguments and the ideas seem solid and make sense.
In the beginning after a brief intro in the industrial revolution the author argues that the technologies are now becoming indistinguishable from magic (quote from Arthur C.Clarke) because of the Moore's law and the technological capabilities. That means that often the only boundary to technological progress is our imagination.
The main theme throughout the books is that the machines will not take away the workplaces of human labour, but we have to learn how to work together with them. For the machines creative and simple tasks are very hard to learn but for humans - easy. On the other hand, complex calculations are easy for machines and sometimes impossible for humans. Working alone machines and humans cannot achieve as good results as working together.
The biggest problems however are:
- growing gap and polarity between different groups like rich and poor, democrats and republicans in the USA and EU optimists and pessimists in Europe. But in this books' context main one is that it is getting harder for the majority to keep up with the technological progress.
- second problem is that educational system is built in a way, that we are learning not to be creative and original but how to follow rules, which means we are learning skills that machines can do better than us anyway and therefor will be useless. Bigger change in educational system is needed for students as well for reeducation workers, whose jobs will be performed by machines in the future.
In the end the book examines the topics of basic income and sharing economy, however in couple of years since publishing the book, sharing economy has gone a long way.
In summary - an interesting and pleasant read, which stimulates thinking and creation of ideas.
In the beginning after a brief intro in the industrial revolution the author argues that the technologies are now becoming indistinguishable from magic (quote from Arthur C.Clarke) because of the Moore's law and the technological capabilities. That means that often the only boundary to technological progress is our imagination.
The main theme throughout the books is that the machines will not take away the workplaces of human labour, but we have to learn how to work together with them. For the machines creative and simple tasks are very hard to learn but for humans - easy. On the other hand, complex calculations are easy for machines and sometimes impossible for humans. Working alone machines and humans cannot achieve as good results as working together.
The biggest problems however are:
- growing gap and polarity between different groups like rich and poor, democrats and republicans in the USA and EU optimists and pessimists in Europe. But in this books' context main one is that it is getting harder for the majority to keep up with the technological progress.
- second problem is that educational system is built in a way, that we are learning not to be creative and original but how to follow rules, which means we are learning skills that machines can do better than us anyway and therefor will be useless. Bigger change in educational system is needed for students as well for reeducation workers, whose jobs will be performed by machines in the future.
In the end the book examines the topics of basic income and sharing economy, however in couple of years since publishing the book, sharing economy has gone a long way.
In summary - an interesting and pleasant read, which stimulates thinking and creation of ideas.
February 3, 2021
3.5 ⭐️
Ein einleuchtendes Buch.
Im Buch sind verschiedenste Beispiele genannt mit denen die Autoren ihre Thesen begründen. Sie decken eine große Spannbreite von Themen innerhalb von nur 300 Seiten ab und erklären diese auch relativ einfach und interessant. Besonders interessant fand ich das Prinzip der Montessori-Schulen und den Aufruf sich kreativ weiterzubilden. Die Idee des bedingungslosen Grundeinkommens fand ich interessant und die Idee der negativen Einkommenssteuer sogar erstrebenswert.
Ein einleuchtendes Buch.
Im Buch sind verschiedenste Beispiele genannt mit denen die Autoren ihre Thesen begründen. Sie decken eine große Spannbreite von Themen innerhalb von nur 300 Seiten ab und erklären diese auch relativ einfach und interessant. Besonders interessant fand ich das Prinzip der Montessori-Schulen und den Aufruf sich kreativ weiterzubilden. Die Idee des bedingungslosen Grundeinkommens fand ich interessant und die Idee der negativen Einkommenssteuer sogar erstrebenswert.
February 6, 2021
Although a bit outdated now, the information and insights still hold true! The Second Machine Age covers everything from Moore's Law & Moravec's Paradox to the effects of digitizing everything, AI, long-term implications, policy recommendations & more. I read the same authors' previous book Race Against the Machine years ago & really enjoyed it, so it's no surprise that I enjoyed this book too. The flow follows very well from the past, present & future of technology and innovation.
January 28, 2014
*A full executive summary of this book is available here: http://newbooksinbrief.com/2014/01/28...
In the first machine age—otherwise known as the Industrial Revolution—we humans managed to build technologies that allowed us to overcome the limitations of muscle power like never before. The result, which has reverberated these past 200 years, has been an increase in economic productivity unprecedented in human history. And the corollary of this increase in productive power has been an increase in material standard of living and social development equally as unprecedented.
In the past 30 years, with the rise of computers and other digital technologies, we have moved from overcoming our physical limitations, to overcoming our mental ones. This is the second machine age. Though we are still at the dawn of the second machine age, it already shows at least as much promise in boosting productivity (and quality of life) as the first. Indeed, by various measures—including the standard ones of GDP and corporate profits—we can see that the past 30 years has witnessed an impressive steepening in productivity.
And this is just the beginning. For digital technology continues to advance at an exponential pace; more digital information is being produced (and kept) all the time (all of which has enormous economic potential); and new ways of combining existing (and new) ideas into newer and better ones are ever being found.
Still, what is equally apparent is that the benefits of this steepening in productivity have gone to the few, rather than the many. Indeed, while the top 20% of earners have seen their pay increase since the early 1980s (and the closer you are to the top the more dramatically your pay has increased), the bottom 80% has actually seen their wealth decrease. And the spread is widening ever more as we go.
This is no random, or merely temporary outcome. Indeed, as Brynjolfsson and McAfee demonstrate, the unequal distribution of wealth in the second machine age is a natural corollary of how digital technology works and is used. Specifically, computer technology produces an economy that favors capital over labor; skilled labor over unskilled labor; and superstars (who are able to reach and corner entire global markets) over local players.
And not only does computer technology tend to play favorites, thereby increasing inequality. It also steadily erodes human employment outright. For as computer technology advances, more and more jobs that could once be carried out only by humans, becomes possible (and cheaper) for computers to accomplish. Nor is there any guarantee that new innovations and advancements will necessarily produce new jobs as fast as old ones are being lost (as was once thought inevitable). Indeed, we have already seen signs that this simply cannot be counted on.
The problem with all this is not just that extreme inequality is a political problem on its own. It’s that as more and more people are driven out of the economy, the prospects for greater growth are themselves undermined.
Nevertheless, just as wise policies have helped us overcome many of the problems with the Industrial Revolution, Brynjolfsson and McAfee argue that the same can be done with the problems of the Digital Revolution. Specifically, more can be done to ensure that our education systems are geared to the realities and demands of the second machine age; more can be done to ignite and encourage entrepreneurship, which is needed to replace many of the jobs that will be lost; and more can be done to mitigate the inequality caused by the new technology, such as introducing a negative income tax—which preserves a minimal standard of living for all (and keeps people in the economy as consumers), while encouraging all who can to stay in the workforce.
The book is very well-researched, well-written and wisely argued. The authors have taken the facts and the data as they stand, without preconception or political coloring, and have delivered an honest and insightful analysis. Both the bounty and the spread of the second machine age are made apparent, and the proposed approach moving forward is well-measured and judicious. An important book for policy-makers, and the generally curious alike. A full executive summary of this book is available here: http://newbooksinbrief.com/2014/01/28... A podcast discussion of the book will be available soon.
In the first machine age—otherwise known as the Industrial Revolution—we humans managed to build technologies that allowed us to overcome the limitations of muscle power like never before. The result, which has reverberated these past 200 years, has been an increase in economic productivity unprecedented in human history. And the corollary of this increase in productive power has been an increase in material standard of living and social development equally as unprecedented.
In the past 30 years, with the rise of computers and other digital technologies, we have moved from overcoming our physical limitations, to overcoming our mental ones. This is the second machine age. Though we are still at the dawn of the second machine age, it already shows at least as much promise in boosting productivity (and quality of life) as the first. Indeed, by various measures—including the standard ones of GDP and corporate profits—we can see that the past 30 years has witnessed an impressive steepening in productivity.
And this is just the beginning. For digital technology continues to advance at an exponential pace; more digital information is being produced (and kept) all the time (all of which has enormous economic potential); and new ways of combining existing (and new) ideas into newer and better ones are ever being found.
Still, what is equally apparent is that the benefits of this steepening in productivity have gone to the few, rather than the many. Indeed, while the top 20% of earners have seen their pay increase since the early 1980s (and the closer you are to the top the more dramatically your pay has increased), the bottom 80% has actually seen their wealth decrease. And the spread is widening ever more as we go.
This is no random, or merely temporary outcome. Indeed, as Brynjolfsson and McAfee demonstrate, the unequal distribution of wealth in the second machine age is a natural corollary of how digital technology works and is used. Specifically, computer technology produces an economy that favors capital over labor; skilled labor over unskilled labor; and superstars (who are able to reach and corner entire global markets) over local players.
And not only does computer technology tend to play favorites, thereby increasing inequality. It also steadily erodes human employment outright. For as computer technology advances, more and more jobs that could once be carried out only by humans, becomes possible (and cheaper) for computers to accomplish. Nor is there any guarantee that new innovations and advancements will necessarily produce new jobs as fast as old ones are being lost (as was once thought inevitable). Indeed, we have already seen signs that this simply cannot be counted on.
The problem with all this is not just that extreme inequality is a political problem on its own. It’s that as more and more people are driven out of the economy, the prospects for greater growth are themselves undermined.
Nevertheless, just as wise policies have helped us overcome many of the problems with the Industrial Revolution, Brynjolfsson and McAfee argue that the same can be done with the problems of the Digital Revolution. Specifically, more can be done to ensure that our education systems are geared to the realities and demands of the second machine age; more can be done to ignite and encourage entrepreneurship, which is needed to replace many of the jobs that will be lost; and more can be done to mitigate the inequality caused by the new technology, such as introducing a negative income tax—which preserves a minimal standard of living for all (and keeps people in the economy as consumers), while encouraging all who can to stay in the workforce.
The book is very well-researched, well-written and wisely argued. The authors have taken the facts and the data as they stand, without preconception or political coloring, and have delivered an honest and insightful analysis. Both the bounty and the spread of the second machine age are made apparent, and the proposed approach moving forward is well-measured and judicious. An important book for policy-makers, and the generally curious alike. A full executive summary of this book is available here: http://newbooksinbrief.com/2014/01/28... A podcast discussion of the book will be available soon.
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