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The Second Machine Age: Work, Progress, and…
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The Second Machine Age: Work, Progress, and Prosperity in a Time of… (original 2014; udgave 2016)

af Erik Brynjolfsson (Forfatter)

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6082029,014 (3.87)3
A revolution is under way. 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 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 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.… (mere)
Medlem:FellowWebcredibles
Titel:The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies
Forfattere:Erik Brynjolfsson (Forfatter)
Info:W. W. Norton & Company (2016), Edition: 1, 336 pages
Samlinger:Dit bibliotek
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The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies af Erik Brynjolfsson (2014)

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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. ( )
  aaronarnold | May 11, 2021 |
There were some worthwhile ideas in here, but nothing really novel or deeply insightful, and it could have been communicated in a few pages instead of a book. If you are really interested in TED Talks and feeling important by learning a superficial amount about a new problem and some potential solution, maybe you should read this, but I'd rather actually learn something meaningful and do something with it. ( )
  octal | Jan 1, 2021 |
If you are in the top 10% of a first world country the future is going to be awesome, like you won't believe. More of the same for everyone else, albeit with better free entertainment. My only complaint is that the book gets highly repetitive whenever the authors get over-enthused. ( )
  Paul_S | Dec 23, 2020 |
πολύ διαφωτιστικό, εξαιρετική μετάφραση ( )
  tonisq | Feb 12, 2019 |
Travail et prospérité à l’heure de la révolution technologique
  guyotvillois | Oct 18, 2018 |
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The strength of “The Second Machine Age” is how it weaves macro- and microeconomics with insights from a wide range of other disciplines into an accessible and convincing story.
 
In the Second Machine Age, though, argues Brynjolfsson, “we are beginning to automate a lot more cognitive tasks, a lot more of the control systems that determine what to use that power for. In many cases today artificially intelligent machines can make better decisions than humans.”
 

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A revolution is under way. 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 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 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.

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