The History of Technological Anxiety and the Future of Economic Growth: Is This Time Different? | Mokyr, Vickers, Ziebarth

Joel Mokyr, Chris Vickers, Nicolas L. Ziebarth. 2015. The History of Technological Anxiety and the Future of Economic Growth: Is This Time Different? In Journal of Economic Perspectives, 29(3): 31-50. DOI:10.1257/jep.29.3.31. landing.

Joel Mokyr is Robert H. Strotz Professor of Arts and Sciences and Professor of Economics and History, Northwestern University, Evanston, Illinois.
Chris Vickers is Assistant Professor of Economics, Auburn University, Auburn, Alabama.
Nicolas L. Ziebarth is Assistant Professor of Economics, University of Iowa, Iowa City, Iowa.

tl/dr → No, it is not different this time.
<quote>From our perspective, the more extreme of modern anxieties about long-term, ineradicable technological unemployment, or a widespread lack of meaning because of changes in work patterns seem highly unlikely to come to pass. As has been true now for more than two centuries, technological advance will continue to improve the standard of living in many dramatic and unforeseeable ways. However, fundamental economic principles will continue to operate. Scarcities will still be with us, most notably of time itself. The law of comparative advantage strongly suggests that most workers will still have useful tasks to perform even in an economy where the capacities of robots and automation have increased considerably. </quote>

Abstract

Technology is widely considered the main source of economic progress, but it has also generated cultural anxiety throughout history. The developed world is now suffering from another bout of such angst. Anxieties over technology can take on several forms, and we focus on three of the most prominent concerns. First, there is the concern that technological progress will cause widespread substitution of machines for labor, which in turn could lead to technological unemployment and a further increase in inequality in the short run, even if the long-run effects are beneficial. Second, there has been anxiety over the moral implications of technological process for human welfare, broadly defined. While, during the Industrial Revolution, the worry was about the dehumanizing effects of work, in modern times, perhaps the greater fear is a world where the elimination of work itself is the source of dehumanization. A third concern cuts in the opposite direction, suggesting that the epoch of major technological progress is behind us. Understanding the history of technological anxiety provides perspective on whether this time is truly different. We consider the role of these three anxieties among economists, primarily focusing on the historical period from the late 18th to the early 20th century, and then compare the historical and current manifestations of these three concerns.

Introduction

<quote>

Technology is widely considered the main source of economic progress, but it has also generated cultural anxiety throughout history. From generation to generation, literature has often portrayed technology as alien, incomprehensible, increasingly powerful and threatening, and possibly uncontrollable (Ellul 1967; Winner 1977). The myth of Prometheus is nothing if not a cautionary tale of these uncontrollable effects of technology. In Civilization and its Discontents, Sigmund Freud (1930 [1961], pp. 38–39) assessed what technology has done to homo sapiens, making him into a kind of God with artificial limbs, “a prosthetic God. When he puts on all his auxiliary organs he is truly magnificent; but those organs have not grown onto him and they still give him much trouble at times.”

So it is surely not without precedent that the developed world is now suffering from another bout of such angst. In fact, these worries about technological change have often appeared at times of flagging economic growth. For example, the Great Depression brought the first models of secular stagnation in Alvin Hansen’s 1938 book Full Recovery or Stagnation? Hansen drew on the macro­economic ideas of John Maynard Keynes in fearing that economic growth was over, with population growth and technological innovation exhausted. Keynes was also drawn into the debate and offered a meditation on the future of technology and unemployment in his well-known essay, “Economic Possibilities for our Grandchildren.”

This was originally written as a set of lectures in 1928 after a decade of dismal economic performance in the United Kingdom and then revised in 1930 to incorporate remarks about the Great Depression (Pecchi and Piga 2008, p. 2). Keynes (1930) remained optimistic about the future in the face of staggering unemployment, writing: “We are suffering, not from the rheumatics of old age, but from the growing-pains of over-rapid changes, from the painfulness of readjustment between one economic period and another. The increase of technical efficiency has been taking place faster than we can deal with the problem of labour absorption; the improvement in the standard of life has been a little too quick.” More recently, Winner’s (1977) “Autonomous Technology: Technics-out-of-Control as a Theme in Political Thought” was published during the economic doldrums of the mid and late 1970s. Today, distinguished economists such as Lawrence Summers (2014), in a speech to the National Association of Business Economists, can be heard publicly musing about the possibility of secular stagnation. In his Martin Feldstein lecture, Summers (2013b) discussed a downright “neo-Luddite” (that famous protest movement against technological innovation in nineteenth century England) position on the effects of technology for long-term trends in employment.

Anxieties over technology can take on several forms, and we focus on what we view as three of the most prominent concerns. The first two worries are based on an “optimistic” view that technology will continue to grow and perhaps accelerate. First, one of the most common concerns is that technological progress will cause widespread substitution of machines for labor, which in turn could lead to technological unemployment and a further increase in inequality in the short run, even if the long-run effects are beneficial. Second, there has been anxiety over the moral implications of technological process for human welfare, broadly defined. In the case of the Industrial Revolution, the worry was about the dehumanizing effects of work, particularly the routinized nature of factory labor. In modern times, perhaps the greater fear is a world like that in Kurt Vonnegut’s 1952 novel Player Piano, where the elimination of work itself is the source of dehumanization (for example, Rifkin 1995). As Summers said (as quoted “not perfectly verbatim” in Kaminska 2014), while “[t]he premise of essentially all economics . . . is that leisure is good and work is bad. . . . economics is going to have to find a way to recognize the fundamental human satisfactions that come from making a contribution . . .” A third concern cuts in the opposite direction, suggesting that the epoch of major technological progress is behind us. In recent years, even in the face of seemingly dizzying changes in information technology, pessimists such as Gordon (2012), Vijg (2011), and Cowen (2010) have argued that our greatest worry should be economic and productivity growth that will be too slow because of, for example, insufficient technological progress in the face of “headwinds” facing western economies. Some of these so-called “headwinds,” including slow productivity and population growth, formed the basis of Hansen’s (1939) secular stagnation hypothesis. The argument of this paper is that these worries are not new to the modern era and that understanding the history provides perspective on whether this time is truly different. The next section of the paper considers the role of these three anxieties among economists, primarily focusing on the historical period from the late 18th to the early 20th century, while the final section offers some comparisons between the historical and current manifestations of these three concerns.

</quote>

Mentions

  • in the Rawlsian sense
  • “headwinds” which is apparently a colorful metaphor in the argot.
  • neo-Luddite
  • stagnation
  • Concerns
    1. Short-Term Disruption, Long-Term Benefits
    2. Technology and the Alienation of Labor
    3. Historical Perspectives on a Horizon for Technological Progress
  • Prognostication
    • Technology and the End of Work?
    • Technology and the Characteristics of Work
    • The Technological Horizon
  • Amara’s Law
    • <quote>We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.</quote>
    • Roy Amara,
      • systems engineer
      • president, Institute for the Future:
        • an idea shop
        • for-profit

Referenced

  • John Maynard Keynes; Economic Possibilities for our Grandchildren; an essay; 1930.

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Via: backfill

Why Are There Still So Many Jobs? The History and Future of Workplace Automation | David H. Autor

David H. Autor (MIT). 2015. Why Are There Still So Many Jobs? The History and Future of Workplace Automation. In Journal of Economic Perspectives, 29(3): 3-30. DOI:10.1257/jep.29.3.3; landing.

David H. Autor is Professor of Economics, Massachusetts Institute of Technology, Cambridge, Massachusetts; ex-Editor of the Journal of Economic Perspectives, 2009 to 2014.

tl;dr → automation creates more manual work around it; journalist boosters overstate the contribution of automation; polarization won’t continue.

Abstract

In this essay, I begin by identifying the reasons that automation has not wiped out a majority of jobs over the decades and centuries. Automation does indeed substitute for labor—as it is typically intended to do. However, automation also complements labor, raises output in ways that leads to higher demand for labor, and interacts with adjustments in labor supply. Journalists and even expert commentators tend to overstate the extent of machine substitution for human labor and ignore the strong complementarities between automation and labor that increase productivity, raise earnings, and augment demand for labor. Changes in technology do alter the types of jobs available and what those jobs pay. In the last few decades, one noticeable change has been a “polarization” of the labor market, in which wage gains went disproportionately to those at the top and at the bottom of the income and skill distribution, not to those in the middle; however, I also argue, this polarization is unlikely to continue very far into future. The final section of this paper reflects on how recent and future advances in artificial intelligence and robotics should shape our thinking about the likely trajectory of occupational change and employment growth. I argue that the interplay between machine and human comparative advantage allows computers to substitute for workers in performing routine, codifiable tasks while amplifying the comparative advantage of workers in supplying problem-solving skills, adaptability, and creativity.

Introduction

<quote>

There have been periodic warnings in the last two centuries that automation and new technology were going to wipe out large numbers of middle class jobs. The best-known early example is the Luddite movement of the early 19th century, in which a group of English textile artisans protested the automation of textile production by seeking to destroy some of the machines. A lesser-known but more recent example is the concern over “The Automation Jobless,” as they were called in the title of a TIME magazine story of February 24, 1961:

The number of jobs lost to more efficient machines is only part of the problem. What worries many job experts more is that automation may prevent the economy from creating enough new jobs. . . . Throughout industry, the trend has been to bigger production with a smaller work force. . . . Many of the losses in factory jobs have been countered by an increase in the service industries or in office jobs. But automation is beginning to move in and eliminate office jobs too. . . . In the past, new industries hired far more people than those they put out of business. But this is not true of many of today’s new industries. . . . Today’s new industries have comparatively few jobs for the unskilled or semiskilled, just the class of workers whose jobs are being eliminated by automation.

Concerns over automation and joblessness during the 1950s and early 1960s were strong enough that in 1964, President Lyndon B. Johnson empaneled a “Blue-Ribbon National Commission on Technology, Automation, and Economic Progress” to confront the productivity problem of that period—specifically, the problem that productivity was rising so fast it might outstrip demand for labor. The commission ultimately concluded that automation did not threaten employment: “Thus technological change (along with other forms of economic change) is an important determinant of the precise places, industries, and people affected by unemployment. But the general level of demand for goods and services is by far the most important factor determining how many are affected, how long they stay unemployed, and how hard it is for new entrants to the labor market to find jobs. The basic fact is that technology eliminates jobs, not work” (Bowen 1966, p. 9). However, the Commission took the reality of technological disruption as severe enough that it recommended, as one newspaper (The Herald Post 1966) reported, “a guaranteed minimum income for each family; using the government as the employer of last resort for the hard core jobless; two years of free education in either community or vocational colleges; a fully administered federal employment service, and individual Federal Reserve Bank sponsorship in area economic development free from the Fed’s national headquarters.”

Such concerns have recently regained prominence. In their widely discussed book The Second Machine Age, MIT scholars Erik Brynjolfsson and Andrew McAfee (2014, p. 11) offer an unsettling picture of the likely effects of automation on employment:

Rapid and accelerating digitization is likely to bring economic rather than environmental disruption, stemming from the fact that as computers get more powerful, companies have less need for some kinds of workers. Technological progress is going to leave behind some people, perhaps even a lot of people, as it races ahead. As we’ll demonstrate, there’s never been a better time to be a worker with special skills or the right education, because these people can use technology to create and capture value. However, there’s never been a worse time to be a worker with only ‘ordinary’ skills and abilities to offer, because computers, robots, and other digital technologies are acquiring these skills and abilities at an extraordinary rate.

Clearly, the past two centuries of automation and technological progress have not made human labor obsolete: the employment‐to‐population ratio rose during the 20th century even as women moved from home to market; and although the unemployment rate fluctuates cyclically, there is no apparent long-run increase. But those concerned about automation and employment are quick to point out that past interactions between automation and employment cannot settle arguments about how these elements might interact in the future: in particular, the emergence of greatly improved computing power, artificial intelligence, and robotics raises the possibility of replacing labor on a scale not previously observed. There is no fundamental economic law that guarantees every adult will be able to earn a living solely on the basis of sound mind and good character. Whatever the future holds, the present clearly offers a resurgence of automation anxiety (Akst 2013).

In this essay, I begin by identifying the reasons that automation has not wiped out a majority of jobs over the decades and centuries. Automation does indeed substitute for labor—as it is typically intended to do. However, automation also complements labor, raises output in ways that lead to higher demand for labor, and interacts with adjustments in labor supply. Indeed, a key observation of the paper is that journalists and even expert commentators tend to overstate the extent of machine substitution for human labor and ignore the strong complementarities between automation and labor that increase productivity, raise earnings, and augment demand for labor.

Changes in technology do alter the types of jobs available and what those jobs pay. In the last few decades, one noticeable change has been “polarization” of the labor market, in which wage gains went disproportionately to those at the top and at the bottom of the income and skill distribution, not to those in the middle. I will offer some evidence on this phenomenon. However, I will also argue that this polarization is unlikely to continue very far into the foreseeable future.

The final section of this paper reflects on how recent and future advances in artificial intelligence and robotics should shape our thinking about the likely trajectory of occupational change and employment growth. I argue that the interplay between machine and human comparative advantage allows computers to substitute for workers in performing routine, codifiable tasks while amplifying the comparative advantage of workers in supplying problem-solving skills, adaptability, and creativity. The frontier of automation is rapidly advancing, and the challenges to substituting machines for workers in tasks requiring flexibility, judgment, and common sense remain immense. In many cases, machines both substitute for and complement human labor. Focusing only on what is lost misses a central economic mechanism by which automation affect the demand for labor: raising the value of the tasks that workers uniquely supply.

</quote>

Mentions

  • yes

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Via: backfill.

Is a Cambrian Explosion Coming for Robotics? I Gill Pratt

Gill A. Pratt (DARPA). 2015. Is a Cambrian Explosion Coming for Robotics? In Journal of Economic Perspectives, 29(3): 51-60. http://dx.doi.org/10.1257/jep.29.3.51. landing.

Gill A. Pratt will be stepping down [2015-09] from his position as a Program Manager of the Defense Advanced Research Projects Agency (DARPA), Arlington, Virginia, where he oversaw the DARPA Robotics Challenge and several other programs in robotics while on leave from the faculty of Franklin W. Olin College, Needham, Massachusetts.

Abstract

About half a billion years ago, life on earth experienced a short period of very rapid diversification called the “Cambrian Explosion.” Many theories have been proposed for the cause of the Cambrian Explosion, one of the most provocative being the evolution of vision, allowing animals to dramatically increase their ability to hunt and find mates. Today, technological developments on several fronts are fomenting a similar explosion in the diversification and applicability of robotics. Many of the base hardware technologies on which robots depend—particularly computing, data storage, and communications—have been improving at exponential growth rates. Two newly blossoming technologies—”Cloud Robotics” and “Deep Learning”—could leverage these base technologies in a virtuous cycle of explosive growth. I examine some key technologies contributing to the present excitement in the robotics field. As with other technological developments, there has been a significant uptick in concerns about the societal implication of robotics and artificial intelligence. Thus, I offer some thoughts about how robotics may affect the economy and some ways to address potential difficulties.

Introduction

<quote>

About half a billion years ago, life on earth experienced a short period of very rapid diversification called the “Cambrian Explosion.” Many theories have been proposed for the cause of the Cambrian Explosion, with one of the most provocative being the evolution of vision, which allowed animals to dramatically increase their ability to hunt and find mates (for discussion, see Parker 2003). Today, technological developments on several fronts are fomenting a similar explosion in the diversification and applicability of robotics. Many of the base hardware technologies on which robots depend—particularly computing, data storage, and communications—have been improving at exponential growth rates. Two newly blossoming technologies—“Cloud Robotics” and “Deep Learning”—could leverage these base technologies in a virtuous cycle of explosive growth. In Cloud Robotics — a term coined by James Kuffner (2010) — every robot learns from the experiences of all robots, which leads to rapid growth of robot competence, particularly as the number of robots grows. Deep Learning algorithms are a method for robots to learn and generalize their associations based on very large (and often cloud-based) “training sets” that typically include millions of examples. Interestingly, Li (2014) noted that one of the robotic capabilities recently enabled by these combined technologies is vision—the same capability that may have played a leading role in the Cambrian Explosion.

</quote>

Mentions

  • A model of technology adoption is presented, page 7.
    Technology creates more supply in some areas, creates new demand in other areas; rinse&repeat; goodness follows.
  • Human services cost more because they entail (human) time which cannot be repleased or scaled.  Hence the craft economy; the services economy.
  • When the robots arrive, do “we” use capitalism or communism to distribute the effusion of abundant bounty?
  • The Personal Preferences Information Economy
    <quote>Internet companies that had their start producing computer tools like search, email, maps and others have monetized the personal preferences about their users gathered by the tools themselves—which are typically given away “for free.” The gathered information is then sold to advertisers who use it to target individuals most likely to purchase specific goods. The business of these companies is fundamentally the arbitrage of personal preference information. Many people today don’t realize the value of their personal preferences, although the substantial profits of the companies that gather and sell such information makes clear its value.</quote>
  • What’s Holding Back Robots?, page 10
    not stated

    • only time will tell
    • the changes will be profound
  • (ahem) “they” don’t yet do enough to earn “their” keep..

Technology Drivers

  1. Moore’s Law
  2. 3D printing
  3. Energy Storage (batteries)
  4. Power management (power density, efficiency)
  5. Packet Radio (wireless, WiFi)
  6. Data Storage
  7. Computation (see #1, something about “embassingly parallel”)

Big Ideas

  1. Memory-based automomy
    delegate to memory in lieu of algorithms
  2. High-Speed experience sharing
    pubsub
  3. Learning from Imagination
    on-device simulation of the external world
  4. Learning from people
    something about social media, trawling photos & videos

Referenced

References

Via: backfill

Robots, Employment, Recession, Labor Economics

General opinement and prognostication by academics and para-academics since 2009.

Recent Promotions

  • Bernard Condon and Paul Wiseman; AP IMPACT: Recession, tech kill middle-class jobs; Associated Press, Syndicated into Yahoo! News; 2013-01-23.
    Mentions:

    • 3-part series (this is tranche 1)
    • Andrew McAfee
      • Principal research scientist (title; an academic)
      • Center for Digital Business at the Massachusetts Institute of Technology
      • Co-author of Race Against the Machine (with Erik Brynjolfsson)
    • Martin Ford
    • Alluded to (poorly or uncited works)
      • Henry Siu  (University of British Columbia), and Nir Jaimovich (Duke University); (uncited) Working Paper; 2010-08.
      • Maarten Goos, University of Leuven in Belgium.
      • Unnamed academics; University of British Columbia and York University in Toronto; study in the area of economics, perhaps labor economics; 2011.
      • Unnamed academics; Hitotsubashi University in Tokyo; 2009; a study in labor economics on the period 2000-2005.
      • The Hackett Group; background factoids.
      • John Haltiwanger and two others (academics); University of Maryland; a study in the labor economics; (private) job caused by young startups.
      • Eleanor Choi and James Spletzer; United States, Department of Labor; 2012-03; a study on hiring  since 1990 (“the 1990s”).
    • Quoted
      • Joseph Stiglitz, Columbia University; gave a color quote: “It doesn’t have political appeal to say the reason we have a problem is we’re so successful in technology. There’s no enemy there.”
      • David Autor, MIT; studies labor economics; gave a color quote: “[Technology causes] cheaper products and cool services, but if you lose your job, that is slim compensation.”
      • Jeff Connally, CEO, CMIT Solutions; a consultancy; gave a color quote: “[In the old days — say, 10 years ago — ] you’d need an assistant pretty early to coordinate everything — or you’d pay a huge opportunity cost for the entrepreneur or the president to set up a meeting, [now technology means] you can look at your calendar and everybody else’s calendar and — bing! — you’ve set up a meeting. [so no assistant gets hired.]“
      • Andrew Schrage, Money Crashers, a finance advice web site; started 2009; has 1 partner, 1 freelance (non-)employee; gave a color quote: “Had I not had access to cloud computing and outsourcing, I estimate that I would have needed 5-10 employees to begin this venture,” Schrage says. “I doubt I would have been able to launch my business.”
      • Peter Lindert, University of California, Davis; an economist; gave a background color recitedin the article “[he] says [that] the computer is more destructive than innovations in the Industrial Revolution because the pace at which it is upending industries makes it hard for people to adapt.”
    • Original Reporting (findings declared)
      • Technology eliminates jobs
      • The vulnerable are doing repetitive tasks; also task “jugglers” (managers)
      • Some numerology about greater earnings than before
      • Startups are job growth; but they need less admin & overhead workers.
      • Self-serve is a trend
      • Union rules won’t help; no country prohibits replacing people with machines
    • Exemplars & Stories
      • Webb Wheel Products; Dwayne Ricketts, President; Cullman AL
      • Sunbird Engineering, Hong Kong; plants in Dongguan; Bill Pike, CEO.
      • Foxconn Technology Group, CN.
      • Roshanne Redmond, a former project manager at a commercial real estate developer; not clear why she is cited except via the former concept
    • Promotions & followons
  • Martin Ford; Paul Krugman is Wrong about the Rise of the Robots; In His Blog; 2013-01-18.
  • ; The End of Labor: How to Protect Workers From the Rise of Robots; In The Atlantic; 2013-01-14.
    Assistant professor of finance, Stony Brook University Blog: Noahpinion.
    Mentions:

    • Where is the money going? => China, or robots
    • Redistribution against the machine => EITC, SBIC, SARBOX, light paternalism, capital portfolio ownership, dividends & capital gains, socialist land reforms via stock ownership
    • Memorable Quote:
      • “the great Chinese Labor Dump”
    • References:
  • James Altucher; 10 Reasons Why 2013 Will Be The Year You Quit Your Job; In TechCrunch; 2013-01-12.
    Summary:

    • His usual vapid selfhelp exuberance
  • Editor; Has the ideas machine broken down?; In The Economist; 2013-01-12.
    Mentions

    • Peter Thiel
      credited as:

      • A founder of PayPal, an internet payment company
      • First outside investor in Facebook, a social network
    • Tyler Cowen
      credited as:

    • Robert Gordon
      credited as:

      • An economist at Northwestern University
    • Charles Jones
      credited as:

      • An economist at Stanford University
      • Uncited, unnamed publication circa 2002
        • Studying the period 1950-1993
        • Measured research intensity defined as the share of the workforce labouring in idea-generating industries.
        • For the period (43 years), 80% of income growth was due to rising educational attainment and research intensity.
        • The share of the American economy given over to R&D has expanded by a third since 1975, to almost 3%
    • Pierre Azoulay
      credited as:

      • Of MIT
      • With Benjamin Jones, a study
    • Benjamin Jones
      credited as:

      • Of Northwestern University
      • Uncited, unnamed publication with Pierry Azoulay
        • Find that, though there are more people in research, they are doing less good.
        • Claim: 1950 R&D worker was 7x more productive than a 2000 R&D worker.
        • The burden of knowledge holds them back
        • Age at first innovation (patent?) rose by 1 year 1950-2000.
    • Robert Solow
      credit as:

      • a growth theorist
      • 1987 pithy quip: “you can see the computer age everywhere but in the productivity statistics”
    • Susanto Basu
      credit as:

      • Of Boston College
      • Paper with Jon Fernald
    • John Fernald
      credited as:

      • Of the San Francisco Federal Reserve
      • Uncited, unnamed publication with Susanto Basu
        • Asserts the leg in productivity improvement of IT is 5-15 years.
        • The 2004 drop in productivity was “pre Google” and “pre web”
    • Ray Kurzweil
      credited as

    • Erik Brynjolfsson
      credited as:

    • Andrew McAfee
      credited as:

    • William Nordhaus
      credited as:

      • Of Yale University
      • An uncited statement or publication
        • A declaration that the productivity slowdown starting in the 1970s radiated outwards from the most energy-intensive sectors, a product of the decade’s oil shocks.
    • Paul Romer
      credited as:

      • Then at the University of Rochester
      • An unnamed publication circa 1987
        • Declared whimsical
        • Asserted that with more workers available in developing countries, cutting labour costs in rich ones became less important. Investment in productivity was thus sidelined
        • Evidence offered [some] economic historians comparing 19th-century Britain with America commonly credit relative labour scarcity in America with driving forward the capital-intense and highly productive “American system” of manufacturing
    • Daron Acemoglu
      credited as:

      • Of MIT.
      • Uncited publication with Gino Gancia, Fabrizio Zilibotti.
    • Gino Gancia
      credited as:

      • Of CREi, an economics-research center in Barcelona.
      • Uncited publication with Daron Acemoglu, Fabrizio Zilibotti.
    • Fabrizio Zilibotti
      credited as:

      • Of the University of Zurich
      • Uncited publication with Daron Acemoglu, Gino Gancia
    • Daron Acemoglu, Gino Gancia, Fabrizio Zilibotti
      • Uncited publication
      • Have built a model to vary labor availability & cost against productivity.
      • Asserted results:
        • Initially
          • Firms in rich countries shipping low-skill tasks abroad when offshoring costs little
        • Early
          • This drives apart the wages of skilled and unskilled workers at home.
        • Asymptotic Steady State
          • Offshoring raises wages in less-skilled countries
          • Over time innovation at home more is more valuable
          • Workers at home are in greater demand.
          • The income distribution narrows
          • The economy comes to look more like the post-second-world-war period than the 1970s and their aftermath.
    • Economic Theory & Background (recitals)
      • Growth Theory
        • Extensive growth is a matter of adding more and/or better labor, capital and resources.
        • Intensive growth is powered by the discovery of ever better ways to use workers and resources.
      • Growth accounting
        • Technology is the bit left over after calculating the effect on GDP of things like labor, capital and education
      • Full exploitation of a technology takes more than twenty and maybe fifty years.
        • Containerized shipping: beyond fifty years.
        • Steam engine: beyond forty years.
      • Moore’s Law
        • “the ability to get calculations out of silicon” doubles every 18 months
      • Claims
        • The economy of 2014 is more regulated than it was in 1914.
        • Cleaner operations (environment) is not captured in GDP
        • There is no current “Apollo Program” subsidy to the technology industry
        • Energy is more expensive “now” than it was “then”
        • Sectors immune to productivity improvements of IT (no market pressures)
          • Health Care
          • Education
          • Government
    • Exemplars & Parables
      • Take your own kitchen; cooking is the same as it ever was.
      • Sailboats
      • Railroads
      • Airplanes
      • Medicine & disease; improved sanitation vs molecular medicine
      • Containerized (railroad) shipping.
      • Steam engine
      • Driverless cars
        • DARPA 2004 => zero entrants completed the 240 km/150 miles
        • Google driverless cars; 2012-08 => 500 Mm/310 kmiles
    • Argument
      • Science fiction isn’t a binding commitment on the future roadmap trajectory; it is a celebration of current thinking.
  • Paul Kedrosky; 2013 : WHAT *SHOULD* WE BE WORRIED ABOUT?; In Edge; 2013 (2013-01, but substantially undated).
    Summary: something incoherent and discursive about path dependence and installed base effects; institutions which perform a function for historical reasons but for no other reasons; he uses the parable of the fire department (“a fire department” “all fire departments”) only receive 20% of calls for actual fires, the rest are for (um) “everything but fires.”
  • Jon Evans; What If Technology Is Destroying Jobs Faster Than It Creates Them?; In TechCrunch; 2011-11-12.
    Summary: substantially pointers to other work formatted together with prose

  • N.V. (?); Difference Engine: Luddite Legacy; In The Economist; 2011-11-04.
    Mentions

    • Ned Ludd
      credited as:

      • A legendary hero of the English proletariat
      • Smashed the mechanical knitting looms being introduced at the time for fear of losing their jobs.
    • Laura D’Andrea Tyson
      credited as:

      • An economist at University of California, Berkeley
      • Was chairman of the Council of Economic Advisers during the Clinton administration.
      • Attributed with vague claims about the years it would take to close gaps in employment after the 2008 recession; “yawning gaps” and so forth.
    • Douglas Rushkoff
      credited as:

      • Media theorist
      • Author Program or Be Programmed
      • Author Life Inc.
      • Not clear why he’s in this article
      • Attributed with the retort “nothing in particular” on a hypothetical basis; relative to the concept of replacing “Dilbert”-type white color jobs lost recently. Rhetorically: “What is in store for the Dilberts of today?”
    • Jeremy Rifkin
      credited as:

      • A social critic
      • Author The End of Work of 1995
      • Quote: “In the years ahead more sophisticated software technologies are going to bring civilisation ever closer to a near-workerless world.”
    • Martin Ford
      credited as:

    • Erik Brynjolfsson and Andrew McAfee
      credited as:

      • From the Massachusetts Institute of Technology
      • Authors of Race Against the Machine
      • Editorial claim <quote>But the authors’ perspective is from an ivory tower rather than from the hands-on world of creating start-ups in Silicon Valley. Their proposals for reform, while spot on in principle, expect rather a lot from the political system and other vested interests.</quote>
    • Marina Gorbis
      credited as:

      • Of the Institute for the Future, an independent think-tank in Palo Alto, CA,
      • Attributed with a belief that people will never be replaced (Why not! “Up with people!”)
    • Economic Theory & Background
      • The Luddite Fallacy
        Assumptions:

        • one is that machines are tools used by workers to increase their productivity
        • the majority of workers are capable of becoming machine operators
    • Parables & Color
      • Walter Reuther vs Henry Ford on robots
        • “Walter, how are you going to get those robots to pay your union dues”
        • “Henry, how are you going to get them to buy your cars?”
      • The Growth Story
        • Advancing technology exist, in the form of automation and innovation, increases productivity.
        • This, in turn, causes prices to fall, demand to rise, more workers to be hired, and the economy to grow.
      • Sectors subject to low-skill automation and software automation
        • First move the work to India, then to software
        • Radiology on X-ray slides looking for tumors
        • Legal discovery looking for terms
        • Generally & also: workers who perform data-analytics, business-intelligence, decision-making.
      • Families earning their living, paying their rent, putting food on their table; though “Such activities may not create a new wave of billion-dollar businesses”
        • Amazon
        • eBay
        • Apple App Store
        • Google Android Marketplace
  • ; Race Against the Machine

Background

There is a whole stable of these books now listed on Amazon in the “related work” trough…