Can We Foresee the Future? Explaining and Predicting Cultural Change | SPSP (Varnum & Grossman)

Igor Grossmann, Michael E. W. Varnum in their roles as; editor of the blog of Society for Personality and Social Psychology) Can We Foresee the Future? Explaining and Predicting Cultural Change; In That Certain Blog; 2017-10-17.

tl;dr → Yes. Betteridge’s Law fails.
ahem → No. Betteridge’s Law holds. Surely no one can know the future, and anyone who says they can is either high or a fool, perhaps both. One can problematize quibble on the epistemology sense of the word “to know,” if you think you have time for that sort of thing.


Michael E. W. Varnum, Igor Grossmann. (2017). Cultural change: The how and the why. In Perspectives on Psychological Science. DOI:10.1177/1745691617699971


The promotional build running up to the release of that certain sequel (2017) to the movie Blade Runner (1982) which is in turn based on a short novel by Philip K. Dick entitled Do Androids Dream of Electric Sheep? (Doubleday 1968) [Answer: No (whereas Androids, after the Ice Cream Sandwich release, are functionally people too, being as they feel pain and love, as eloquently and forcefully testified by Rutger Hauer in a monologue performed so memorably on that dark & rainy night), again, Betteridge's Law holds, c.f. Jimi Wales' Wiki, Jimi Wales' Wiki].


A means & method for producing new predictions, which is better.

  • Uniqueness.
  • Rigorous
    • Theory-Driven [not Theory-Laden].
    • Testable [falsifiable]
  • Empirical.
    • Documentation
      Whereas sociology is either slow journalism [documentation] or activism [promotion] in service to personal ideals.
    • Repeatable
      Replicatability is not claimed. It’s a best practice for high fidelity journalism.

<quote>What is unique is a rigorous theory-driven attempt to not only document but to test explanations for patterns of societal change empirically </quote>

The enumerated [cultural] changes are features of the ecology [our ecologies].
<quote>This emerging work suggests <snide>asserts</snide> that among the most powerful contributors to cultural changes in areas like individualism, gender equality, and happiness are shifts in essential features of our ecologies.</quote>
This schema was shown in animal behavior; now it is replicated with people [our people].
<quote>The idea that variations in ecological dimensions and cues like scarcity or population density might be linked to behavioral adaptations has been widely explored in animal kingdom, and recently started to gain prominence as a way to explain variations in human behavior.</quote>

  • Ellis, Bianchi, Griskevicius, & Frankenhuis, 2017.
  • Sng, Neuberg, Varnum, & Kenrick, 2017.


  • It’s an “implications” paper:
    <quote>but also has fundamental implications for psychometric assumptions and replicability in psychological science.</quote>
  • <quote>Neither experts nor lay people do much better than chance
    as “proven” in: Tetlock, 2006; Tetlock & Gardner, 2016.</quote>
  • <quote>psychological phenomena unfold within a temporal context,</quote> → <fancier>events occur over spans of time; therefor psychological events occur over spans of time<fancier>,
    the insight is attributed to Kurt Lewin and Lev Vygotsky; unnamed “other theorists.”
  • ngrams, as mentioned in Google Books.
  • cross-lagged statistical models
  • cross-correlation functions
  • tests of Granger causality
  • SES (Socio-Economic Status; i.e. Marx-archetype class.1
  • The Misery Index, of [NAME] Okun.
  • ecological framework
  • big data
  • econometric tools
  • insights from machine learning
  • predictive science of cultural change.
  • emerging science of cultural change
  • predictive psychological science (Yarkoni & Westfall, 2017)


Individualism ↔ Collectivism
A focus on uniqueness and independence and emphasis of self-expression (or not.
Gender Equality
Obvious: equality between the [two] genders, which are named as: Male and Female (Female and Male).
Obvious: that buddhist thing; as evidenced in self-attestation surveys.
The WEIRD Population
The white American middle-class college students.

  • Western,
  • Educated,
  • Industrialized,
  • Rich,
  • Democratic.

References (at least):

  • Joseph Nenrich, Steven J. Heine, Ara Norenzayan; The Weirdest People in the World; In Some Journal, Surely; 2009-03-05; 58 pages (23,703 words).
    Cited herein: Henrich, Heine, & Norenzayan, 2010.
    Teaser: How representative are experimental findings from American university students? What do we really know about human psychology?


  • Isaac Asimov, boffo.
    Honorific: <quote>the seminal science fiction author — inventor of the fictional discipline of psycho-history.</quote>
  • Gerd Hofstede, documentarian.
  • Kurt Lewin, theorist.
  • Nostradamus; boffo.
    Opus: Quatrains, many years ago.
  • Lev Vygotsky, theorist.



  • individualism,
  • gender equality,
  • happiness.


  • model cultural change
    on a large scale.
  • using data,
    using cross-temporal data
  • using theory or theories,
    using theories derived from behavioral ecology.
  • “can usher in” [what?]
  • a new era in research,
    a new era in research social psychological and personality research.

unclear… if this means more better hard Sci-Fi or more sooth can be said:

  • more voluminous,
  • more accurate,
  • more relevant,
  • more pithy,
  • more cogent,
  • more better prognostications.


Method of Prognostication
  • ecological framework,
  • big data,
  • econometric tools.


far future: 2047 → 2117.


Obtain the Salubrious Result.

  • society,
  • the economy,
  • politics.

Events in the areas of…

  • scientists,
    specifically: behavioral scientists,
  • policy makers,
    specifically: [hired] regulators and [elected] politicians.
  • anyone,
    as such: the laity, the general public.
Charlatans, Experts
  • pundits,
  • economists,
  • intelligence analysts,
    generally, any and all analysts.
Drift, across time, same place
Results in social science are idiosyncratic and perishable. To wit:
<quote>There is no guarantee that the structure of psychological constructs (and their relationship to each other) remains consistent over time – a critical insight for anybody studying individual differences or the interaction of the social context and personality.</quote>
Drift, across time, different places
Results in social science are idiosyncratic to the place and perishable. To wit:
Second, in behavioral and management sciences that focus on cross-cultural comparisons, we need to ensure that our measurements are made contemporaneously.</quote>
Untestable, uninferrable
Documentation practices produces records as evidence; such cannot be used to as inputs to a reasoning process. To wit:
<quote><snip/> for those interested in the ways socio-cultural context impacts human minds, the new field of cultural change enables better tests of theories regarding the origin and evolution of cross-cultural variations than the cross-sectional approaches that are currently standard in the field. Time series data permit stronger inferences regarding the causes of cultural variation than is possible from datasets where putative causes and outcomes are measured only once and at the same time.</quote>
Implications, there are implications; this is important work.
<quote><snip/> have some implications for debates about replicability.
This is not to say that cultural change is likely the explanation for many or most failures to replicate previous findings, but when there is a large temporal remove between the original studies and replication attempts, it may be wise to consider this when interpreting any discrepancies or changes in effect sizes.

  • Greenfield, 2017; Varnum & Grossmann, 2017.
Drift, invalid population sampling
Whereas psychology “research” is done on The WEIRD Population, the results are incorrect.
<quote>Most samples we collect are “WEIRD,” consisting largely of white American middle-class college students who it turns out are not psychologically representative of humanity. But perhaps more importantly emerging insights from the cross-temporal study of psychological processes suggest <snide>assert<snide> that as psychologists, whether we are aware of it or not, we are studying a moving target.


  • Changes in baby naming practices in the US from the 1880’s to the 2010s and predictions for future trends through 2030.
    from Grossmann and Varnum (2015).
  • Voter turnout
  • Twenge & Campbell
  • …others…


Self-esteem, narcissism, and intelligence have increased in Western societies since 1980.
<quote>over the past several decades<quote>

  • Twenge & Campbell, 2001.
  • Twenge, Konrath, Foster, Campbell, & Bushman, 2008.
  • Flynn, 1984.
  • Trahan, Stuebing, Fletcher & Hiscock, 2014.
Social capital has declined since [sometime]
…as evidenced in e.g. involvement in civic organizations and voter turn-out.

  • Putnam, 1995.
  • Putnam, 2000.
Gender equality has risen, in “The West,” since 1950.
<quote>over the past 60-70 years.<quote>

  • Varnum & Grossmann, 2016.
Individualist attitudes, practices, and relational patterns have increased in 60+ countries
  • Grossmann & Varnum, 2015.
  • Santos, Varnum & Grossmann, 2017.
Changes in The Environmemt, generalized, cause changes in Behavior, generalized;
This occurs in individuals and composes into groups.
><quote>The idea that variations in ecological dimensions and cues like scarcity or population density might be linked to behavioral adaptations has been widely explored in animal kingdom, and recently started to gain prominence as a way to explain variations in human behavior.</quote>

  • Ellis, Bianchi, Griskevicius, & Frankenhuis, 2017.
  • Sng, Neuberg, Varnum, & Kenrick, 2017.
White-collar employment causes individualism.
White-collar employment correlates with individualism.
<quote><snip/>a shift toward greater affluence and white- (vs. blue) collar occupations was the most robust ecological predictor of levels of individualism over time, further shifts in levels of SES consistently preceded changes in levels of individualism in America – a finding that has since been extended and cross-validated by our team in a study examining the rise of individualism around the globe.</quote>

  • Grossmann & Varnum, 2015.
  • Santos, Varnum, & Grossmann, 2017.
Disease causes sexism.
The disease level cause the sexism level.
Infectious disease level decline causes the gender equaltiy increase.
<quote>It turned out that a decline in levels of infectious disease was the most robust factor predictor of rising gender equality, a finding we were able to replicate in the UK, and in both societies we found evidence that changes in pathogen levels preceded shifts in gender equality</quote>

  • Varnum & Grossmann, 2016.
Happiness has decreased in the United States since 1800.
<quote>Research examining affect in books and newspaper articles over a 200-year span shows a long-term decline in American happiness.</quote>

  • Iliev, Hoover, Dehghani, & Axelrod, 2016.
Misery causes inverse happiness
Whereas well-being is functionally the same as happiness, the Misery Index measures inverse happiness.
<quote>Levels of well-being in [these] studies appeared linked to Okun’s Misery Index, an economic indicator that combines unemployment and inflation rates, consistent with the idea that scarcity or abundance of resources matters for happiness.</quote>

  • Iliev et al., 2016.
Only the level of envy matters.
Whereas well-being is functionally the same as happiness,
and envy being a manifestation of differential happiness,
and happiness decreases as inequality increases;
thus absolute levels of happiness do not matter,
the differences between the happiness levels matters,
the level of envy matters.
<quote>Another study exploring the cause of changes in levels of well-being over time in the US found strong links to levels of economic inequality, suggesting <snide>asserting without proof</snide> that happiness decreases as inequality increases, suggesting<snide>asserting</snide> that not only absolute levels of resources but their distribution in an environment (what behavioral ecologists call “resource patchiness”) help to explain changes in well-being over time.</quote>

  • Oishi, Kesebir, & Diener, 2011.


  • Ellis, B. J., Bianchi, J., Griskevicius, V., & Frankenhuis, W. E. (2017). Beyond risk and protective factors: An adaptation-based approach to resilience. Perspectives on Psychological Science, 12(4), 561–587. DOI:10.1177/1745691617693054
  • Flynn, J. R. (1987). Massive IQ gains in 14 nations: What IQ tests really measure. Psychological Bulletin, 101(2), 171 – 191. DOI:10.1037/0033-2909.101.2.171.
  • Greenfield, P. M. (2017). Cultural change over time: Why replicability should not be the gold standard in psychological science. Perspectives on Psychological Science, 12(5), 762-771. DOI:10.1177/1745691617707314
  • Grossmann, I. & Varnum, M. E. W. (2015). Social structure, infectious diseases, disasters, secularism, and cultural change in America. Psychological Science, 26(3) 311-324. DOI:10.1177/0956797614563765
  • Henrich, J., Heine, S.J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33, 62–135. doi:10.1017/S0140525X0999152X
  • Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and organizations: Software of the mind (revised and expanded). New York, NY: McGraw-Hill I
  • liev, R., Hoover, J., Dehghani, M., & Axelrod, R. (2016). Linguistic positivity in historical texts reflects dynamic environmental and psychological factors. Proceedings of the National Academy of Sciencesof the U.S.A, 113(49), 7871-7879. DOI:10.1073/pnas.1612058113
  • Oishi, S., Kesebir, S., & Diener, E. (2011). Income inequality and happiness. Psychological science, 22(9), 1095-1100. DOI:10.1177/0956797611417262
  • Putnam, R. D. (1995). Bowling alone: America’s declining social capital. Journal of Democracy, 6(1), 65-78.
  • Putnam, R. D. (2000). Bowling alone: America’s declining social capital. In Culture and politics (pp. 223-234). Palgrave Macmillan US.
  • Santos, H. C., Varnum, M. E. W., Grossmann, I. (2017). Global increases in individualism. Psychological Science. DOI:10.1177/0956797617700622
  • Sng, O., Neuberg, S. L., Varnum, M. E., & Kenrick, D. T. (2017). The crowded life is a slow life: Population density and life history strategy. Journal of Personality and Social Psychology, 112(5), 736 754. DOI:10.1037/pspi0000086
  • Tetlock, P. E. (2006). Expert Political Judgment. How Good Is It? How Can We Know? Princeton, NJ: Princeton University Press.
  • Tetlock, P. E., & Gardner, D. Superforecasting: The art and science of prediction. Broadway Books.
  • Trahan, L. H., Stuebing, K. K., Fletcher, J. M., & Hiscock, M. (2014). The Flynn effect: A meta-analysis. Psychological Bulletin, 140(5), 1332 – 1360. DOI:10.1037/a0037173
  • Twenge, J. M., & Campbell, W. K. (2001). Age and birth cohort differences in self-esteem: A cross-temporal meta-analysis. Personality and Social Psychology Review, 5(4), 321-344. DOI:10.1207/S15327957PSPR0504_3
  • Twenge, J. M., Konrath, S., Foster, J. D., Keith Campbell, W., & Bushman, B. J. (2008). Egos inflating over time: A cross-temporal meta-analysis of the Narcissistic Personality Inventory. Journal of Personality, 76(4), 875-902. DOI:10.1111/j.1467-6494.2008.00507.x
  • Varnum, M. E. W. & Grossmann, I. (2017). Cultural change: The how and the why. Perspectives on Psychological Science. DOI:10.1177/1745691617699971
  • Varnum, M. E. W. & Grossmann, I. (2016). Pathogen prevalence is associated with cultural changes in gender equality. Nature Human Behaviour, 1(0006). doi:10.1038/s41562-016-0003
  • Yarkoni, T., & Westfall, J. A. (2017). Choosing prediction over explanation in psychology: lessons from machine learning. Perspectives on Psychological Science. DOI:10.1177/1745691617693393

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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.


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.



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.



  • yes


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  • Markoff, John. 2012. “How Many Computers to Identify a Cat? 16,000.” In New York Times, June 25.
  • Mazzolari, Francesca, Giuseppe Ragusa. 2013. “Spillovers from High-Skill Consumption to Low-Skill Labor Markets.” In Review of Economics and Statistics 95(1): 74–86.
  • Michaels, Guy, Ashwini Natraj, John Van Reenen. 2014. “Has ICT Polarized Skill Demand? Evidence from Eleven Countries over Twenty-Five Years.” In Review of Economics and Statistics 96(1): 60–77.
  • Mishel, Lawrence, Heidi Shierholz, John Schmitt. 2013. “Don’t Blame the Robots: Assessing the Job Polarization Explanation of Growing Wage Inequality.” EPI-CEPR Working Paper, November 19.
  • Moravec, Hans. 1988. Mind Children: The Future of Robot and Human Intelligence. Harvard University Press.
  • Nordhaus, William D. 2007. “Two Centuries of Productivity Growth in Computing.” In Journal of Economic History 67(1): 17–22.
  • Pierce, Justin R., Peter K. Schott. 2012. “The Surprisingly Swift Decline of U.S. Manufacturing Employment.” NBER Working Paper 18655.
  • Polanyi, Michael. 1966. The Tacit Dimension. New York: Doubleday.
  • Ruggles, Steven, Trent J. Alexander, Katie Genadek, Ronald Goeken, Matthew B. Schroeder, Matthew Sobek. 2010. Integrated Public Use Microdata Series: Version 5.0 [Machine-readable database]. University of Minnesota.
  • Sachs, Jeffrey D., Seth G. Benzell, Guillermo LaGarda. 2015. “Robots: Curse or Blessing? A Basic Framework.” NBER Working Paper 21091, April.
  • Sachs, Jeffrey D., Laurence J. Kotlikoff. 2012. “Smart Machines and Long-Term Misery.” NBER Working Paper 18629, December.
  • Sagan, Carl. 1980. Cosmos. New York: Random House.
  • Simon, Herbert. A. 1966. “Automation” (a letter in response to “Where Do We Go From Here?” March 17, 1966 issue) In New York Review of Books, May 26.
  • Smith, Christopher L. 2013. “The Dynamics of Labor Market Polarization.” Federal Reserve Board, Finance and Economics Discussion Series No. 2013-57, August.
  • TIME. 1961. “The Automation Jobless.” February 24. In TIME
  • US Bureau of the Census. 1949. Historical Statistics of the United States, 1789–1945. U.S. Government Printing Office, Series D 134-144.
  • Varian, Hal R. 2014. “Big Data: New Tricks for Econometrics.” In Journal of Economic Perspectives 28(2): 3–28.

Via: backfill.

What If Everybody Didn’t Have to Work to Get Paid? | The Atlantic

What If Everybody Didn’t Have to Work to Get Paid?; David R. Wheeler; In The Atlantic; 2015-05-19.

tl;dr → it would look like graduate school on the occasion of the professor’s sabbatical abroad.

tl;dr → one needs
  • a patron as one is an artist
  • granted tenure at a large bureaucratic host, a university, as one is a professor
  • a trust fund as one is substantially indolent
  • charity, this is a solicitation for a charity.


  • Guaranteed Basic Income (GBI), also Unconditional Basic Income (UBI)
  • Proponents (previous oped work in The Atlantic)
  • Patreon, a donation conduit.
  • <quote>The crowdfunding approach to basic income has shown some promise: A group of more than 19,000 basic-income advocates in Germany have funded11 people so far with living stipends of 1,000 euros per month, no strings attached. The first few winners, chosen by a lottery, started receiving their basic incomes in 2014-09. The eleventh winner was announced 2015-05-07.</quote>
    • Who?
    • “I did not realize how unfree we all are,” attributed to the commentariat
  • North American Basic Income Guarantee Congress
    • New York
    • 2015-03.

Robots & Unemployment

Something about how robots took all the jobs, so therefore “we” “need” the Guaranteed Basic Income.


  • Scott Santens, bio

    • a wruterm an exemplar, receives the dole.
    • a leader (of the Basic Income Movement)
    • age 37
    • New Orleans
    • Bachelor of Science, Psychology, University of Washington, YEAR?
  • Jason Burke Murphy
    • an activist (of the Basic Income Movement)
    • professor, philosophy, Elms College in Massachusetts,
  • Matt Zwolinski
    • professor, philosophy, University of San Diego.
    • quoted for color, background & verisimilitude
  • Guy Standing
  • Karl Phillip Widerquist, bio, cv
    • a leader (of the Basic Income Movement)
    • professor, philosophy at SFS-Qatar
    • professor, Georgetown University
    • Opera, in archaeological order
      • author, Propertylessness, and Basic Income: A Theory of Freedom as the Power to Say (Palgrave Macmillan 2013).
      • coauthor, Economics for Social Workers (Columbia University Press 2002).
      • coeditor, Basic Income: An Anthology of Contemporary Research (Wiley-Blackwell 2013).
      • author, Alaska’s Permanent Fund Dividend: Examining its Suitability as a Model (Palgrave Macmillan 2012)
      • author, Exporting the Alaska Model: Adapting the Permanent Fund Dividend for Reform around the World (Palgrave Macmillan 2012).
      • author, Ethics and Economics of the Basic Income Guarantee (Ashgate 2005).
    • Estimated as forthcoming
      • Prehistoric Myths in Modern Political Philosophy (Edinburgh University Press forthcoming)
      • Justice as the Pursuit of Accord (Palgrave Macmillan forthcoming).

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Overview of ‘The Downward Ramp’, Opinements Upon the Economic Condition


in archaeological order … derivative works on top, originals below

Via: backfil


  • Concept
    • U-Shaped pattern
    • polarization
    • hollowing out
  • Trend
    • New College Grads (NCG) do service jobs, not “knowledge work”


in archaeological order



Josh Bivens, Elise Gould, Lawrence Mishel, Heidi Shierholz; Raising America’s Pay: Why It’s Our Central Economic Policy Challenge; Economic Policy Institute; 2014-06-04; x pages; landing, press release.


The clear connections between wages, income, and living standards mean that progress in reversing inequality, boosting living standards, and alleviating poverty will be extraordinarily difficult without addressing wage growth. Indeed, converting the slow and unequal wage growth of the last three-and-a-half decades into broad-based wage growth is the core economic challenge of our time.

Slow and unequal wage growth in recent decades stems from a growing wedge between overall productivity and pay. In the three decades following World War II, hourly compensation of the vast majority of workers rose in line with productivity. But for most of the past generation (except for a brief period in the late 1990s), pay for the vast majority has lagged further and further behind overall productivity. This breakdown of pay growth has been especially evident in the last decade, affecting both college- and non-college-educated workers as well as blue- and white-collar workers.

This paper argues that broad-based wage growth is necessary to address a constellation of economic challenges the United States faces: boosting income growth for low- and moderate-income Americans, checking or reversing the rise of income inequality, enhancing social mobility, reducing poverty, and aiding asset-building and retirement security. The paper also points out that strong wage growth for the vast majority can boost macroeconomic growth and stability in the medium run by closing the chronic shortfall in aggregate demand (a problem sometimes referred to as “secular stagnation”). Finally, the paper argues that any analyses of the causes of rising inequality and wage stagnation must consider the role of changes in labor market policies and business practices, which are given far too little attention by researchers and policymakers.

Andrew Sum, Ishwar Khatiwada, Mykhaylo Trubskyy, and Martha Ross with Walter McHugh, Sheila Palma (<snide>what a complicated author attribution statement</snide>); The Plummeting Labor Market Fortunes of Teens and Young Adults; Brookings Institution; 2014-03-14; 28 pages.


Employment prospects for teens and young adults in the nation’s 100 largest metropolitan areas plummeted between 2000 and 2011. On a number of measures—employment rates, labor force underutilization, unemployment, and year-round joblessness—teens and young adults fared poorly, and sometimes disastrously. While labor market problems affected all young people, some groups had better outcomes than others: non-Hispanic whites, those from higher income households, those with work experience, and those with higher levels of education were more successful in the labor market. In particular, education and previous work experience were most strongly associated with employment. Policy and program efforts to reduce youth joblessness and labor force underutilization should focus on the following priorities: incorporating more work-based learning (such as apprenticeships, co-ops, and internships) into education and training; creating tighter linkages between secondary and post-secondary education; ensuring that training meets regional labor market needs; expanding the Earned Income Tax Credit; and facilitating the transition of young people into the labor market through enhanced career counseling, mentoring, occupational and work-readiness skills development, and the creation of short-term subsidized jobs.

David Autor, David Dorn; The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market; In American Economic Review; 2013; 103(5); 1553-1597 (45 pages).


We offer a unified analysis of the growth of low-skill service occupations between 1980 and 2005 and the concurrent polarization of US employment and wages. We hypothesize that polarization stems from the interaction between consumer preferences, which favor variety over specialization, and the falling cost of automating routine, codifiable job tasks. Applying a spatial equilibrium model, we corroborate four implications of this hypothesis. Local labor markets that specialized in routine tasks differentially adopted information technology, reallocated low-skill labor into service occupations (employment polarization), experienced earnings growth at the tails of the distribution (wage polarization), and received inflows of skilled labor.

Paul Beaudry, David A. Green, Ben Sand; The great reversal in the demand for skill and cognitive tasks; working paper; 2013-01; 70 pages.


What explains the current low rate of employment in the US? While there has substantial debate over this question in recent years, we believe that considerable added insight can be derived by focusing on changes in the labour market at the turn of the century. In particular, we argue that in about the year 2000, the demand for skill (or, more specifically, for cognitive tasks often associated with high educational skill) underwent a reversal. Many researchers have documented a strong, ongoing increase in the demand for skills in the decades leading up to 2000. In this paper, we document a decline in that demand in the years since 2000, even as the supply of high education workers continues to grow. We go on to show that, in response to this demand reversal, high-skilled workers have moved down the occupational ladder and have begun to perform jobs traditionally performed by lower-skilled workers. This de-skilling process, in turn, results in high-skilled workers pushing low-skilled workers even further down the occupational ladder and, to some degree, out of the labor force all together. In order to understand these patterns, we offer a simple extension to the standard skill biased technical change model that views cognitive tasks as a stock rather than a flow. We show how such a model can explain the trends in the data that we present, and offers a novel interpretation of the current employment situation in the US.

David Autor (MIT, NBER); The Polarization of Job Opportunities in the U.S. Labor Market Implications for Employment and Earnings; a commissioned work; Center for American Progress, The Hamilton Project; 2010-04; 48 pages.


Between December 2007, when the U.S. housing and financial crises became the subject of daily news headlines, and March of 2010, the latest period for which data are available, the number of employed workers in the United States fell by 8.2 million, to 129.8 million from 138.0 million. In the same interval, the civilian unemployment rate nearly doubled, to 9.7 percent from 5.0 percent, while the employment-to-population ratio dropped to 58.6 percent from 62.7 percent—the lowest level seen in more than 25 years. Job losses of this magnitude cause enormous harm to workers, families, and communities.

A classic study by economists Lou Jacobson, Robert LaLonde, and Daniel Sullivan found that workers involuntary displaced by plant downsizings in Pennsylvania during the severe recession of the early 1980s suffered annual earnings losses averaging 25 percent, even six years following displacement.2 The nonpecuniary consequences of job losses due to the Great Recession may be just as severe. Studying the same group of workers with the benefit of 15 more years of data, labor economists Daniel Sullivan and co-author Till Von Wachter3 show that involuntarily job displacement approximately doubled the short-term mortality rates of those displaced and reduced their life expectancy on average by one to one and a half years. Thus, long after the U.S. unemployment rate recedes into single digits, the costs of the Great Recession will endure.

Despite the extremely adverse U.S. employment situation in 2010, history suggests that employment will eventually return and unemployment will eventually subside. But the key challenges facing the U.S. labor market—almost all of which were evident prior to the Great Recession—will surely endure. These challenges are two-fold. The first is that for some decades now, the U.S. labor market has experienced increased demand for skilled workers. During times like the 1950s and 1960s, a rising level of educational attainment kept up with this rising demand for skill. But since the late 1970s and early 1980s, the rise in U.S. education levels has not kept up with the rising demand for skilled workers, and the slowdown in educational attainment has been particularly severe for males. The result has been a sharp rise in the inequality of wages.

A second, equally significant challenge is that the structure of job opportunities in the United States has sharply polarized over the past two decades, with expanding job opportunities in both high-skill, high-wage occupations and low-skill, low-wage occupations, coupled with contracting opportunities in middle-wage, middle-skill white-collar and blue-collar jobs. Concretely, employment and earnings are rising in both high- education professional, technical, and managerial occupations and, since the late 1980s, in low-education food service, personal care, and protective service occupations. Conversely, job opportunities are declining in both middle-skill, white-collar clerical, administrative, and sales occupations and in middle-skill, blue-collar production, craft, and operative occupations. The decline in middle-skill jobs has been detrimental to the earnings and labor force participation rates of workers without a four-year college education, and differentially so for males, who are increasingly concentrated in low-paying service occupations.

Post-Industrious Society: Why work time will not disappear for our grandchildren | Gershuny, Fisher

Jonathan Gershuny, Kimberly Fisher; Post-Industrious Society: Why work time will not disappear for our grandchildren; Working Paper 20143; Department of Sociology, University of Oxford; 2014-04-05; 43 pages; landing.


We provide a comprehensive focussed discussion of the long-term evolution of time budgets in a range of European, North-American and Pacific democracies, summarising arguments about the changing balances between work and leisure as well as paid and unpaid work. We contrast economists’ assumptions about the purely instrumental nature of work, with sociological and social-psychological arguments as to why we might want or need work in and for itself. We use evidence from 16 countries drawn from the day-diaries included in the Multinational Time Use Study to describe trends in paid and unpaid work over five decades. We demonstrate:

  1. the approximate historical constancy and cross-national similarity in the total of paid plus unpaid work time;
  2. a gender convergence in work patterns and the emergence of the phenomenon of iso-work; and
  3. a reversal in the human capital-related work-leisure gradient, which we associate with a relative decline in “industriousness” in the paid work of early 21st century societies.


  • Much turns on the definition of work.
  • <quote>The leisure of the leisure classes consisted, to some degree, of honorific idleness—but free time only really implied honour, for Veblen’s social leaders, when it indicated, not mere freedom from industry, but specifically the availability for exploit. Exploit is how Veblen’s leisure class demonstrated its superordinate status.</quote>
  • The Third Person Criterion of work => <quote>Work is any business that could be conducted on your behalf by some agent without loss of the final product. You can wash your own shirt or pay someone to wash it for you: you get the clean shirt irrespective, and either you or the launderer has done some work. Note the conditionality: work that could be undertaken by a paid agent but is in fact undertaken unpaid for one’s self or own
    household, or on a volunteer basis for others, is still work though it lies outside any specific exchange relationship.</quote>
  • embodied human capital => must devote time to paid work.
  • Factors of provision that satisfy human wants
    1. Paid labour time,
    2. unpaid labour time
    3. consumption time
  • Technical change scopes affecting time use
    1. innovation in complex technical systems
      • Broadly scoped
        • Roads, phones, power.
        • White goods, consumer goods
        • Dotcom, Internet
      • <quote>As a result much of what had once been paid work in service industries was substituted for by unpaid labour within the household (Gershuny 1977).</quote>
    2. Birth control.
      • Allows women to choose paid or unpaid work work.
      • <quote><snip/> we find a historical convergence between men’s and women’s paid/unpaid work balance, albeit driven more by a reduction of unpaid work done by women than by an increase in that done by men (Kan et al. 2011).</quote>
  • <quote>Becker (1965) provided a socially differentiated view of consumption, in
    which high-wage individuals might choose to consume expensive “time-intensive goods” (e.g. power boating, “standing under a cold shower tearing up $20 bills”) which maximise the affective return-per-minute of their consumption time, and increasing their paid work time to finance these, while low-wage individuals reduce their paid work and consume low-cost time extensive goods (“walks in the park”).</quote>
  • UN System of National Accounts (UNSD 2014)
    • System of National Accounts Production Boundary (SNAPB)
    • General Production Boundary (GPB)
  • The Great Day, a national time budget
  • <quote>the so-called “cost disease” process (Baumol 1993) in which technological innovation increases manufacturing productivity, putting pressure on service sector wages while reducing the costs of the machines used in final service production, to the point that they become feasible purchases by private households. </quote> which produces the “self-service” phenomenon (Skolka 1977, Gershuny 1977)
  • iso-work [page 18] unclearly defined.  Something about how men and women have/do the “similar” amounts of work across long periods of time.
  • Claim: <quote>Our results constitute the most comprehensive-ever description of the long-term progress of the work-leisure balance in the developed world.</quote>
  • Read the summary
  • End note: <quote>a quite new sort of theorising about the nature of work. Individuals’ time-use sequences are the DNA of economic activity.</quote>


  • commodification
  • consumption
    • time devoted to consumption
  • exchange
  • exploit
    • play-like; in the Veblen sense
    • not “exploited” in the Marxist sense
    • paid exploit
  • free time
  • industry
    • industriousness
    • dutiful
  • leisure
  • paid
    • paid labor time
  • potential earnings
  • sphere
    • sphere of exchange
    • sphere of productivity
  • unpaid
    • unpaid work time
  • volunteer
  • work


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A History of the Future | David J. Staley

David J. Staley; A History of the Future; In History and Theory; Theme Issue 41; ISSN: 0018-2656; 2002-12; pages 72-89 (18 pages).


Does history have to be only about the past? “History” refers to both a subject matter and a thought process. That thought process involves raising questions, marshalling evidence, discerning patterns in the evidence, writing narratives, and critiquing the narratives written by others. Whatever subject matter they study, all historians employ the thought process of historical thinking.

What if historians were to extend the process of historical thinking into the subject matter domain of the future? Historians would breach one of our profession’s most rigid disciplinary barriers. Very few historians venture predictions about the future, and those who do are viewed with skepticism by the profession at large. On methodological grounds, most historians reject as either impractical, quixotic, hubristic, or dangerous, any effort to examine the past as a way to make predictions about the future.

However, where at one time thinking about the future did mean making a scientifically-based prediction, futurists today are just as likely to think in terms of scenarios.Where a prediction is a definitive statement about what will be, scenarios are heuristic narratives that explore alternative plausibilities of what might be. Scenario writers, like historians, understand that surprise, contingency, and deviations from the trend line are the rule, not the exception; among scenario writers, context matters. The thought process of the scenario method shares many features with historical thinking. With only minimal intellectual adjustment, then, most professionally trained historians possess the necessary skills to write methodologically rigorous “histories of the future.”


  • Covering-Law Models
  • Initial Conditions
  • Counterfactual historians
  • Retrodictions (contra predictions)
  • Narrative sentences => refer to at least two time-separated events; give descriptions of the events which could not have been observed at the time [due to anti-causlity]; e.g. The thirty Years War begin in 1618.
  • scenarios
    • prediction, plausibilities, possibilities
    • opportunities for control
  • The Advice Establishment
    • hardening the soft sciences
    • Rand Corporation, US
    • Futuribles, FR; a think tank, Ford Foundation, Bertrand de Jouvenel
  • Scenarios
    • Peter Wack
    • The Shell Method
    • The Intuitive Method
    • <quote>The goal of scenario writing is not to predict the one path the future will follow but to discernthe possible states toward which the future might be “attracted.”</quote> [page 79]
      • “what if …”
      • [what would you have to believe if ...]
    • <quote>Each version of the future has its own “logics,” “the plot which ties togetherthe elements of the system.”</quote>
    • Three alternates [the tri-lemma concept]
  • A postmodernist approach
    • Wagar
    • the past is just as inaccessible as the future.
    • <quote>Wagar believes historians are empowered to write stories about the future using scenario thinking as a license to avoid making definitive predictions — in the same way postmodernism has freed them from searching for the inaccessible objective truth of the past.</quote> [page 82]
  • Immanuel Wallerstein’s world systems theory
  • <quote>Evidence makes counterfactuals”practicable”and future scenarios “futurible.”</quote> [page 86]
  • thick descriptions; of anthropological methods.
  • <quote>the scenarios historians write would need to be synchronic narratives, rather than the diachronic narratives we usually prefer.</quote> [page 87]
  • structure vs [temporal] ordering


  • Hannah Arendt
  • Michael Biddiss
  • Marc Bloch
  • Fernand Braudel
  • Thomas J. Chermack
  • Paul Costello
  • Arthur Danto
  • Max Dublin
  • Richard J. Evans
  • Niall Ferguson
  • James Gleick
  • Raymond Grew
  • Thane Gustafson
  • Geoffrey Hawthorn
  • Hegel
  • Robert Heilbroner
  • Edward J. Honton
  • Neil Howe
  • Bertrand de Jouvenel
  • Herman Kahn
  • Susan A. Lynham
  • Gordon Leff
  • Antonio Martelli
  • Marx
  • Ernest May
  • William McNeill
  • Matthew Melko
  • Stephen M. Millett,
  • Richard Neustadt
  • Karl Popper
  • Kevin Reilly
  • Nicholas Rescher
  • Wendy E. A. Ruona
  • Marshall Sahlins
  • T. Irene Sanders
  • Arthur Schlesinger
  • Arthur Schlesinger Jr.
  • Hagen Schulze
  • Michael Stanford
  • Leften Stavrianos
  • William Strauss
  • Toynbee
  • Peter Schwartz
  • William A. Sherden
  • Spengler
  • Stephen Vaughan
  • Vico
  • Pierre Wack
  • W. Warren Wagar
  • Immanuel Wallerstein
  • Hayden White
  • Sam Wineburg
  • Daniel Yergin


  • National Standards for History; 2002.
  • Sam Wineburg; Historical Thinking and Other Unnatural Acts: Charting the Future of Teaching the Past; Temple University Press; 2001.
  • Robert Heilbroner; The Future as History; Grove Press; 1959.
  • Arthur Schlesinger; The Cycles of American History; 1986; Mariner Books; 1999.
  • William Strauss, Neil Howe; The Fourth Turning: What the Cycles of History Tell Us About America’s Next Rendezvous with Destiny; Broadway Books; 1997; ; noted herein.
  • William Strauss, Neil Howe; Generations: The History of America’s Future 1584 to 2069; Quill; 1991; noted herein.
  • Matthew Melko; The Perils of Macrohistorical Studies; In World History Bulletin, Issue 17; 2001-Fall; pages 27-32 (6 pages); noted herein.
  • Raymond Grew; “Review Essay on Paul Costello, World Historians and Their Goals: Twentieth-Century Answers to Modernism”; In History and Theory; Volume 34; 1995; pages 371-394.
  • Michael Biddiss, “History as Destiny: Gobineau, H. S. Chamberlain and Spengler”; In Transactions of the Royal Historical Society; Volume 7; 1997; pages 73-100.
  • Max Dublin; Futurehype: The Tyranny of Prophecy; Dutton; 1991.
  • Gordon Leff; “The Past and the New,” in The Vital Past: Writings on the Uses of History; Stephen Vaughn, editor; University of Georgia Press; 1985.
  • Karl Popper; “Prediction and Prophecy in the Social Sciences”; In Conjectures and Refutations;  Routledge and Kegan Paul; 1963.
  • Karl Popper; The Poverty of Historicism; Routledge; 1957.
  • Arthur C. Danto, Narration and Knowledge; Columbia University Press; 1968, 1985.
  • Robert Heilbroner; Visions of the Future: The Distant Past, Yesterday, Today, Tomorrow; New York Public Library and Oxford University Press, 1995.
  • Bertrand de Jouvenel; The Art of Conjecture; Basic Books; 1967.
  • Nicholas Rescher; Predicting the Future: An Introduction to the Theory of Forecasting; State University of New York Press; 1998.
  • William A. Sherden; The Fortune Sellers: The Big Business of Buying and
    Selling Predictions; John Wiley and Sons, Inc., 1998.
  • James Gleick; Chaos: The Making of a New Science; Viking; 1987.
  • Stephen M. Millett, Edward J. Honton; A Manager’s Guide to Technology Forecasting and Strategy Analysis Methods; Battelle Press, 1991.
  • T. Irene Sanders; Strategic Thinking and the New Science: Planning in the Midst of Chaos, Complexity,and Change; The Free Press; 1998.
  • Herman Kahn; The Year 2000: A Framework for Speculation on the Next Thirty-Three Years; The Macmillan Company, 1967.
  • Pierre Wack, “Scenarios: Uncharted Waters Ahead”; In Harvard Business Review; Volume 63; 1985;, pages 72-79,
  • Pierre Wack; “Scenarios:Shooting the Rapids”; In Harvard Business Review; Volume 63; 1985; pages 139-150.
  • Stephen M. Millett; History of Business Scenarios (busted link)
  • Thomas J. Chermack, Susan A. Lynham, Wendy E. A. Ruona; “A Review of Scenario Planning Literature”; In Futures Research Quarterly; Volume 17; 2001-Summer; pages 7-31.
  • Antonio Martelli, “Scenario Building and Scenario Planning: State of the Art and Prospects of Evolution”; In Futures Research Quarterly; Volume 17; 2001-Summer; pages 57-74.
  • Peter Schwartz; The Art of the Long View: Planning for the Future in an Uncertain World; Currency/Doubleday; 1991.
  • Innovators of Digital Economy Alternatives (IDEA).
    • (ibidem.)
    • (ibidem.)
  • W. Warren Wagar; “Past and Future”; In American Behavioral Scientist; Volume 42; 1998-11/1998-12.
  • Daniel Yergin, Thane Gustafson; Russia 2010, and What It Means for the Rest of the World; Vintage Books; 1995.
  • W. Warren Wagar; Short History of the Future; University of Chicago Press; 1999.
  • “Tomorrow and Tomorrow andTomorrow”; staff; In Technology Review; Volume 96; 1993-04; pages 50-59.
  • David J. Staley; “Japan’s Uncertain Future: Key Trends and Scenarios”; In The Futurist; Volume 26; 2002-03/2002-04; pages 48-53.
  • Michael Stanford; The Nature of Historical Knowledge; Blackwell; 1986.
  • Richard J. Evans; In Defense of History; W. W. Norton; 1999.
  • William H. McNeill; Mythistory and Other Essays; University of Chicago Press,; 1986.
  • Niall Ferguson; VirtualHistory: Alternatives and Counterfactuals; Basic Books,
  • Geoffrey Hawthorn; Plausible Worlds: Possibility and Understanding in History and the Social Sciences; Cambridge University Press; 1991.
  • Hagen Schulze; Germany: A New History; Harvard University Press; 1998.
  • Richard E. Neustadt, Ernest R. May; Thinking in Time: The Uses of History by Decision-Makers; The Free Press; 1986.
  • Marshall Sahlins; Islands of History; University of Chicago Press; 1985.
  • Fernand Braudel; On History; University of Chicago Press; 1980.
  • Douglas Hofstadter; Metamagical Themas: Questing for the Essence of Mind and Pattern; Basic Books; 1985.
  • David J. Staley; “Realistic and Responsible Imagination: Ordering the Past to Envision the Future of Technology”; In Futures Research Quarterly; Volume 14; 1998-Fall; pages 29-39.

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Toward a General Theory of Strategic Action Fields | Fligstein, McAdams

Neil Fligstein, Doug McAdams; Toward a General Theory of Strategic Action Fields; In Sociological Theory; Volume 29, Number 1; 2011-03; 26 pages.


In recent years there has been an outpouring of work at the intersection of social movement studies and organizational theory. While we are generally in sympathy with this work, we think it implies a far more radical rethinking of structure and agency in modern society than has been realized to date. In this article, we offer a brief sketch of a general theory of strategic action fields (SAFs). We begin with a discussion of the main elements of the theory, describe the broader environment in which any SAF is embedded, consider the dynamics of stability and change in SAFs, and end with a respectful critique of other contemporary perspectives on social structure and agency.


Neil Fligstein, Doug McAdam; A Theory of Fields; Oxford University Press; 2012-04-16; 253 pages; kindle: $13, paper: $19+SHT.


(quoting where possible)

Components of the Theory

  1. strategic action fields
  2. incumbents, challengers, and governance units
  3. social skill
  4. the broader field environment
  5. exogenous shocks, field ruptures, and the onset of contention
  6. episodes of contention
  7. settlement


Proposition 1. Unorganized social spaces become organized through a crescive social process akin to a social movement.

Proposition 2. Skilled social actors are pivotal for new fields to emerge. They must find a way to translate existing rules and resources into the production of local orders by convincing their supporters to cooperate and finding means of accommodation with other groups.

Proposition 3. Skilled social actors can help produce entirely new cultural frames for fields. They do so by building compromise identities that bring many groups along. In this process, every group’s identities and interests can be transformed.

Proposition 4. Initial resource allocations affect whether or not SAFs become organized hierarchically or cooperatively. The greater the inequality of initial resource distribution, the more likely the field will be hierarchical. Conversely, the existence of a set of groups of roughly equal size or resource endowment will encourage coalition building.

Proposition 5. SAFs are stable when they have role structures that are based on either hierarchical incumbent/challenger structures or political coalitions. Unorganized social space, on the contrary, is characterized by the frequent entry and exit of organizations, no stable social relationships, and no agreement on means and ends. This kind of drift or conflict can go on for long periods of time.

Proposition 6. New SAFs are likely to emerge nearby [to] existing SAFs. They are likely to be populated by existing groups who “migrate” or by offshoots of existing groups.

Proposition 7. States aid in the creation of new social space as intended and unintended consequences of state actions. States will also be the focus of attention from emerging SAFs.

Proposition 8. Emergent fields produce new forms of organizing. These frames can be borrowed from actors in nearby social space.

Proposition 9. Stable SAFs are characterized by a well-known role structure of incumbents and challengers or a set of political coalitions. The rules of the game will be known. Response to instability will be met by attempts to reinforce the status quo. Challengers will be particularly vulnerable to downturn. Challengers risk their survival under stable or crisis circumstances by undertaking actions vis-á-vis incumbents.

Proposition 10. Skilled actors of dominant and challenger groups will engage in moves that they hope will preserve or improve their position in the existing SAF. These constant adjustments constitute a form of organizational learning. Tactics for challengers include building niches and taking advantage of crises of other challengers. Tactics for incumbents include imitation, cooptation, or merger.

Proposition 11. SAFs are generally destabilized by external shock originating from other SAFs, invasion by other groups of organizations, actions of the state, or large-scale crises such as wars or depressions.

Proposition 12. The more connected an SAF is to other SAFs, the more stable that SAF is likely to be. Similarly, new SAFs or those with a few connections will be unstable.

Proposition 13. The more dependent an SAF is on others for resources, or the lower it is in the hierarchy of SAFs, the less stable it is.

Proposition 14. States will be the focus of action in crises. This explains why modern societies appear to be crisis ridden. General societal crises are rare, but when they occur, they have the potential to rewrite the rules across much of society.

Proposition 15. Incumbent socially skilled actors will defend the status quo. It follows that if a new frame emerges, it will come from an invader or challenger groups. They will attempt to create new rules and a new order and therefore either will build a new political coalition based on interest or create a new cultural frame that reorganizes interests and identities.

Proposition 16. An SAF crisis can result in the following:

  1. A reimposition of the old order with some adjustments. This will occur most frequently with the state enforcing whatever new agreements have been reached, most often at the expense of challenger groups.
  2. The SAF breaks down into unorganized social space. If the groups that make up the social space are unable to find a new conception of control and the state is unwilling or unable to impose a new order, then the field can become disorganized. This kind of condition is likely by definition to be unstable for the groups that remain and one can expect that they will migrate to other social spaces or else disappear.
  3. The SAF is partitioned into several social spaces. One solution is to break the field down by redefining the activities of the groups in the field so that they are no longer trying to occupy the same social space. Thus, new agreements are possible amongst potentially smaller set of groups.
  4. The challengers can build a coalition to produce a new SAF. Challengers and incumbents can migrate to already existing social space or they can try and colonize new social space. Depending on the circumstances, it might make sense for groups to join already existing social space. They might do so as invaders, challengers, or incumbents. This may prove problematic (i.e., no one wants them there). Under these conditions, occupying unorganized social space may prove the most appropriate way for groups to survive.


strategic action field
  • is a meso-level social order where actors (who can be individual or collective) interact with knowledge of one another under a set of common understandings about the purposes of the field, the relationships in the field (including who has power and why), and the field’s rules.
  • [Our view] attempts to combine the social constructionist aspects of institutional
    theory with a focus on how, at their core, field processes are about who gets what.
  • [] fields are constructed on a situational basis,
    as shifting collections of actors come to define new issues and concerns as salient.
  • Aspects
    1.  there is a diffuse understanding of what is going on in the field,
    2. there is a set of actors in the field who can be generally viewed as possess-
      ing more or less powe; incumbents vs challengers
    3. there is a set of shared understandings about the “rules” in the field,
    4. there is the interpretive frame that individual and collective strategic actors
      bring to make sense of what others are doing.
  • Perspectives
    • Incumbent vs Challenger
    • Established vs Oppositional
  • Distinctions
    • fields as only rarely organized around a truly consensual “taken for granted” reality.
    • Accent on constant contention in contrast to “traditional” institutional theory (settled fields) where settled times is common, change is rare.
    • Constant contention; with different initial conditions will settle to different states.
incumbents, challengers, and governance units
  • Incumbents vs Challengers
    • obvious definitions; winners write history
    • Most of the time challengers can be expected to conform to the prevailing order.
    • Potentially extended to coalitions; dominant vs disorganized
  • Governance Units
    • Internal to the jurisdiction.
    • External governance is a separate concept.
    • Designed to reinforce the position of the Incumbents; etc.
social skill
  • <quote>Much of sociology contends it is interested in society’s challengers, the downtrodden and the dispossessed.</quote> [So then ... it is stipulated: sociology is institutionalized activism]
  • Viewpoints
    • Standard Sociology => cultural & structural factors dominate causes towards outcomes
    • [theirs] => individuals and groups have varying skill to cause outcomes; there’s a “there” there.
  • Definitions
    • strategic action [is defined as] the attempt by social actors to create and maintain stable social worlds by securing the cooperation of others; to control.
    • social skill can be defined as how individuals or collective actors possess a highly developed cognitive capacity for reading people and environments,
      framing lines of action, and mobilizing people in the service of these action “frames.”
  • Social skill is always required & applied; institutions and consensus may automate the process so that less substantial skill is required to operate [to preserve the current détente]
the broader field environment
  • Three sets
    • distant vs proximate fields
    • vertical vs horizontal fields
    • state vs non-state fields
  • Whither The State?
    • The definition of “a state” is loose; both monolithic and diffuse.
    • Carry jurisdictional authority.
    • Can legitimize (delegitimize) non-state fields.
exogenous shocks, field ruptures, and the onset of contention
  • the interdependence of fields is a source of a certain level of rolling turbulence in modern society.
  • contention as a highly contingent outcome of an ongoing process of interaction involving at least one incumbent and one challenger
  • Three Mechanisms
    1. The collective construction/attribution of threat or opportunity.
    2. Organizational appropriation.
    3. Innovative action.
episodes of contention
  • An episode is defined as a period of emergent, sustained contentious interaction between . . . . [field] actors utilizing new and innovative forms of action vis-a-vis one another.
  • Indica & Diagnostics
    • Within an episode
      1. a shared sense of uncertainty/crisis regarding the rules and power relations governing the field,
      2. sustained mobilization by incumbents and challengers.
    • Continuance else ending of an episode
      • [continues so long as the] shared sense of uncertainty regarding the structure and dominant logic of the field persists.
      • A field is no longer in crisis when a generalized sense of order and certainty return.
      • Continuance can be self-powering; till the revolution consumes itself.
    • Actions
      • Framing, reframing
      • Imposition of settlements
      • Assertion of oppositional logics
  • State actors => state solutions, institutional settlement
  • Non-state actors => spillover, spin-off, legitimate forms from proximate fields


  • Scales
    • Macro => big
    • Meso => medium
    • Micro => tiny
  • Disclaimer of the paper, page 2.
    • <quote>Space constraints preclude a full rendering of our theory here.</quote>
    • <quote>We are presently working on a book manuscript that will allow us to explicate the theory in much greater detail.</quote>


  • branded theories; institutional theories
    • Sectors
    • Organizational Fields
    • Games
    • Fields
    • Networks
    • Policy Domains
    • Markets
    • Social Movement Industries
      • Social Movement Organizations
      • activists
  • viewpoints, perspectives, foc{ii,uses}
    • social poiwer
    • constructionist
  • more branded theory
    • institutional logic
    • organizational logic (generally)
  • branded concepts
    • Bordieu’s habitus is repository of feelings and motives as well as a repertoire of actions and strategies [and other things].
    • Giddens’s view that the function of routines of everyday life is to alleviate ontological anxiety

Social Class and the Hidden Curriculum of Work

Jean Anyon; Social Class and the Hidden Curriculum of Work; In Journal of Education, Vol. 162, No. 1; 1980-Fall.
Anyon is (was) the chairperson of the Department of Education at Rutgers University, Newark


It’s no surprise that schools in wealthy communities are better than those in poor communities, or that they better prepare their students for desirable jobs. It may be shocking, however, to learn how vast the differences in schools are – not so much in resources as in teaching methods and philosophies of education. Jean Anyon observed five elementary schools over the course of a full school year and concluded that fifth-graders of different economic backgrounds are already being prepared to occupy particular rungs on the social ladder. In a sense, some whole schools are on the vocational education track, while others are geared to produce future doctors, lawyers, and business leaders. Anyon’s main audience is professional educators, so you may find her style and vocabulary challenging, but, once you’ve read her descriptions of specific classroom activities, the more analytic parts of the essay should prove easier to understand.


Via: backfill

The Surveillant Assemblage | Haggerty, Ericson

Kevin D. Haggerty, Richard V. Ericson; The Surveillant Assemblage; In British Journal of Sociology; Vol. 51, No. 4; 2000-12; 18 pages.


George Orwell’s ‘Big Brother’ and Michel Foucault’s ‘panopticon’ have dominated discussion of contemporary developments in surveillance. While such metaphors draw our attention to important attributes of surveillance, they also miss some recent dynamics in its operation. The work of Gilles Deleuze and Félix Guattari is used to analyse the convergence of once discrete surveillance systems. The resultant ‘surveillant assemblage’ operates by abstracting human bodies from their territorial settings, and separating them into a series of discrete flows. These flows are then reassembled in different locations as discrete and virtual ‘data doubles’. The surveillant assemblage transforms the purposes of surveillance and the hierarchies of surveillance, as well as the institution of privacy.

Via: backfill

Facebook Use Predicts Declines in Subjective Well-Being in Young Adults | Kross, Verduyn, Demiralp, Park, Lee, Lin, Shablack, Jonides, Ybarra

Ethan Kross, Philippe Verduyn, Emre Demiralp, Jiyoung Park, David Seungjae Lee, Natalie Lin, Holly Shablack, John Jonides, Oscar Ybarra; Facebook Use Predicts Declines in Subjective Well-Being in Young Adults; In PLoS ONE; 2013-06-12; 6 pages; landing.


Over 500 million people interact daily with Facebook. Yet, whether Facebook use influences subjective well-being over time is unknown. We addressed this issue using experience-sampling, the most reliable method for measuring in-vivo behavior and psychological experience. We text-messaged people five times per day for two-weeks to examine how Facebook use influences the two components of subjective well-being: how people feel moment-to-moment and how satisfied they are with their lives. Our results indicate that Facebook use predicts negative shifts on both of these variables over time. The more people used Facebook at one time point, the worse they felt the next time we text-messaged them; the more they used Facebook over two-weeks, the more their life satisfaction levels declined over time. Interacting with other people “directly” did not predict these negative outcomes. They were also not moderated by the size of people’s Facebook networks, their perceived supportiveness, motivation for using Facebook, gender, loneliness, self-esteem, or depression. On the surface, Facebook provides an invaluable resource for fulfilling the basic human need for social connection. Rather than enhancing well-being, however, these findings suggest that Facebook may undermine it.


Via: backfill

Vance Oakley Packard


  • 1946 How to Pick a Mate, with Clifford Adams
  • 1950 Animal IQ
  • 1957 The Hidden Persuaders
    On advertising.
  • 1959 The Status Seekers
    On social stratification and class-based behavior.
  • 1960 The Waste Makers
    On planned obsolescence.
  • 1962 The Pyramid Climbers
    On middle managers and conformity.
  • 1964 The Naked Society
    On privacy, surveillance and its influence on behavior.
  • 1968 The Sexual Wilderness
    On the Sexual Revolution
  • 1972 A Nation of Strangers
    The attrition of communal structure through frequent geographical transfers of corporate executives
  • 1977 The People Shapers
    On psychological & biological experimentation to manipulate human behavior.
  • 1983 Our Endangered Children
    The preoccupation with money, power, status, and sex, ignores future generations.
  • 1989 The Ultra Rich: How Much Is Too Much?
    The lives of thirty American multimillionaires.

Source: Jimi Wales’ Wiki

Reviews & Summaries

The Status Seekers

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.

    • 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.

    • 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.

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

    • 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.

    • 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

        • 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


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