Artificial Intelligence, Robotics, and the Future of Work: Myths and Facts | ITIF

Robert D. Atkinson (ITIF); Artificial Intelligence, Robotics, and the Future of Work: Myths and Facts; In Their Blog, at the Information Technology & Innovation Foundation (ITIF); 2017-09-19.
Robert D. Atkinson is proprietor President, ITIF.

tl;dr → There is nothing to fear. The world is big, the effect is small. Anyway, all KPIs are stagnating, not amplifying. And the olds; there are too many old people. The robots will make [the youngs] rich. Say “No” to UBI.


Artificial Intelligence Challenges And Opportunities; a talk; at Some Conference, by Bruegel; 2017-03-23.
Bruegel is a think tank, in Europe, with thoughts on economics.
The essay is edited & amplified since that performance.


  • Artificial Intelligence (AI)
  • Universal Basic Income (UBI)
  • “Oxford University researchers have estimated that 47 percent…”, as opined in Wired, 2015-04.
    <quote>Maybe this could be a good drinking game: Every time an article cites the Oxford study, you have to drink a shot of Jack Daniels.</quote>
  • techno-utopians/dystopians, a self-conscious class of persons.
  • Moore’s Law, In Jimi Wales’ Wiki.
    • uttered over 50 years ago,
    • Prognosticates that computing power would double every 25 months or so.
      [queue those who say it says something else entirely, …and… CUT!] …<snip/> [Aaan…and we're back]
  • “suitcase words,” an epithet, attributed to Rodney Brooks.


The two key steps
  1. First, slow down to a more manageable pace of change by imposing a tax on robots.
  2. The second, point, and he did have one was [WHAT?]


“We” Need
  • better workforce training systems
  • worker adjustment programs (like unemployment insurance)
“We” Don’t Need
  • A dole, as branded: Universal Basic Income (UBI)


  1. Technological change has always been gradual and always will be
  2. mostAll of these techno-utopians/dystopians base their “predictions” on the continuation of Moore’s law
    which in its ending stages now.
  3. That is because, historically, there is no relationship between higher productivity and unemployment.
  4. All the Baby Boomers will retire, and there is nobody and no wealth to care for them; [we] will want need the machines for that.
  5. … human needs are far from being satisfied.


Of Labor-Intensive Technology-Insensitive Occupations
  • fashion models
  • manicurists
  • carpet installers
  • barbers
  • brick masons
  • block masons
  • machinists
  • cartographers
  • photogrammetrists
  • dental laboratory technicians
  • social science research assistants
    <snide>uttered with out irony</snide>
  • firefighters
  • preschool teachers
  • doctors
  • Chief Executive Officers (CEOs), as an occupation, as a self-conscious class
    <snide>again, uttered with out irony</snide>


  • <quote>Our needs are very large and it is farfetched to think technology will eliminate the need for work.</quote>i>
  • <quote>But one innovation that is absolutely not needed is UBI (Universal Basic Income), which some have suggested as a reponse to technological progress, and which has to rank as one of the dumbest ideas of all time. </quote>


  • Carl Benedikt Frey, staff, Oxford University.
  • Rodney Brooks
    • professor, Massachusetts Institute of Technology (MIT).
    • CEO, Rethink Robotics
  • Bill Gates, boffo.
  • Benoit Hamon, candidate for president, Socialist Party, France.
  • Marvin Minsky, a scientist, Massachusetts Institute of Technology (MIT).
  • Gordon Moore, co-founder, Intel.
  • Nil NilsonNils John Nilsson
  • Michael A. Osborne, staff, Oxford University.
  • Klaus Schwab, founder and chairman, World Economic Forum (WEF).
  • Gail Garfield Schwartz, an economist, specializing in labor.
  • Gianni Versace, boffo.



In Their Blog, at the Information Technology & Innovation Foundation (ITIF)…


The Suitcase Words
  • artificial intelligence
  • unprecedented
  • 4th Industrial Revolution
  • artificial intelligence
  • autonomous vehicles
  • robots
  • other breakthroughs
  • Industrial Revolution
  • look like a period of stability. We are already seeing this shake the very foundations of our economies, with
  • labor productivity growth rates
  • skyrocketing
  • worker dislocation
  • the lion’s share,
    the lion’s share powered by technology.
  • the pace
    the pace of dislocation will only increase.
  • The only constant is change
    made that one up, you like?
  • a scientist,
    one scientist,
    one leading scientist,one leading artificial intelligence scientist
  • predicts
  • general intelligence
  • an average human being
  • AI scientist Nil Nilson (sic) Nils John Nilsson
  • warns
  • full employment,
    the notion of full employment.
  • the pace,
    the pace of technical change is accelerating
  • the pace of technical change is accelerating
    and the only constant is change, see it works!
  • labor economist Gail Garfield Schwartz
  • warns
  • out of work
  • in a generation
  • warns
  • jobs,
    jobs will be eliminated,
    jobs will be eliminated worldwide by 2020 by robotics and AI.
  • Oxford researchers Michael A. Osborne and Carl Benedikt Frey
  • predict
  • warn
  • sex workers,
    sex workers could be out of work
    [who are these people?]
  • incumbent on policymakers
  • slow down,
    slow down to a more manageable pace of change.
    to where only the change is only constant! Wheee!
  • a tax on robots
  • Social Security taxes.
    Social Security taxes, on robots.
  • This is an idea that has been championed by luminaries such as
  • Bill Gates
  • French Socialist presidential candidate Benoit Hamon
  • the wealth,
    the wealth creates benefits for the shareholders
  • the social contribution
  • added value
  • <quote><snip/>the social contributions on the whole of the added value and not just on the work<quote>, attributed ot Benoit Hamon.
  • Universal Basic Income (UBI)
  • sustain themselves
  • productivity rates
  • slowdowns
  • the risk,
    the risk of a U.S. worker losing their job,
    the risk of a U.S. worker losing their job from a shutdown or downsizing.
  • 4th Industrial Revolution
  • predictions,
    predictions by experts?
  • “predictions”
    “predictions” were made in the 1970’s and 80’s.
  • the machine,
    the machine with human intelligence
    the machine with human intelligence within the next three to eight years
  • MIT scientist Marvin Minsky
  • The prediction about 20 percent of the workforce out of work was made in 1982.
  • full employment,
    give up on full employment,
    The call to give up on full employment.
  • scary
  • distinguish,
    can’t distinguish,
    someone can’t distinguish between millions and billions.
  • winning the lottery,
    chance of winning the lottery,
    almost as much chance of winning the lottery as…
  • incompetent,
    your CEO is incompetent.
  • <quote>Maybe robots replacing CEO’s is the answer to job security.</quote>
  • the study,
    The Study. That. Shows.
    the Oxford study by Osborne and Frey,
    the Oxford study by Osborne and Frey that warns…
  • the study,
    the Oxford study,
    coverage of the Oxford study.
  • Jack Daniels,
    a bottle of Jack Daniels,
    to wager a bottle of Jack Daniels.
  • peer review
  • occupational categories,
    702 occupational categories,
    all 702 occupational categories,
    neglected to examine all 702 occupational categories
  • task measures,
  • task measures from the Department of Labor,
    task measures from the Department of Labor, which assessed occupations based on factors…
    task measures from the Department of Labor, which assessed occupations based on factors such as how much manual dexterity…
    task measures from the Department of Labor, which assessed occupations based on factors such as how much manual dexterity and social perceptiveness [as occupational requirements].
  • destined,
    destined for the trash heap…
    destined for the trash heap of techno-history.
  • nonsense,
    their methodology produces nonsense.
  • going
    going the way of the buggy whip maker
  • Versace
  • The Jetsons
  • chair,
    the magic robot chair
  • fretting,
    instead of fretting…
    instead of fretting about … killing jobs,
    instead of fretting about tech killing jobs.
  • worrying,
    instead be worrying…
    instead be worrying about … productivity …,
    instead be worrying about … productivity growth rates …
    instead be worrying about … raise productivity growth rates …
    instead be worrying about … raise productivity growth rates, which have been at all-time lows over the last decade.
    instead be worrying about … going to raise productivity growth rates, which have been at all-time lows over the last decade.
    instead be worrying about how the heck are we ever going to raise productivity growth rates, which have been at all-time lows over the last decade.
    <wow!> <paf!> </wow!>
  • assault,
    the assault,
    the robot assault
  • MIT professor and CEO of Rethink Robotics Rodney Brooks
  • words,
    suitcase words,
    misled by suitcase words.
  • errors,
    category errors,
    category errors in fungibility of capabilities.
  • errors,
    category errors,
    category errors comparable to seeing the rise of more efficient internal combustion engines …
    category errors,
    category errors comparable to seeing the rise of more efficient internal combustion engines and jumping to the conclusion that warp drives are just around the corner.
  • Beam me up, Scotty.
  • techno-utopians/dystopians,
    these techno-utopians/dystopians.
  • Moore’s law, (sic) Moore’s Law),
    the continuation of Moore’s Law.
  • Intel’s co-founder [Gordon Moore]
  • exponentials,
    The nature of exponentials
  • is that you push them out and eventually disaster happens.” Disaster will happen long before
  • Ex Machina,
    the alluring robot in Ex Machina.
  • There’s another reason to calm down.
  • This is pretty obvious if you just think about it.
  • Productivity leads to lower prices and/or higher wages.
  • This money gets spent.
  • That spending creates jobs.
  • panic,
    to panic,
    we are to panic,
    if we are to panic …
    if we are to panic, and panic can be a good thing.
  • retirement,
    the massive retirement,
    the massive retirement of baby boomers.
  • a war,
    a generational war,
    a generational war where …
    a generational war where either the old people or the younger workers will win.
  • people,
    working-age people, old people,
    the ratio of working-age people to old people.
  • incomes,
    after-tax incomes.
  • productivity,
    increasing productivity,
    increasing productivity to raise incomes,
    keep increasing productivity to raise incomes.
  • household,
    household today,
    American household today,
    the average American household today.
  • incomes,
    increased their incomes,
    productivity gains increased their incomes …
    productivity gains increased their incomes from $60K to $240K.
  • hippies,
    simple-living hippies,
    a few simple-living hippies.

The Digital Privacy Paradox: Small Money, Small Costs, Small Talk | Athey, Catalini, Tucker

Susan Athey, Christian Catalini, Catherine Tucker; The Digital Privacy Paradox: Small Money, Small Costs, Small Talk; working paper; 2017-02-13; 32 pages; landing; Working Paper W23488; National Bureau o Gratuitously Paywall Rough Drafts (NBER); paywall.
Susan Athey, senior fellow, Stanford Institute for Economic Policy Research
Christian Catalini, MIT
Catherine Tucker, MIT

tl;dr → <quote>Consumers say they care about privacy, but at multiple points in the process they end up making choices that are inconsistent with their stated preferences.</quote>

See Item #3, How cool of a result is that? You are safe, you are loved, you are subtle, you are special. You may opt out any time. And we give back to the community.


This paper uses data from the MIT digital currency experiment to shed light on consumer behavior regarding commercial, public and government surveillance. The set- ting allows us to explore the apparent contradiction that many cryptocurrencies offer people the chance to escape government surveillance, but do so by making transactions themselves public on a distributed ledger (a ‘blockchain’). We find three main things.

  1. First, the effect of small incentives may explain the privacy paradox, where people say they care about privacy but are willing to relinquish private data quite easily.
  2. Second, small costs introduced during the selection of digital wallets by the random ordering of featured options, have a tangible effect on the technology ultimately adopted, often in sharp contrast with individual stated preferences about privacy.
  3. Third, the introduction of irrelevant, but reassuring information about privacy protection makes consumers less likely to avoid surveillance at large.


  • Acquisti, A., C. Taylor, and L. Wagman (2016). The economics of privacy. In Journal of Economic Literature 54 (2), 442–492.
  • Allcott, H. and T. Rogers (2014). The short-run and long-run effects of behavioral interventions: Experimental evidence from energy conservation. In The American Economic Review 104 (10), 3003–3037.
  • Athey, S., I. Parashkevov, S. Sarukkai, and J. Xia (2016). Bitcoin pricing, adoption, and usage: Theory and evidence. SSRN Working Paper ssrn:2822729.
  • Barnes, S. B. (2006). A Privacy Paradox: Social Networking in the United States. In First Monday 11 (9).
  • Bertrand, M., D. Karlan, S. Mullainathan, E. Shafir, and J. Zinman (2010). What’s advertising content worth? evidence from a consumer credit marketing field experiment. In The Quarterly Journal of Economics 125 (1), 263–306.
  • Catalini, C. and J. S. Gans (2016). Some simple economics of the blockchain. SSRN Working Paper No. ssrn:2874598.
  • Catalini, C. and C. Tucker (2016). Seeding the s-curve? The role of early adopters in diffusion. SSRN Working Paper No. 28266749,
  • Chetty, R., A. Looney, and K. Kroft (2009). Salience and taxation: Theory and evidence. In The American Economic Review 99 (4), 1145–1177.
  • DellaVigna, S. (2009). Psychology and economics: Evidence from the field. In Journal of Economic Literature 47 (2), 315–372.
  • DellaVigna, S., J. A. List, and U. Malmendier (2012). Testing for altruism and social pressure in charitable giving. In The Quarterly Journal of Economics, qjr050.
  • DellaVigna, S. and U. Malmendier (2006). Paying not to go to the gym. The American Economic Review 96 (3), 694–719.
  • Gneezy, U. and J. A. List (2006). Putting behavioral economics to work: Testing for gift exchange in labor markets using field experiments. In Econometrica 74 (5), 1365–1384.
  • Greenstein, S. M., J. Lerner, and S. Stern (2010). The economics of digitization: An agenda for the National Science Foundation (NSF).
  • Gross, R. and A. Acquisti (2005). Information revelation and privacy in online social networks. In Proceedings of the 2005 ACM Workshop on Privacy in the Electronic Society (WPES ’05), New York, NY, USA, pp. 71–80. ACM: ACM.
  • Harrison, G. W. and J. A. List (2004). Field experiments. In Journal of Economic Literature 42 (4), 1009–1055.
  • Ho, D. E. and K. Imai (2008). Estimating causal effects of ballot order from a randomized natural experiment the california alphabet lottery, 1978–2002. In Public Opinion Quarterly 72 (2), 216–240.
  • Kim, J.-H. and L. Wagman (2015). Screening incentives and privacy protection in financial markets: a theoretical and empirical analysis. In The RAND Journal of Economics 46 (1), 1–22.
  • Landry, C. E., A. Lange, J. A. List, M. K. Price, and N. G. Rupp (2010). Is a donor in hand better than two in the bush? evidence from a natural field experiment. In The American Economic Review 100 (3), 958–983.
  • Madrian, B. C. and D. F. Shea (2001). The power of suggestion: Inertia in 401 (k) participation and savings behavior. In The Quarterly Journal of Economics 116 (4), 1149–1187.
  • Marthews, A. and C. Tucker (2015). Government Surveillance and Internet Search Behavior SSRN Working Paper No. ssrn:2412564,
  • Miller, A. and C. Tucker (2011). Can healthcare information technology save babies? In Journal of Political Economy (2), 289–324.
  • Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system.
  • Narayanan, A., J. Bonneau, E. Felten, A. Miller, and S. Goldfeder (2016). Bitcoin Cryptocurrency Technologies. Princeton University Press: Princeton NJ.
  • Posner, R. A. (1981). The economics of privacy. In The American Economic Review 71 (2), 405–409.



Publishers withdraw more than 120 gibberish papers | Nature (2014)

Publishers withdraw more than 120 gibberish papers; Richard Van Noorden; In Nature; 2014-02-24.
Teaser: Conference proceedings removed from subscription databases after scientist reveals that they were computer-generated.


  • Cyril Labbé
    • (postdoc?), Joseph Fourier University, Grenoble, FR
    • Demo:
    • 2010-04, Used SCIgen to generate 102 fake papers by a fictional author called Ike Antkare [see pdf].
    • <quote>t. Last year, researchers at the University of Granada, Spain, added to Labbé’s work, boosting their own citation scores in Google Scholar by uploading six fake papers with long lists to their own previous work2.</quote>
  • Some Study; in Scientometrics in 2012.
  • Accused of admitting autogenerated papers
    • 2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering; in Chengdu, CN.
  • SCIgen
    • 2005
    • Massachusetts Institute of Technology (MIT)
  • arXiv vs. snarXiv, a satire site.


  • Labbé, C. & Labbé, D. Scientometrics 94, 379–396 (2013).
  • López-Cózar, E. D., Robinson-García, N. & Torres-Salinas, D. In Journal of the Association of Information Science Technology. 65, 446–454 (2014).
  • Cyril Labbé, Ike Antkara, One of the great stars in the scientific firmament, International Society for Scientometrics and Informetrics Newsletter, 2010 6(2), pages 48-52, hal-00713564.


  • Alan Sokal
    • New York University
    • Social Text
    • 1996
    • Scheme: constructed paper (entitled something like) Hermaneutics of Quantum Gravity
  • John Bohannon
    • a reporter
    • Science
    • 2013
    • Scheme: convinced 150 open-access journals to accept a deliberately flawed study for publication.


  • Monika Stickel, director of corporate communications, IEEE.
  • Ruth Francis, UK head of communications, Springer.

I Didn’t Tell Facebook I’m Engaged, So Why Is It Asking About My Fiancé? | The Atlantic

I Didn’t Tell Facebook I’m Engaged, So Why Is It Asking About My Fiancé?; ; In The Atlantic; 2012-03-14.

The Downward Ramp | NYT

The Downward Ramp; Thomas B. Edsall; an oped; In The New York Times (NYT); 2014-06-10.


HTTP with Accountability (HTTPA)

Transforming the web into a HTTPA ‘database’; ; In ZD Net; 2014-06-13.
Summary: Researchers under Tim Berners-Lee at MIT develop a new HTTP, dubbed HTTPA, a web protocol with accountability.

HTTP With Accountability: Tim Berners-Lee Wants To Reinvent The World Wide Web; Staff; Science 2.0; 2014-06-13.

Who’s using your data?; Larry Hardesty; MIT News Office; 2014-06-13.
Teaser: New Web technology would let you track how your private data is used online.

tl;dr => a promotion of a paper, forthcoming


  • Tim Berners-Lee
  • Oshani Seneviratne, a graduate student in electrical engineering and computer science, MIT
  • Lalana Kagal, a principal research scientist at CSAIL, MIT
  • A paper to appear at the IEEE’s Conference on Privacy, Security and Trust, 2014-07.
  • <quote>Every time the server transmitted a piece of sensitive data, it would also send a description of the restrictions on the data’s use. And it would also log the transaction, using the URI, in a network of encrypted servers.</quote>
  • Audit Servers
  • Distributed Hash Tables (DHT)
  • Decentralized Information Group(DIG), CSAIL, MIT

How Finance Gutted Manufacturing | Boston Review

How Finance Gutted Manufacturing; Suzanne Berger; In Boston Review; 2014-03-10.

Suzanne Berger, Raphael Dorman-Helen Starbuck Professor of Political Science at MIT, is author of Making in America: From Innovation to Market.

Silicon Valley’s Youth Problem | NYT

Silicon Valley’s Youth Problem; Yiren Lu; In The New York Times; 2014-03-12.

The future of jobs: The onrushing wave | The Economist

Editor; The onrushing wave; In The Economist; 2014-01-18.
Teaser: Previous technological innovation has always delivered more long-run employment, not less. But things can change