The Coming Tech Backlash | Ross Mayfield

Ross Mayfield; The Coming Tech Backlash; In That Certain Blog at possibly entitled Shift (too much cobranding), sponsored by Newco, but centrally hosted at Medium; 2017-01-03.
Teaser: Tech innovation is killing jobs, not foreign scapegoats, and revolt after Trump will be Luddite
Summary: The tech industry played an influential role in the outcome of the US Presidential election. Not just in providing the medium for Fake News and propaganda. The root cause is job destruction by Automation — that drove a base of dissatisfied rust-belt voters to support Trump. Job destruction is accelerating, and if Tech doesn’t get ahead of this problem, there will be a significant populist backlash against the industry and it’s ability to progress.

Ross Mayfield is CEO & Co-founder, Pingpad; ex-LinkedIn, SlideShare, Socialtext, RateXchange.

tl;dr → The future is foretold. The hipster socialism. A startup is promoted. Robots bad. Need Jobs for the unpublished classes. the lede is buried.  The working classes need Slack addon, Pingpad, that create jobs; a bot-augmented wiki knowledge base.


<quote>Here’s what Ross Mayfield is doing about the Backlash. Also, for an example of augmentation in action, see our bot-augmented wiki for Slack teams


  • “Tech”, The Tech, The Tech Industry
    a.k.a. publishing on the online web, the blogging.
  • McKinsey
  • Oxford
  • <pro-forma><cliché>The future is unevenly distributed</cliché></pro-forma>
  • The Singularity
  • Jobs
    • Truck Driver
    • Bloggist?
  • Basic Income
    • (semi-)Universal Basic Income
    • YCombinator has a “fellows” grant program
  • Pot (a.k.a. Marijuana)
  • Google
    • Google Busses
  • post-ethics era
    • GOP
  • post-truth era
    • Trump
  • Joi Ito, Jeff Howe; Whiplash: How to Survive Our Faster Future; Grand Central Publishing; 2016-12-06; 320 pages; ASIN:1455544590: Kindle: $15, paper: $5+SHT; separately filled.
  • Sack
    • Slack Channel


  • Quartz
  • GeekWire
  • Some Study. That. Shows, branded as An Oxford Study
  • Some Study. That. Shows, branded as A McKinsey Study

As Google Fights Fake News, Voices on the Margins Raise Alarm | NYT

As Google Fights Fake News, Voices on the Margins Raise Alarm; Daisuke Wakabayashi; In The New York Times (NYT); 2017-09-26.

tl;dr → Google Bad. They change their indexing; publishers beholden to search-generated traffic sourcing schemes are affected.
and → <quote>The New York Times could not find the same level of traffic declines at all of those publications, based on data from SimilarWeb</quote> <ahem>then why write the article about a non-event?</ahem>


The voices on the margins,
The marginal voices.
  • Socialists, specifically, David North
  • SourceFesters
  • Breitbartists
  • Frank Pasquale


Frank Pasquale; The Black Box Society: The Secret Algorithms That Control Money and Information; Harvard University Press; 2016-08-29; 320 pages; ASIN:0674970845: Kindle: $10, paper: $11+SHT; separately filled.


  • World Socialist Web Site (WSWS)
  • Project Owl, of Google
    • Announced 2017-04.
    • <google>algorithmic updates to surface more authoritative content</google>
      <ny-times>stamp out fake news stories from its search results</ny-times>
  • Google performs search results page rating
    • A panel method, of living humans.
    • The panel is paid-staff of Google.
    • N=10,000.
  • Search Quality Evaluator Guidelines; Google; 2013.
  • Alexa, of Amazon,
    not the robot, the web analytics shop.
    has independent traffic estimates.
  • David North (WSWS); open letter to Google, World Socialist Web Site (WSWS); 2017-08-25.
  • SimilarWeb, a web analytics firm.
  • some video, unattributed; hosted on SourceFed; 2016-06.
    tl;dr → accuses Google; asserts there is manipulation of the search results.
  • Four Times Google was Linked Directly to Hillary Clinton; Some Screeching Troll (SST); On Breitbart; 2017-08-14


  • is buried.
  • The New York Times (NYT) is not able to replicate or validate the claims of traffic falloff.
    <quote>The New York Times could not find the same level of traffic declines at all of those publications, based on data from SimilarWeb, a web analytics firm. </quote>


  • Michael Bertini, expert, iQuanti.
    iQuanti is a marketing agency.
  • Pandu Nayak, spox, fellow, Google.
  • David North, the editorial chairman, World Socialist Web Site
  • Frank Pasquale, professor, law, information law, University of Maryland.


In The New York Times (NYT)…

As IBM Ramps Up Its AI-Powered Advertising, Can Watson Crack the Code of Digital Marketing? | Ad Week

As IBM Ramps Up Its AI-Powered Advertising, Can Watson Crack the Code of Digital Marketing?; ; In Ad Week (Advertising Week); 2017-09-24.
Teaser: Acquisition of The Weather Company fuels a new division

tl;dr → Watson (a service bureau, AI-as-a-Service) is open for business.


The 4 pillars of Watson Advertising.
  1. Targeting, Audience construction & activation.
  2. Optimization, Bidding & buying.
  3. Advertising, Synthesis of copy and creative.
  4. Planning, Campaign planning for media buying.

Separately noted.


Help Your Users `Save-Data` (an HTTP header for Chrome) | CSS-Tricks

Help Your Users `Save-Data` Jeremy Wagner; In CSS-Tricks; 2017-10-02..

Original Sources


  • Apache configuration settings
  • Android Chrome only.
  • Chrome plugins to make it work “on the desktop.”

Grand ideas from 12 disruptive marketing thought leaders distilled into 6 marketing & advertising predictions for 2030 | Michael Haupt

1Michael Haupt; Grand ideas from 12 disruptive marketing thought leaders distilled into 6 marketing & advertising predictions for 2030; In His Blog, centrally hosted on Medium; 2016-11-11.
Teaser: Grand ideas from 12 disruptive marketing thought leaders distilled into 6 marketing & advertising predictions for 2030.

tl;dr → What’s hot circa 2015: Interactive Voice Response, The Data Licentiate, The Universal Dossier, (Ever-more) Precise Targeting, Propensity Prediction


  1. The End of Privacy Concerns
  2. The Transfer of Data Ownership
  3. The End of Broadcast Advertising
  4. The Rise of Personal ChatBots
  5. The Shift Toward Evolved Enterprises (more services, more persuasion)
  6. The Shift From Communicating to Predicting


  1. Jay Abraham
  2. Paul Adams
  3. Alex Bogusky
  4. Cindy Gallop
  5. Seth Godin
  6. Bob Hoffman
  7. Naomi Klein
  8. Kalle Lasn
  9. Mary Meeker
  10. Al Ries & Laura Ries
  11. Luke Sullivan
  12. Monte Wilson
  • Peter Diamandis
  • Ray Kurzweil
  • Gerd Leonhard
  • Mat Schlicht


  • A universal history approach.
    as technological megashifts
    • Funding: $23M, Series B funding.
  • Additive Manufacturing
    his neologism for 3-dimensional Printing (3D Printing)
  • The consumer (the users) are the product, of the social venues.
  • Something about predictive analytics (propensity scoring) in content marketing
    but the concept is not developed.
  • Precision>target audiencesto timely circumstances</quote>


Understood as transitions current state to next state.

Concern Current State Next State
Focus Science, Technology, Engineering and Math (STEM) Creativity, Originality, Reciprocity, Empathy and Intuition (COREI)
World Rational, Logical, Predictable Random, Empatetic, Emotional
World View Mechanistic Ecological
Interactions Competition and Manipulation Collaboration and Problem Solving
Organizations Hierarchical Command & Control Circles, Swarms, Swirls
Fetish Efficiency, Cost Reduction, Speed, Profit Connection, Nurturing, Love.


In order of apparance in the work…

Social Venues

  • Google
  • Twitter
  • Facebook
  • LinkedIn
  • Siri of Apple
  • Cortana of Microsoft
  • Now of Google
  • Echo of Amazon
    (sic) Alexa
  • Google
  • Microsoft
  • HTC
  • Samsung


  • Infinite Computing
  • Artificial Super-Intelligence
  • Sensors & Networks
  • Robotics
  • 3D Printing
  • Virtual and Augmented Reality:


Jay Abraham
Jimi Wales’ Wiki.
Paul Adams
ex-Google, ex-Facebook, “head” of product, Intercom.
Grouped; Publisher?; 2011; ASIN:0321804112: Kindle: $20?
Alex Bogusky
Jimi Wales’ Wiki.
The 9-Inch Diet; Publisher; 2009; ASIN:157687320X: Kindle: $20?
tl;dr → Burger King is bad.
Peter Diamandis
Cindy Gallop
Honorific: is brash.
Make Love Not Porn, a talk, at Theater, Entertainment, Distraction (TED), hosted on YouTube; WHEN? (these performances typically run ~20 min).
Seth Godin
Claimed: has popularized “permission marketing.”
Bob Hoffman
Scrivener, the Ad Contrarian, a blog <quote>who’s been “making marketers uncomfortable since 2013.</quote>
Naomi Klein
Jimi Wales’ Wiki
Honorific: an activist.
Claimed: branding is oppression.
No Logo; Publisher?; 2000; ASIN:000734077X: Kindle: $20?
Ray Kurzweil
Chief futurist, Google.
Kalle Lasn
Jimi Wales’ Wiki
Founder, Adbusters (magazine).
“Chief architect,” Occupy Wall Street Movement.
Claimed: consumerism is evil.
Culture Jam: America’s Suicidal Binge; Publisher?; WHEN? ASIN:B00DY4O5GE: Kindle: $20?
Gerd Leonhard
Seer, booster.
Mary Meeker
Staff, Partner title?, Kleiner Perkins, Caulfield & Byers (KPCB)
Claimed: publishes Internet Trends, serial slideware, annual.
Al Ries
Jimi Wales’ Wiki
Claimed: “the father of positioning”
Al Reis, Laura Reis, The Fall of Advertising; self-published (ebook); 209; ASIN:B000FC11PG: Kindle: $20?
Website, Al & Laura Ries, father and daughter marketing strategists
Laura Ries
Jimi Wales’ Wiki
Al Reis, Laura Reis; The Fall of Advertising; ibidem.
Website, ibidem.
Luke Sullivan
Hey Whipple, Squeeze This; Publisher?; WHEN? ASIN:B01AVKWLCS: Kindle: $20?; Website Twitter.
tl;dr → <quote>a diatribe</quote>.
Matt Schlicht
Monte Wilson
ex-Adobe, Oracle, EMC.
Some Talk; At Some Venue, hosted On YouTube; 2016.
tl;dr → on the scientism of “sided” brain thinking.



In His Blog


Also His Blog

W3C Payment Request API is Being Implemented in All Major Browsers | ProgrammableWeb

W3C Payment Request API is Being Implemented in All Major Browsers; Janet Wagner; In ProgrammableWeb; 2017-09-20.

Original Sources



  • Chrome,
  • Edge,
  • Firefox,
  • WebKit.
  • Facebook
    • Facebook Messenger Extensions SDK
  • Samsung
    • Samsung Internet for Android 5.


For color, background & verisimilitude…

  • Ian Jacobs, Lead, Web Payments Working Group, W3C.
  • Lukasz Olejnik, expert
    • Dr. Lukasz Olejnik
    • site

As Microsoft Joins Coalition for Better Ads, Blocking by Browsers Looks Set to Spread | Advertising Age

As Microsoft Joins Coalition for Better Ads, Blocking by Browsers Looks Set to Spread; ; In Advertising Age; 2017-09-20.

tl;dr → Microsoft has joined the Coalition for Better Ads.

Original Sources

Rik van der Kooi (Microsoft); Microsoft Joins The Coalition For Better Ads; In Their Blog; 2017-09.
Rik van der Kooi is corporate VP for search advertising, Microsoft.


  • Microsoft
  • Coalition for Better Ads (CBA)
    • for Chrome
    • of Google
  • Edge
    • a browser
    • of Microsoft
  • <could><eventually>unilaterally block ads that coalition research editorial has deemed annoying.</eventually></could>
  • Google
  • Will call it “ad filtering” going forward
    <quote>The term “blocking” carries a lot of baggage.</quote>
  • <quote>Chrome browser will start “filtering” in “early” 2018.
  • Digital Content Next
    • a trade association
    • for online publishers
    • member, CBA
  • Adblock Plus
    • Eyeo
    • <quote>charges [large] companies fees to participate in its whitelisting program<quote>
    • The business model is extortion, attributed to Randall Rothenberg.
      The spox of Microsoft did not <quote>immediately respond to a request for comment on that point.</quote> [but did she later?]


  • Procter & Gamble
  • Unilever
  • WPP’s GroupM
  • Facebook
  • Thomson, of Reuters
  • The Washington Post
  • Interactive Advertising Bureau (IAB)
  • Association of National Advertisers (4As)
  • Digital Content Next, a trade association for online publishers and a coalition member itself.
  • <ahem>…and more!</ahem>


For color, background &&amp verisimilitude…

  • A spox, a ‘droid, presented as a woman, Microsoft.
  • Rik van der Kooi, corporate VP for search advertising, Microsoft.
  • Satya Nadella, CEO, Microsoft.
  • Jason Kint, CEO, Digital Content Next.
  • Randall Rothenberg, CEO, Interactive Advertising Bureau (IAB).


In Advertising Age

On the Protection of Private Information in Machine Learning Systems: Two Recent Approaches | Abadi, Erlingsson, Goodfellow, McMahan, Mironov, Papernot, Talwar, Zhang

Martín Abadi, Ulfar Erlingsson, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Nicolas Papernot, Kunal Talwar, Li Zhang (Google); On the Protection of Private Information in Machine Learning Systems: Two Recent Approaches; arXiv:1708.08022; 2017-08-28; 5 pages.


The recent, remarkable growth of machine learning has led to intense interest in the privacy of the data on which machine learning relies, and to new techniques for preserving privacy. However, older ideas about privacy may well remain valid and useful. This note reviews two recent works on privacy in the light of the wisdom of some of the early literature, in particular the principles distilled by Saltzer and Schroeder in the 1970s.


  1. J. H. Saltzer, M. D. Schroeder, “The protection of information in computer systems,” Proceedings of the IEEE, vol. 63, no. 9, pp. 1278–1308, 1975. DOI:10.1109/PROC.1975.9939 .
  2. W. H. Ware, “Security and privacy: Similarities and differences,” in Proceedings of the April 18-20, 1967, Spring Joint Computer Conference, ser. AFIPS ’67 (Spring). ACM, 1967, pp. 287–290. DOI:10.1145/1465482.1465525.
  3. R. Turn, W. H. Ware, “Privacy and security in computer systems,” Jan. 1975. P5361.
  4. Erlingsson, V. Pihur, A. Korolova, “RAPPOR: randomized U. aggregatable privacy-preserving ordinal response,” in Proceedings of the 21st ACM SIGSAC Conference on Computer and Communications Security, ACM, 2014, pp. 1054–1067. DOI:10.1145/2660267.2660348.
  5. M. Abadi, A. Chu, I. J. Goodfellow, H. B. McMahan, I. Mironov, K. Talwar, L. Zhang, “Deep learning with differential privacy,” in Proceedings of the 23rd ACM SIGSAC Conference on Computer and Communications Security, 2016, pp. 308–318. DOI:10.1145/2976749.2978318.
  6. N. Papernot, M. Abadi, U. war, “Semi-supervised knowledge transfer for deep learning from private training data,” CoRR, vol. arXiv:1610.05755, 2016, performed at the 5th International Conference on Learning Representations, 2017.
  7. Y. LeCun, Y. Bengio, G. Hinton, “Deep learning,” In Nature, vol. 521, pp. 436–444, 2015.
  8. I. Goodfellow, Y. Bengio, A. Courville, Deep Learning. MIT Press, 2016.
  9. C. Dwork, F. McSherry, K. Nissim, A. D. Smith, “Calibrating noise to sensitivity in private data analysis,” in Proceedings of the Theory of Cryptography, Third Theory of Cryptography Conference, TCC 2006, 2006, pp. 265–284. DOI:10.1007/11681878 14.
  10. S. P. Kasiviswanathan, H. K. Lee, K. Nissim, S. Raskhodnikova, A. D. Smith, “What can we learn privately?” In SIAM Journal Computing, vol. 40, no. 3, pp. 793–826, 2011. DOI:10.1137/090756090.
  11. K. Chaudhuri, C. Monteleoni, A. D. Sarwate, “Differentially private empirical risk minimization,” In Journal of Machine Learning Research, vol. 12, pp. 1069–1109, 2011.
  12. D. Kifer, A. D. Smith, A. Thakurta, “Private convex optimization for empirical risk minimization with applications to high-dimensional regression”, in Proceedings of the 25th Annual Conference on Learning Theory, 2012, pp. 25.1–25.40.
  13. S. Song, K. Chaudhuri, A. Sarwate, “Stochastic gradient descent with differentially private updates,” in Proceedings of the GlobalSIP Conference, 2013.
  14. R. Bassily, A. D. Smith, A. Thakurta, “Private empirical risk minimization: Efficient algorithms and tight error bounds,” in Proceedings of the 55th IEEE Annual Symposium on Foundations of Computer Science. IEEE, 2014, pp. 464–473. DOI:10.1109/FOCS.2014.56.
  15. R. Shokri, V. Shmatikov, “Privacy-preserving deep learning,” in Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security. ACM, 2015, pp. 1310–1321. DOI:10.1145/2810103.2813687.
  16. J. Hamm, Y. Cao, M. Belkin,”>“Learning privately from multiparty data”< in Proceedings of the 33nd International Conference on Machine Learning (ICML) 2016, 2016, pp. 555–563.
  17. X. Wu, A. Kumar, K. Chaudhuri, S. Jha, J. F. Naughton, “Differentially private stochastic gradient descent for in-RDBMS analytics,” CoRR, vol. arXiv:1606.04722, 2016.
  18. I. Mironov, “On significance of the least significant bits for differential privacy,” in Proceedings of the 19th ACM SIGSAC Conference on Computer and Communications Security. ACM, 2012, pp. 650–661. DOI:10.1145/2382196.2382264.
  19. M. Fredrikson, S. Jha, T. Ristenpart, “Model inversion attacks that exploit confidence information and basic countermeasures,” in Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security. ACM, 2015, pp. 1322–1333. DOI:10.1145/2810103.2813677.
  20. R. Shokri, M. Stronati, V. Shmatikov, “Membership inference attacks against machine learning models,” CoRR, vol. arXiv:1610.05820, 2016.
  21. B. W. Lampson, “Protection,” Operating Systems Review, vol. 8, no. 1, pp. 18–24, 1974. DOI:10.1145/775265.775268.
  22. R. Gilad-Bachrach, N. Dowlin, K. Laine, K. E. Lauter, M. Naehrig, J. Wernsing,”>“CryptoNets: Applying neural networks to encrypted data with high throughput and accuracy”, in Proceedings of the 33nd International Conference on Machine Learning (ICML) 2016, 2016, pp. 201–210.
  23. C. Zhang, S. Bengio, M. Hardt, B. Recht, O. Vinyals, “Understanding deep learning requires rethinking generalization,” CoRR, vol. arXiv:1611.03530, 2016, performed at the 5th International Conference on Learning Representations, 2017.
  24. A. Neelakantan, L. Vilnis, Q. V. Le, I. Sutskever, L. Kaiser, K. Kurach, J. Martens, “Adding gradient noise improves learning for very deep networks,” CoRR, 2015. arXiv:1511.06807.
  25. T. G. Dietterich, “Ensemble methods in machine learning,” in International workshop on multiple classifier systems. Springer, 2000, pp. 1–15.
  26. K. Nissim, S. Raskhodnikova, A. Smith, “Smooth sensitivity and sampling in private data analysis,” in Proceedings of the 39th Annual ACM Symposium on Theory of Computing, ACM, 2007, pp. 75–84.
  27. M. Pathak, S. Rane, B. Raj, “Multiparty differential privacy via aggregation of locally trained classifiers,” in Advances in Neural Information Processing Systems, 2010, pp. 1876–1884.
  28. I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, Y. Bengio, “Generative adversarial nets,” in Advances in Neural Information Processing Systems, 2014, pp. 2672–2680.
  29. T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, X. Chen, “Improved techniques for training GANs,” arXiv:1606.03498, 2016.
  30. J. H. Saltzer, M. F. Kaashoek, Principles of Computer System Design: An Introduction,/em>. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2009.
  31. S. L. Garfinkel, Design principles and patterns for computer systems that are simultaneously secure and usable, Ph.D. dissertation, Massachusetts Institute of Technology, Cambridge, MA, USA, 2005.
  32. R. Smith, “A contemporary look at Saltzer and Schroeder’s 1975 design principles,” In IEEE Security and Privacy, vol. 10, no. 6, pp. 20–25, Nov. 2012. DOI:10.1109/MSP.2012.85.
  33. S. Ioffe, C. Szegedy,”>“Batch normalization: Accelerating deep network training by reducing internal covariate shift”, in Proceedings of the 32nd International Conference on Machine Learning (ICML) 2015, 2015, pp. 448–456.
  34. C. Dwork, K. Kenthapadi, F. McSherry, I. Mironov, M. Naor, “Our data, ourselves: Privacy via distributed noise generation,” in Proceedings of EUROCRYPT (EUROCRYPT). Springer, 2006, pp. 486–503.
  35. I. Mironov, “Renyi differential privacy,” CoRR, vol. arXiv:1702.07476, 2017.
  36. A. Kerckhoffs, “La cryptographie militaire”, In Journal des sciences militaires, vol. IX, pp. 5–38, Jan. 1883.
  37. D. Proserpio, S. Goldberg, F. McSherry, “Calibrating data to sensitivity in private data analysis: A platform for differentiallyprivate analysis of weighted datasets,” In Proceedings of the Conference Sponsored by the VLDB Endowment (VLDB), vol. 7, no. 8, pp. 637–648, Apr. 2014. DOI:10.14778/2732296.2732300.

You Are Already Living Inside a Computer | The Atlantic

You Are Already Living Inside a Computer; Ian Bogost; In The Atlantic; 2017-09-14.
Teaser: Futurists predict a rapture of machines, but reality beat them to it by turning computing into a way of life.

Ian Bogost
  • The Ivan Allen College Distinguished Chair in media studies
  • A professor of interactive computing at the Georgia Institute of Technology
  • Play Anything: The Pleasure of Limits, the Uses of Boredom, and the Secret of Games
    Ian Bogost; Basic Books; 2016-09-13; 288 pages; ASIN:0465051723: Kindle: $19, paper: $7+SHT; site
  • Biography, by The Atlantic.

tl;dr → Computers are a fetish (just like any other). The “smart gadgets” are silly.
and → <quote>This new cyberpunk dystopia is more Stepford Wives, less William Gibson.</quote>
and → <quote>There’s some tragedy in this future. <snip/>  It’s [computers] they might remain just as ordinary and impotent as they are today, and yet overtake us anyway.</quote>


  • planned obsolescence
  • Google
  • fidget spinners
  • Roomba
  • GasWatch
  • connected toasters
  • Smartphone-connected bike locks .
  • Samsung TV
  • Automated Content Recognition (ACR)
  • CIA
  • hacked TVs
  • hacked baby monitors
  • botnet
  • Hilton
  • Hampton Inn
  • Twitter
  • Denial of Service (DoS) attack
  • Ring, a “smart” doorbell
  • <quote>these are not the robots we were promised</quote>, attributed to Nicholas Carr, as a “wisecrack.”
  • Alan Turing, paper, 1950
  • Turing machine, 1936
  • Silicon Valley
  • Watson, an “Artificial Intelligence (AI)”, IBM
  • Something about how Twitter will trial Watson to detect abuse.
  • Earlier this year, Chris Moody, Twitter’s vice president of data strategy, because <quote>stopping abuse [as] the company’s first priority</quote>, attributed to Chris Moody, VP Stratego®, Twitter
  • Turing Test
  • reverse Turing Test (the CAPTCHA)
  • Uber
    honorific: <quote>The ride-hailing giant</quote>
  • Ring
  • the “disruption”
  • intelligent machines
  • robot apocalypse
  • pleasure of connectivity.
  • early dystopic scenarios
  • the actions computers take become self-referential
  • cyberpunk dystopia
  • Stepford Wives
  • William Gibson.
  • “hyperemployment”
  • Facebook
  • Google
  • Nick Bostrom
  • Artificial Intelligence (AI)
  • “superintelligence”
  • robot apocalypse.
  • David Chalmers
  • Ray Kurzweil
  • the “singularity”
  • Google, which operates
  • a division devoted to human immortality


  • GasWatch
  • Nest
  • Nokē
  • Roomba


  • Nick Bostrom
  • Nicholas Carr
  • David Chalmers
  • William Gibson
  • Ray Kurzweil
  • Chris Moody, vice president of data strategy, Twitter
  • Alan Turing,
  • Joseph Weizenbaum


The editor has helpfully placed certain sentences of the essay in the 50pt font to develop a sort of “spinal navigation” to the piece; and so you can’t miss the point, given all the words.

  • Computers already are predominant, human life already takes place mostly within them, and people are satisfied with the results.</quote>
  • People don’t seek out computers in order to get things done; they do the things that let them use computers.
  • People choose computers as intermediaries for the sensual delight of using computers.
  • The Turing test works best when everyone knows the interlocutor is a computer but delights in that fact anyway.
  • Doorbells and cars and taxis hardly vanish in the process. Instead, they just get moved inside of computers.
  • The present status of intelligent machines is more powerful than any future robot apocalypse.






In Jimi Wales’ Wiki


In The Atlantic

Escape The Matrix | Wired

Escape The Matrix: The Internet is the Uncanniest Valley, Don’t Get Trapped There; Virginia Heffernan; In Wired; 2017-09.
Teaser: The Great Tech Panic: The Internet is The Uncanniest Valley
Virginia Heffernan performs the tweeting at @page88.

tl;dr → The techno panic is discursive: internet life is not A Life Well Lived; as such, and wrapped in 2125 words.
and → Computers are a fetish (just like any other).


The Great Tech Publishing Panic of 2017.


Virginia Heffernan; Magic and Loss: The Internet as Art; Simon & Schuster; 2017-06-027; 272 pages; ASIN:1501132679: kindle: $13, paper: $2+SHT.


  • Amazon
    • Alexa, of Amazon
    • Echo, of Amazon
  • Facebook
  • Google
  • Instagram
  • Snapchat
  • Snopes
  • Spotify
  • Twitter
  • YouTube


  • Elaine Scarry, a philosoph.
    • Professor of English and American Literature and Language, the Walter M. Cabot Professor of Aesthetics and the General Theory of Value at Harvard University; via Jimi Wales’ Wiki
  • David Kessler
    • this guy
      David Kessler, expert, popularizer

      • grief counseling
      • adviser to the stars of Hollywood.
    • not this guy
      David Aaron Kessler. In Jimi Wales’ Wiki.

      • pediatrics
      • law
      • Commissioner of the Food &amp Drug Administration (FDA)
  • Masahiro Mori, professor, robtics.


<quote>The same anxiety turned contempt attends much of today’s social media, notably Twitter and Snapchat, where the sheen of fatuousness, cryptic UX, and clubhouse jargon appears designed to humiliate and enfeeble.</quote>

<quote>David Kessler has written about mental illness, thoughts, ideologies, and persistent images of past or future can “capture” a person and stall their mental freedom.</quote>

<quote>Paradoxically, framing the internet as a text to be read, not a life to be led, tends to break, without effort, its spell. Conscious reading, after all, is a demanding ocular and mental activity that satisfies specific intellectual reward centers. And it’s also a workout; at the right time, brain sated, a reader tends to become starved for the sensory, bodily, three-dimensional experience of mortality, nature, textures, and sounds—and flees the thin gruel of text.</quote>
Challenge to the reader: edit this down to ten words, but retain the metaphor of “breaks the spell” and the (physical) “workout” concept.


  • Elaine Scarry, Dreaming by the Book, 1999
    tl;dr → <quote>a manifesto on literature and the imagination.</quote>
  • Arrival of a Train at La Ciotat,, a movie, 1896.
  • The Polar Express, a movie, 2010+ (recent)


The Suitcase Words

Oh my, lots of them…
  • Acela
  • Artificial Intelligence (AI)
  • blockchain
  • Coke
    Diet Coke
  • James Comey
  • cyber, the cyber
    • cyberattack
    • cyberwarefare
  • Diet Coke
  • drones
  • digitization
  • GIF
  • GPS
  • McModern design
  • Mentos
  • OGG (sic)
    Ogg, definition
  • Barack Obama
  • PGP
  • Pokémon Go
  • Redit
    • reditor
    • subredditor
  • Russia
  • Super Mario Odyssey
  • web metropolis
  • UX
  • vapors
    suffering the vapors
  • YouTube