Algorithmic Accountability: The Big Problems | SAP

Tom Slee (SAP); Algorithmic Accountability: The Big Problems; Their Blog; 2017-10.

tl;dr → You have problems, SAP has expertise in this practice area. Call now.

Original Sources

Yvonne Baur, Brenda Reid, Steve Hunt, Fawn Fitter (SAP); How AI Can End Bias; In Their Other Blog, entitled The D!gitalist; 2017-01-16.
Teaser: Harmful human bias—both intentional and unconscious—can be avoided with the help of artificial intelligence, but only if we teach it to play fair and constantly question the results.


  • The Canon is rehearsed.
  • General Data Protection Regulation (GDPR)
    • European
    • “in effect in” 2018 (2018-05-28).

Anti-patterns, Negative (Worst) Practices

  • Bad statistics
  • Ill-defined scales
  • Bad Incentives
  • Lack of transparency

Five Axes of Unfairness
Unfairness ↔ Disparate Impact

  1. Target variables
  2. Training data
  3. Feature selection
  4. Proxies
  5. Masking


  • Explanation
  • Transparency
  • Audits
  • Fairness


  • Solon Barocas, self [Princeton]
    Trade: theorist.
  • Cynthia Dwork, self [Microsoft]
    Trade: pioneer [theorist]..
  • Seth Flaxman, staff, Oxford University.
    Trade: expert.
  • Bryce Goodman, staff, Oxford University.
    Trade: expert.
  • Cathy O’Neil, self.
    Trade: data scientist statistician who works on a Macintosh Computer and lives in San Francisco.
  • Frank Pasquale, professor, law [Maryland]
    Ttrade: educator.
  • Andrew Selbst, self [U.S. .Court of Appeals]
    Trade: theorist


“Information Bottleneck” Theory Cracks Open the Black Box of Deep Learning | Quanta Magazine

New Theory Cracks Open the Black Box of Deep Learning; Natalie Wolchover; In Quanta Magazine, also syndicated out to copied onto; 2017-10-09; pdf.
Teaser: A new idea called the “information bottleneck” is helping to explain the puzzling success of today’s artificial-intelligence algorithms — and might also explain how human brains learn.

tl;dr → the “information bottleneck,” an explainer; as the metaphor.
and → <quote><snip/> that a network rids noisy input data of extraneous details as if by squeezing the information through a bottleneck, retaining only the features most relevant to general concepts.</quote>


Phases of Deep Learning

“fitting” or “memorization”
Is shorter (than the longer phase).The network learns labels for training data.
“compression” or “forgetting”
Is longer (than the shorter phase).
The network observes new data, to generalize against it. The network
optimizes (“becomes good at”) generalization, as measured differential with the (new) test data.


  • Alex Alemi, Staff, Google.
    …quoted for color, background & verisimilitude; a booster.
  • William Bialek, Princeton University.
  • Kyle Cranmer, physics, New York University.
    …quoted for color, background & verisimilitude; a skeptic.
  • Geoffrey Hinton,
    …quoted for color, background & verisimilitude; is non-committal, “It’s extremely interesting.”

    • Staff, Google
    • Faculty, University of Toronto
  • Brenden Lake, assistant professor, psychology & data science statistics, New York University.
    In which a data scientist is a statistician who performs statistics on a Macintosh computer in San Francisco; and Prof. Lake’s employer is the university system of the State of New York.
  • Pankaj Mehta
  • Ilya Nemenman, faculty, biophysics, Emory University.
  • Fernando Pereira, staff, Google.
  • David Schwab
  • Andrew Saxe, staff, Harvard University.
    Expertise: Artificial Intelligence, The Theory of The Science of The Study of The Neuron; a.k.a. neuroscience.
  • Ravid Shwartz-Ziv, graduate student, Hebrew University, Jerusalem, IL.
    Advisor: Naftali Tishby
  • Naftali Tishby, Hebrew University, Jerusalem, IL.
  • Noga Zaslavsky, graduate student, Emory Univerity.
    Advisor: Ilya Nemenman.


  • Stuart Russell, éminence grise.
  • Claude Shannon, theorist.


Yes, there were papers referrenced.  See notes..


In archaeological order, in Quanta Magazine

Separately noted..

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.


Five Disruptions Reshaping Marketing as We Know It | ChiefMarTec

Scott Brinker (ChiefMarTec); Five Disruptions Reshaping Marketing as We Know It; a whitepaper; ChiefMarTec; 2017-04; 21 pages; video.

  1. Digital Transformation
  2. Open source and APIs
  3. Vertical Competition
  4. Digital Everything
  5. Artificial Intelligence


  • 2016 “Stackies” Awards, their in-house intra-industry promotional anointment

Open Sources

ad server
web analytics
marketing automation
video management
SB Socioboard
social media marketing
business intelligence
Oxwall O
online community
data integration
customer surveys
agile management


How Brendan Eich plans to flip the online ad model and fix the web | Digiday

How Brendan Eich plans to flip the online ad model and fix the web; Lucia Moses; In Digiday; 2017-09-28.

tl;dr → Brendan Eich, Brave, Basic Attention Token (BAT); privacy, ad block, tracker block.
and → <quote>It all sounds like utopian, Silicon Valley hippie talk.</quote>


  • Brendan Eich, boffo
    • ex-Mozilla, since 2014.
    • the story:
      • Proposition 8 (no gay marriage)
      • Mozilla is diverse, but not for this.
    • (a) (the) JavaScript booster
  • Brave (browser)
    • 1M UU (one mega-user, one million installs).
    • 7M UU (seven mega-users, seven million installs).
  • Brave (Inc?, LLC?, what?)
    • Brendan Eich
    • Brian Bondy
  • Basic Attention Token (BAT)
    • 2017-03
    • <blink><buzzzz!>Something about The Blockchain</blink></buzzzz!>
      Something about <quote>micropayments in exchange for <snip/> reading [words]</quote>
    • Currently it’s a “donation” scheme.
  • Google
    • Chrome
    • GMail
    • the lockin
    • Will have ad block (soon)
    • Accelerated Mobile Pages (AMP)
  • Facebook
    • an AMP clone.
  • Mozilla, Firefox
  • <quote>Chrome owned 56 percent of the browser market share at the end of 2016, while Mozilla’s Firefox bleeds market share.</quote>
  • Newspaper Association of America
    News Media Alliance

    • 2016-01, was unhappy
      wasn’t there a C&D
    • 2,000 members
      Exemplars, with the honorific: “the stalwarts”

      • The New York Times
      • The Washington Post
      • Dow Jones
  • Lumascape
  • Federal Trade Commission (FTC)
  • Interactive Advertising Bureau (IAB)
  • Safari
    • Blocks auto-play video
    • Blocks tracking
  • General Data Protection Regulation (GDPR)



  • Facebook
  • Google
  • TMZ
    • header bidding
    • tracking


For color, background & verisimilitude…

  • Harvey Anderson, ex- svp of business and legal affairs, Mozilla.
  • Ben Barokas, co-founder of Sourcepoint; ex-Google;
    is a competitor, Sourcepoint has a competing product.
  • David Chavern, CEO, News Media Alliance.
  • Andreas Gal, ex-Mozilla.
  • Darren Herman, staff, Bain Capital; ex-Mozilla
    uses the word “fucking” as a sentence enhancer.
  • Peter Thiel, boffo.


In Digiday

Social Discounting Theory answers “How Much Is the Future Worth?” | Slate

How Much Is the Future Worth?; ; Series “Future of the Future,” in Slate;2017-09 (no specific date)


  • Discount Rate
    you know, like from undergraduate B-school.
  • Social Discounting Theory
  • Integrated Assessment Model (IAM)
  • Social Cost of Carbon (SCC)
  • Climate Policy Design


  • pure time preference, definitional; at some educational site
  • three “500-year” storms
  • The Stern Review, referenced via their archives.
  • Some Other Report about The Stern Review, UK; referenced in Their Archives
  • Some book; in Google Books.
  • Some Article; Some Cub Reporter; In The Guardian; 2008-06-26.
  • Nordhaus? Stern?; Some Paper (Stern’s approach to discounting); Hosted at Yale University; 2008-05-03.
  • Nordhaus, Stern; Some Article; with the word “science”; Hosted at Yale University
  • Laurie Johnson; Some Paper; In Some Venue, Surely; 2012; paywall
  • Climate Cost Project
  • An Article; In Science News; WHEN?
  • Burke, Craxton, Kolstad, Onda; Some Paper (a “deep and subtle discussion of discount rates”); 2016.
    <quote>First, we discuss the social cost of carbon (SSC) and how it could be improved, including the consideration of catastrophes, nonmarket damages, impacts in developing countries, growth versus level effects, adaptation, and the use of discount rates. We then turn our attention to the integrated assessment models (IAMs) used in the computation of the SCC, arguing that, in addition to the need for incorporating the latest scientific understanding, we need to examine leading models’ consideration of uncertainty, the aggregation of heterogeneous agents, and technology options. Finally, we look at ways to improve climate policy design, in particular through the use of ex post analyses, insights from behavioral economics, the consideration of technology policy, and considerations specific to the developing world. With significant time and resources, we believe that progress can be made and many of these gaps filled.</quote>
  • canceling the entire project; Some Cub Reporter (SCR); In Politico; 2017-03.
  • Houston Cyptess; at Pro Publica.


In Slate

Governments turn tables by suing public records requesters | Associated Press

Governments turn tables by suing public records requesters; Ryan J. Foley; In News of The Associated Press; 2017-09-18.


Some litigation, Kentucky, Louisiana, Michigan, Oregon.

Original Sources

Jonathan Peters; Some Some Article; In Columbia Journalism Review; “in” 2015,


Jonathan Peters; professor of journalism, University of Kansas


The Future of Computing Depends on Making It Reversible | IEEE Spectrum

The Future of Computing Depends on Making It Reversible; Michael P. Frank; In IEEE Spectrum; 2017-08-25; in print as “Throwing Computing Into Reverse.”, 2017-09.

Michael P. Frank, a senior member of the technical staff, Sandia National Laboratories, in Albuquerque, NM..


  • Rolf Landauer, IBM, 1961.
  • Charles Bennet
  • K. Eric Drexler
  • Ralph Merkle





In Jimi Wales’ Wiki


In IEEE Spectrum

The Washington Post’s robot reporter, Heliograf, has published 850 articles in the past year

tl;dr → they are using robots so that reporters can focus on “high value work.” i.e. most of what you’re reading, right now, today, even at the big brightly-lit news shops, is farmed content auto-formfill-assembled drek.


  • Heliograph
  • The Associated Press
  • USA Today


  • Jeremy Gilbert, director of strategic initiatives, The Washington Post.
  • Francesco Marconi, strategy manager, and AI co-lead (that’s an actual title?) Associated Press.
  • Seth Lewis, professor, of journalism, University of Oregon.


The Suitcase Words
  • Artificial Intelligence (AI)

GitLab freezes GraphQL project amid looming Facebook patent fears | The Register

GitLab freezes GraphQL project amid looming Facebook patent fears; Thomas Claburn; In The Register; 2017-09-20.
Teaser: Promising query language garbled by legal lingo

Original Sources

Jamie Hurewitz (GitLab); A Post, WHEN? (recently)
Jamie Hurewitz is senior director of legal affairs, GitLab.



  • Paul Berg, expert.
  • Jamie Hurewitz is senior director of legal affairs, GitLab.
  • Dennis Walsh, expert, attorney.