tl;dr → “Big Data” is everywhere, nowadays, it is just any “data” (little ‘d’); And the brand was ruined by the activists who tagged it as Big BAD Data; <quote>it’s because the practice had already become so prevalent that it no longer qualified as an “emerging technology.”</quote>
and → Big Data is Facebook; Facebook is bad.
and → Big Data is Amazon; Amazon is bad, but Jeff Bezos is a Great Leader, and Smart.
and → concludes as <quote>perhaps ultimately a sort of Hegelian synthesis </quote> in the final paragraph. <snide> Mistakes will be made, only time will tell, told ya so!</snide> Yup. It’s a Freshman Seminar essay.
You’re reading this cultural analysis and prognostication in Slate. You going to be okay with that? They publish articles with titles such as
- Why the Witch is the Pop-Culture Heronie We Need Right Now,
- Watch the Uncanny Eyeball Installation That Seems to Watch You Back,
- Implanted Medical Devices are Saving Lives. they’re Also Causing Exploding Corpses.
OK? … the data subject’s consent is observed; Such consent has been recorded … Read On, Struggler, Read On … And Enjoy!
- “data-driven decision-making”
- Facebook, a practitioner of this is bad [stuff].
- fetishization of data
- tweet count, at Internet Live Statistics
- <quote>to measure users’ interest</quote>
- <quote>the “like” button</quote>
- <quote>the algorithmically optimized news feed</quote>
- <quote>overrun by clickbait, like-bait, and endless baby photos</quote>
- whereas: “social study” as a situated practice of “science” is fraught,
to wit: <quote>The wider the gap between the proxy and the thing you’re actually trying to measure, the more dangerous it is to place too much weight on it.</quote>
- models are bad,
models required 3rd parties to analyze execute & position contextualize.
- Michelle Rhee, ex-schools chancellor, Washington D.C.
- <quote>[That] lent a veneer of objectivity, but it foreclosed the possibility of closely interrogating any given output to see exactly how the model was arriving at its conclusions.</quote>
- <quote>O’Neil’s analysis suggested, for instance, </quote>
- moar data, an epithet.
c.f. moar defined at know your meme
- “slow food,”
is contra “fast food.”
- Martin Lindstrom
- a Danish citizen
- purveyor to the trades, of advice, upon the domain of marketing
- is a Danish company
- markets to Millennials
- an exemplar is identified,
the trend is: “big data” → “small data”
- parable by Martin Lindstrom
- Chronicle of Lego, a business case
- was data-driven → failure
- used ethographics → success.
- <quote ref=”CNN” date=”2017-09-05″>Lego announced plans to cut roughly 8% of its workforce — 1,400 jobs — as part of an overhaul aimed at simplifying its structure. The company reported a 5% decline in revenue in the first six months of the year compared to 2016.</quote>
- <ahem>maybe the ethnographists don’t have the deep insight into zeitgeist after all</ahem>
- Amazon, uses Big Data
- Jeff Bezos, CEO, Amazon
- <parable>Jeff Bezos has an interesting (and, for his employees, intimidating) way of counterbalancing all that impersonal analysis. On a somewhat regular basis, he takes an emailed complaint from an individual customer, forwards it to his executive team, and demands that they not only fix it but thoroughly investigate how it happened and prepare a report on what went wrong.</quote> filed under: how the great ones do it.
- <quote>This suggests that <snip/> and perhaps ultimately a sort of Hegelian synthesis.</quote>
- machine learning
- deep learning
- autonomous vehicles
- virtual assistants
- The Age of Big Data; Staff; Sunday Review, of the The New York Times (NYT) ; 2012-02-12 (five years ago).
- Michael Lewis, Moneyball, 2003, ASIN:0393057658
tl;dr → boosterism upon the use of analytics within the business operations of a baseball team.
- Big Data Helps Companies Find Some Surprising Correlations; Some Cub Reporter (SCR); In The Wall Street Journal (WSJ); WHEN? (maybe 2014-03-18).
tl;dr → cites the McKinsey output.
- Our Insights Big Data The Next Frontier For Innovation; staff; McKinsey etc. circa 2011
accolade: <quote>seminal McKinsey report from 2011</quote>
- Big Data, Big Impact: New Possibilities in International Development; Bain & Company, commissioned work; World Economic Forum (WEF); 2012.
accloade: <quote>an official report</quote>
- Big Data, Big Deal; Office of the White House, President Barack Obama; 2012-03-29.
tl;dr → Funding of $200M for a “national big data initiative”
- Cathy O’Neil; Weapons of Math Destruction; 2016; ASIN:0553418831
accolade: <quote>her important book</quote>
- Frank Pasquale; The Black Box Society; 2015; ASIN:0674970845.
- Shopping Habits; Some Cub Reporter (SCR); In The New York Times (NYT); 2012-02-10.
tl;dr → <perhaps>that story of Charles Duhigg’s about the [Christian?] girl who is pregnant and Target’s algo finds her in her home and serves her advertisements for the happy arrival, but she isn’t married and her father is unamused.</perhaps>
- Pinterest Congratulates Single Women on Marriage; Some Cub Reporter (SCR); In New York (Magazine); 2014-09.
- Google Apologizes Photos App Tags Two Black People Gorillas; Some Cub Reporter (SCR); In The Verge; 2015-07-01.
- Can An Algorithm Be Racist? Our Analysis Is More Cautious Than Propublicas; Some Cub Reporter (SCR); In the Washington Post; 2016-10-17.
- Staff (ProPublica); Machine Bias Risk Assessments In Criminal Sentencing; In Their Blog/em>; WHEN?
tl;dr → a.k.a. racial bias in recidivism models
- Staff (NPR); Weapons Of Math Destruction Outlines Dangers Of Relying On Data Analytics; In Their Blog; 2016-09-12.
- Tom Bradley Loses Close Contest On [West] Coast; Some Cub Reporter (SCR); In That Certain East Coast Paper Of Record For The Establishment; 1982-11-04.
- overfitting, an explainer, a commentariat, At Quora.
- Zynga Analytics, at its peak; In Some Blog; 2015-06-24.
- Hadoop jobs, general background, cited in Some Blog, some service promotion literature, at SAS.
- Martin Lindstrom; Small Data: The Tiny Clues That Uncover Big Trends; 2016; ASIN:1250118018.
- Brad Stone; The Everything Store; WHEN?; ASIN:0316219282.
- Staff (Gartner); Top Trends In The Gartner Hype Cycle For Emerging Technologies 2017; In Their Blog; 2017.
In archaeological order, in Slate…
- The Real Moneyball Effect Our Fetishization Of Data; Julia Rose West; 2017-09.
- Facebook Invented A Spam Filter For Clickbait: Will It Save You The Right [or The Left?]; 2016-08-04.
- Facebook’s 5 New Reactions Buttons Are All About Data Data Data; 2016-02-24.
- How Facebook S News Feed Algorithm Works; 2016-01.
- How The Hype Cycle Explains Moocs Big Data, VR and Google Glass; 2014-06.
- Facebook News Feed Edgerank Facebook Algorithms Facebook Machine Learning; 2014-04.
- Quants: Bad, a series; WHEN? [some time ago]