tl;dr → A paean. “The mobile” is the Bee’s Knees!
and → The signal is given: a new S-Curve is commencing.
and → The unbunding / rebundling / unbundling / rebundling cycle, a metaphor of growth-cum-renewal.
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!
<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>
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>
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.
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>
tl;dr → There is peril to display advertising systems, which are mid-sized linkbaitists and newspapers. Paywalls are indicated.
Two recent disruptions to the online advertising market are the widespread use of ad-blocking software and proposed restrictions on third-party tracking, trends that are driven largely by consumer concerns over privacy. Both primarily impact display advertising (as opposed to search and native social ads), and affect how retailers reach customers and how content producers earn revenue. It is, however, unclear what the consequences of these trends are. We investigate using anonymized web browsing histories of 14 million individuals, focusing on “retail sessions” in which users visit online sites that sell goods and services. We find that only 3% of retail sessions are initiated by display ads, a figure that is robust to permissive attribution rules and consistent across widely varying market segments. We further estimate the full distribution of how retail sessions are initiated, and find that search advertising is three times more important than display advertising to retailers, and search advertising is itself roughly three times less important than organic web search. Moving to content providers, we find that display ads are shown by 12% of websites, accounting for 32% of their page views; this reliance is concentrated in online publishing (e.g., news outlets) where the rate is 91%. While most consumption is either in the long-tail of websites that do not show ads, or sites like Facebook that show native, first-party ads, moderately sized web publishers account for a substantial fraction of consumption, and we argue that they will be most affected by changes in the display advertising market. Finally, we use estimates of ad rates to judge the feasibility of replacing lost ad revenue with a freemium or donation-based model.
Black Lives Matter Global Network, a “chapter” of Black Lives Matter (BLM)
Clarkstown, New York
Rockland County, upstate New York
We the People, a protest group
<quote>Michael Sullivan, ex? Chief of Police, Clarkstown, New York, was suspended 2016-07, fired 2017-09. A special prosecutor had been hired by the town supervisor (the equivalent of a mayor) to investigate the unit and had uncovered evidence of improper surveillance targeting Sullivan’s perceived political enemies—including the county sheriff, a judge, the supervisor himself, and even residents who supported cutting the police department’s budget. The investigation resulted in more than a dozen disciplinary charges against Sullivan—who was found guilty for 11 of them. He was fired in September 2017.</quote>
Background for the piece…
Department of Homeland Security (DHS)
uses Geofeedia into Fusion Centers, to prospectively track persons of interest via Instagram, Facebook, Twitter. ref
<quote><snip/>had obtained search warrants to access Facebook accounts of “anti-administration activists.</quote>
…and “civli rights leaders”
<quote>well aware of the FBI’s history of surveillance against civil rights leaders and the Black Panthers</quote>
2017-10, <quote>[the FBI] had identified a new surveillance category for “black identity extremists”</quote>
Definition “black identity extremists,” a precrime designator
Are [people] who are assessed to have a propensity to attack police in retaliation for police violence against African Americans.
Strategic Intelligence Unit, Police Department, State of New York.
Clarkstown, New York
[police] used a “geofence” twice in the month.
Nyack, New York [State]
Clarkstown, New York [State]
Stephen Cole-Hatchard, ex-? Sergeant,ex-”head,” Strategic Intelligence Unit, Police Department, Clarkstown.
Peter Modafferi, ex-chief detective, District Attorney’s Office, Rockland County, New York
Michael Sullivan, ex-Chief of Police, Clarkstown, New York,
was suspended 2016-07, was fired 2017-09 [see above].
William O. Wagstaff III, attorney for the plaintiffs.
For Color, Backgorund & Verisimilitude
Chris Conley, staff, attorney-cert., ACLU of Northern California.
Susan Freiwald, professor, Law School, University of San Francisco (USF).
Cedric L. Richmond, D, LA, chairman, Congressional Black Caucus.
How Smartphones Hijack Our Minds; Nicholas Carr; In The Wall Street Journal (WSJ); 2017-10-06 (paywalled).
Teaser: Research suggests that as the brain grows dependent on phone technology, the intellect weakens
tl;dr → <quote>[people] aren’t very good at distinguishing the knowledge we keep in our heads from the information we find on our phones or computers. </quote>
The Shallows: What the Internet Is Doing to Our Brains, W. W. Norton, 2011-06-08, 404 pages, ASIN:0393339750: Kindle: $9, paper: $10+SHT.
Utopia Is Creepy, and Other Provocations, W. W. Norton; 2016-09-06, 384 pages, ASIN:0393254542: kindle: 10, paper: $8+SHT.
and [many] other books
…in the boosterist and anthologized thinkpiece longread blogpost genres e.g.
The Glass Cage: How Our Computers Are Changing Us, W. W. Norton, 2015-09-08, 288 pages, ASIN:0393351637: Kindle: $9, paper: $6+SHT.
IT Matter? Information Technology and the Corrosion of Competitive Advantage, Harvard Business Review Press, 2004-04, 208 pages, ASIN:1591394449, Kindle: $20, paper: $0.01+SHT.
“available cognitive capacity”
“brain drain” (a technical term, attributed to Ward et al.)
“data is memory without history”, attributed to Cynthia Ozick.
the “Google effect,” strictly, pertains to information retrieval.
…they are bad…
Maarten Bos, staff, Disney.
Kristen Duke, staff, University of California, San Diego (UCSD).
Ayelet Gneezy, staff, University of California, San Diego (UCSD).
William James, boffo, quoted circa 1892.
Expertise: psychology, philosophy.
Honorific: pioneering .
Cynthia Ozick, self.
Trade: scrivener, dissent.
Betsy Sparrow, staff, Columbia University.
Adrian Ward, professor, marketing professor, University of Texas at Austin (UTA)
Expertise: psychology, cognitive psychology
Daniel Wegner, Harvard.
Many Unlock Events Per Day; video segment; ABC News; WHEN?.
…Where more Americans get their news than from any other source [grammar police be damned!]
Some Survey, Gallup, 2015.
tl;dr → <quote>Over 50% “can’t image” life without a cellphone.</quote>
Adrian Ward, et al. A Study. That. Shows. In Journal of Experimental Psychology. 2015. pubmed:26121498
Some Authors. Another Study. That. Shows. In Journal of Computer-Mediated Communication, 2015.
Adrian Ward (U.T. Austin), Kristen Duke, Ayelet Gneezy (UCSD), Maarten Bos (Disney). Study. That. Shows. 2015.
Adrian Ward (UTA) et al.More Study. That. Shows. In Journal of the Association for Consumer Research. 2017-04. preprint. DOI:10.1086/691462.
Some Authors (University of Southern Maine). Another Study. That. Shows. In Social Psychology. psycnet:2014-52302-001
More Authors. Yet Another Study. That. Shows. In Applied Cognitive Psychology. 2017-04. another study. DOI:10.1002/acp.3323.
tl;dr → N=160 & WEIRD (students) at the University of Arkansas at Monticello.
Even More Authors. Even More Study. That. Shows. In Labour Economics; 2016.
More Authors. More Study. That Shows. In Journal of Social and Personal Relationships. 2013. paywall. DOI:10.1177/0265407512453827.
tl;dr → N=192, WIERD (students), University of Essex in the U.K.
Betsy Sparrow (Columbia), Daniel Wegner (Harvard), et al. Authors. Yet Another Study. That. Shows. In Science (Magazine). 2011. paywall.
ahem → <ahem>it’s an implications performance.</ahem>
tl;dr → Tadayoshi et al. are virtuosos at these performance art happenings. Catchy hook, cool marketing name (ADINT) and press outreach frontrunning the actual conference venue. For the wuffie and the lulz. Nice demo tho.
and → They bought geofence campaigns in a grid. They used close-the-loop analytics to identify the sojourn trail of the target.
and → Er… don’t use Grindr.
The online advertising ecosystem is built upon the ability of advertising networks to know properties about users (e.g., their interests or physical locations) and deliver targeted ads based on those properties. Much of the privacy debate around online advertising has focused on the harvesting of these properties by the advertising networks. In this work, we explore the following question: can third-parties use the purchasing of ads to extract private information about individuals? We find that the answer is yes. For example, in a case study with an archetypal advertising network, we find that — for $1000 USD — we can track the location of individuals who are using apps served by that advertising network, as well as infer whether they are using potentially sensitive applications (e.g., certain religious or sexuality-related apps). We also conduct a broad survey of other ad networks and assess their risks to similar attacks. We then step back and explore the implications of our findings.
ADINT (a title); Some ‘bot (That Certain Robot, TCR); In BoingBoing; 2017-10-18.
tl;dr → cut & paste, merely points to the Wired piece.