Through the scanner darkly, darkly; and the future of information

scanner eye by jvaughan

The digitization of everything is an elixir for some people. It spawns visions. If we could only open up all the data…how about taking the college facebook and putting it on line …. why not street-level and satellite-level photos of every home in the U.S. of A. Ok! Build and sell a picture database of all the license plates on all the cars and trucks on the road? Gee, I don't know. The Department of Fatherland Security recently moved to create a national license-plate recognition database to garner data from commercial and law enforcement tag readers. Then, with NSA skulduggery still a little too current, they canceled it a' sudden. Note that commercial tag reader systems remain out there. DRN or Digital Recognition Network provides "data that puts your company in the driver's seat" helping you repo your assets (e.g., cars) and reduce asset charge-offs. Together with Vigilant Solutions of Livermore, Calif., the company is fighting a Utah law that banned the private, commercial use of the license plate scanning technology. DRN was the only speaker at a hearing on the topic at the Mass State House earlier this month. They see it as their first amendment right to make money taking pictures of stuff. When you think of all the big data uses of license plates beyond immigration, repossession, well its boggling. Probably their more big data apps to come, that we cant even think of, but why not collect the data for that big day in the future? The undercurrent is, if I don’t want the NSA or DFS to do it, why would I want some Starbuck's guzzling nerdster to? Re-jiggering of status quo is what massive levels of data can do. Google has met a few people who don't want pictures of their houses in Google's database and, apparently, will remove them if you ask. I don't think First Amendment rights to take pictures are a foundation for massively scaled reproduction, and would not my license plate in some software company data services offering. In "Who owns the Future," Jaron Lanier lays down some framework for a more credible understanding of where we want to go with data and privacy. By asking questions of the future he takes a sharper picture of the present: "... as technology advances i this century, our present intuition about the nature of information will be remembered as narrow and shortsighted." - Jack Vaughan

Related 
http://www.foxnews.com/politics/2014/02/19/dhs-plan-for-national-license-plate-tracking-system-raises-privacy-concerns/
http://www.googletutor.com/asking-google-to-remove-your-home-from-maps-street-view/
http://betaboston.com/news/2014/03/05/a-vast-hidden-surveillance-network-runs-across-america-powered-by-the-repo-industry/
http://consumerist.com/2014/03/05/the-repo-man-might-be-scanning-your-cars-license-plate-and-location-selling-the-data/
http://www.drndata.com/Content/Docs/DRN%20Vigilant%20Utah%20Press%20Release.pdf
http://www.drndata.com/
http://vigilantsolutions.com/

I have heard all about Grantland

I'm reading interesting book called Talk Nerdy to Me. This is by the ultra-hip Grantland (as in Grantland Rice) crew whose totally cool cat's sportswriting on the web packaged here bears the blistering subtitle of "Talk Nerdy to Me: Grantland's Guide to the Advanced Analytics Revolution" (sold out says the site today) and it is a more interesting take on big data analytics then many other tomes that you maybe have anted up for. Let's start with "Belichick's Fourth and Reckless" by contributor Bill Simmons. The story centers at times maniacally but on Patriots coach Bill Belichick's famously strange call on fourth-and-2 on November 15, 2009 against Peyton Manning and the Baltimore Colts. It trumps many other coaching failures in Boston sports  fabled history of failures, he writes. It was such a strange call – the Pats were on their own 28, with less than 2 minutes to play and a lead - that people began to look at the statistics trying to see what was in the coaches – the great, mind you - mind. Simmons goes over some of the stats and pretty well proves how at times statistics can lie, or at least outsmart the lazy intellectual (you know the type that works for media!)Bellichick's crazy gambit had backing in stats. "Bellichick did play the percentages if you took those percantages at face value." But Simmons points out for example, that statistics (that going for fourth down had an 80.5 % chance of succeeding) don’t account for the obvious confused funk that had descended on the Pat's in that final quarter.  That there is a big difference between fourth-and-2 on a Sunday in September against a lazed Falcons outfit than there is in November against Petyon Bloody Manning and the Colts. Stop and grok on this:

"I know it's fun to think stats can settle everything, but they can't and they don’t."

If you are playing the statistics card, which one do you choose? Writes Simmons. There are all sorts of statistics to count, but which are the ones to count on? Pulling out all the stop here I am going to recall Mark Twain, or maybe Vin Scully, plenty of argue over who said it:

Statistics are used much like a drunk uses a lamppost: for support, not illumination.

Beware, you would be masters of the big data universe! I said that. - Jack Vaughan

Duck duck goose

Today's clamor around big data will one day subside. Like the love affair in Cole Porter's Just One of Those Things, it is ''too hot not too cool down''.  It is a sort of process;  vendors and media builds things up and then break things down again. Take as example a recent New York Times story entitled "Big (Bad) Data." The item revolves around the case of A&E's Duck Dynasty star Phil Robertson. His antigay comments in a magazine article went viral on Twitter, and A&E execs, as if in the thrall of big data analytics, suspended him from the show. Then, the Twitter sentiments rebounded, big data was recalibrated, and Robertson was back in. The Times' story suggests the first response was wrong, the second right. But time may prove otherwise. This episode in review is hardly an indictment, although that is how the writer or his editors would have it.  The advent of big data does not obviate the need for exes to have full liberal educations with philosophy, ethology, ethics and economics studies under their belts.  The execs of A&E give vent to the old saw: If you don't know where you're going, any road will take you there.

http://tmagazine.blogs.nytimes.com/2014/02/26/media-report-big-bad-data/

Going down to Stasiland

In the era of the Stasi there was an overarching NSA style apparatus. Projections  were mainly of 'grays and dour greens.' Citizen informants were networked nodes. These were the browser cookies of the time. But they were embedded not in a browser but in a physical world. This was when humans were computers, or computers were humans, have it as you will. It may have been an apex of sorts, though "the jury is still out." The platform as you might say was East Germany, or GDR  (1946-1990). Then and there was created an internet of spies, detecting on their neighbors – on each other – with fault tolerance, high availability and cyclical redundancy checking. Psychological Zesetung, or Brainwave Decomposition, was a common application type. There were 8 Stasi agents for every 5 citizens. Today the file of the concern is available on the world wide zeb. The Stasi Records Agency (BStU) is responsible for making the records of the State Security Service of the former GDR accessible to the public. Every individual has the right to request to view his own personal file. There are files on Michael Jackson.  In 1954, Angela Merkel was born in the West but soon her family moved into Stasiland. Her pater was a Lutheran minister, which made young Angela and outsider in an outside land. Her family's ability to visit the West made her father's connections suspect. Her grade in compulsory Marxist-Lentilist education was 'sufficient – or passing'  (making her a student much like me-oh!) One day Merkel became presient of reunified Germany. When she discovered the U.S. N.S.A. was tapping her cell phone, a slew of 'grays and dour greens' danced in her momentarily fevered and dizzy field of vision.

Today's Data Drippings

Data as an enthusiasm or even hobby is in the air. As noted in an Economist article (Briefing: Clever Cities: The Multiplexed Metropolis –Sept 7 2013, p.21. ) But does close inspection of the results to date tell us the enthusiasm is warranted? Is this truly like the introduction of electricity to the city? Who benefited from the introduction of electricity, and if data is as powerful a game changer, who will benefit most on this go-round? "The importance of political culture will remain," according to the anonymous Economist writer (Ludwig Siegele).

Nist data symposium

Nist is looking into Big data and measurement thereof. Upcoming is a symposium in March. Symposium Topics:
Understanding the Data Science Technical Landscape:
Primary challenges in and technical approaches to complex workflow components of Big Data systems, including ETL, lifecycle management, analytics, visualization & human-system interaction.
Major forms of analytics employed in data science.
Improving Analytic System Performance via Measurement Science
Generation of ground truth for large datasets and performance measurement with limited or no ground truth.
Methods to measure the performance of data analytic workflows where there are multiple subcomponents, decision points, and human interactions.
Methods to measure the flow of uncertainty across complex data analytic systems.
Approaches to formally characterizing end-to-end analytic workflows.
Datasets to Enable Rigorous Data Science Research
Useful properties for data science reference datasets.
Leveraging simulated data in data science research.
Efficient approaches to sharing research data.

http://www.nist.gov/itl/iad/data-science-symposium-2014.cfm

IBM shows its plan to move Watson forward

The IBM Watson supercomputer has garnered a lot of attention in recent years, but it's entering a particularly critical passage now. What happens next could influence the future paths of data analytics generally, and IBM specifically -- for better or for worse. This week, IBM showed its plan to move Watson forward. Virginia Rometty, the company's chairman, president and CEO, said IBM would invest more than $1 billion in a new business group dedicated to commercializing Watson. That figure includes $100 million for venture investments to create an ecosystem of application developers and other business partners. The challenge, though, will be to take highly technical machine learning software from the lab -- and the game show milieu -- to the business mainstream.

 http://searchdatamanagement.techtarget.com/opinion/For-IBM-Watson-no-easy-answers-on-commercial-cognitive-computing

How the memes were won

Cerf and Kahn on Future Web