10,000 New Yorkers. 2 Decades. A Data Trove About ‘Everything.’

Linked Data | Internet of Everything | Privacy

By MARC SANTORAJUNE 4, 2017

Paul W. Glimcher, a neuro-economist at New York University who created the Human Project, which will track thousands of New Yorkers over two decades or more. Credit Todd Heisler/The New York Times 

 

 

 

Your phone, in all likelihood, knows more about you than your doctor. Your credit card company knows your likes and dislikes better than your closest friend. Google knows your thoughts, and even completes your sentences. Your telephone service provider knows where you are at all times. Facebook, for many, knows more than the rest combined.

But Paul W. Glimcher, a neuro-economist at New York University, looks at all that data and sees a “train wreck.”

For all of Silicon Valley’s cheerleading of “big data,” Mr. Glimcher said it had yet to be used to effectively solve some of society’s most vexing problems.

So he was intrigued when Miyoung Chun, the executive vice president for science programs at the Kavli Foundation and a leader of the Obama administration’s Brain Initiative, approached him five years ago about what the future of big data might look like. Read more...

Big Doubts About Big Data - The Chronicle Review - The Chronicle of Higher Education

October 13, 2014

Big-Data Doubts

Mark Shaver for The Chronicle Review

By Emma Uprichard

As you may have noticed, Big
Data is, well, big. Very BIG. So big it’s becoming boring, a bandwagon
term that everyone needs to talk about to show that they can play the
game, keep up with the gossip, or do contemporary small talk. Many
observers once thought the craze would go away, and some wish it had.
But the hype keeps growing through data streams and dreams.




The term itself is quite phenomenal. Its capacity to morph into so
many forms and functions is akin to a powerful shape-shifter, taking on
new meaning amid a new data-driven grammar. Put any noun in front of the
term, and you have just named an area of life that Big Data is going to
somehow transform: health, finance, education, marketing and retail,
sports, environment and climate, housing and cities. Put an adjective in
front of it—gloopy, colored, short, fat, thin—and you’ll see it catch
on, at least in some circles, for at least a short time.




But mostly the grammar of Big Data is about verbs and what we can do
with it: predict; steer, shape; harvest, harness, mine; sort, store,
synthesize; track and trace; innovate and transform; optimize, maximize,
visualize; and so on. So many of those verbs are about maximizing the
capacity to model human behavior: intervening, faster and more
efficiently than ever before, now, in real time—or as quickly as
possible, so we can shift from forecasting to "now-casting" and prevent traffic hot spots, epidemics, riots, and civil unrest.  Read more...

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• Big Doubts About Big Data (chronicle.com)
• How To Identify Fake Big Data Products (forbes.com)
• A Conversation with Arthur Whitney (2009) (queue.acm.org)
• 5 Shortcuts to Keep Data on Risks in Perspective (blogs.scientificamerican.com)
• Online Article: Nothing Personal; Just the Business Layer (codemag.com)