be lying around in various supplier operational systems that I won’t have access to (and probably don’t want to—much of it is not worth me bothering about).”
■ In 2011, Julia Angwin and Emily Steel published “Web’s Hot New Commodity:
Privacy” (http://online.wsj.com/
article/SB1000142405274870352900 4576160764037920274.html) in The Wall Street Journal, as part of that paper’s “What They Know” series, which began on July 31, 2010—a landmark event I heralded in “The Data Bubble”
(http://blogs.law.harvard.edu/
doc/2010/07/31/the-data-bubble) and “The Data Bubble II”
(http://blogs.law.harvard.edu/
doc/2010/10/31/the-data-bubble-ii).
Joel Stein also published “Data Mining: How Companies Now Know Everything About You”
(http://www.time.com/time/magazine/
article/0,9171,2058205,00.html), in Time.
The most influential work on the subject in 2011 was “Personal Data:
The Emergence of a New Asset Class”
(http://www.time.com/time/magazine/
article/0,9171,2058205,00.html), a (.pdf) paper published by the World Economic Forum. While the paper focused broadly on economic
opportunities, the word “asset” in its title suggested fungibility, which loaned weight to dozens of other pieces, all making roughly the same case: that personal data is a sellable asset, and, therefore, the sources of that data should be able to get paid for it.
F o r e x a m p l e , i n “ A S t o c k
E x c h a n g e f o r Yo u r P e r s o n a l D a t a ” (http://www.technologyreview.com/
computing/40330/?p1=MstRcnt), on May 1 of this year, Jessica Leber of MIT’s Technology Review visited a research paper titled “A Market for
Unbiased Private Data: Paying Individuals According to Their Privacy Attitudes”
(http://www.hpl.hp.com/research/scl/
papers/datamarket/datamarket.pdf), written by Christina Aperjis and
Bernardo A. Huberman, of HP Labs’
Social Computing Group. Jessica said the paper proposed “something akin to a New York Stock Exchange for personal data. A trusted market operator could take a small cut of each transaction and help arrive at a realistic price for a sale.” She went on to explain:
On this proposed market, a person who highly values her privacy might choose an option to sell her shopping patterns for $10, but at a big risk of not
finding a buyer. Alternately, she might sell the same data for a guaranteed payment of 50 cents.
Or she might opt out and keep her privacy entirely.
You won’t find any kind of opportunity like this today. But with Internet companies making billions of dollars selling our information, fresh ideas and business models that promise users control over their privacy are gaining momentum. Startups like Personal and Singly are working on these challenges already. The World Economic Forum recently called an individual’s data an emerging “asset class”.
Naturally, HP Labs is filing for a patent on the model.
In “How A Private Data Market Could Ruin Facebook”
(http://www.hpl.hp.com/research/scl/
papers/datamarket/datamarket.pdf), also in Technology Review, MTK
wrote, “The issue that concerns many Facebook users is this. The company is set [to] profit from selling user data, but the users whose data is being traded do not get paid at all. That seems unfair.” After sourcing Jessica Leber’s earlier piece, MTK added,
“Setting up a market for private data
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won’t be easy”, and gave several reasons, ending with this:
Another problem is that the idea fails if a significant fraction of individuals choose to opt out altogether because the samples will then be biased towards those willing to sell their data.
Huberman and Aperjis say this can be prevented by offering a high enough base price. Perhaps.
Such a market has an obvious downside for companies like
Facebook which exploit individuals’
private data for profit. If they have to share their profit with the owners of the data, there is less for themselves. And since Facebook will struggle to achieve the kind of profits per user it needs to justify its valuation, there is clearly trouble afoot.
Of course, Facebook may decide on an obvious way out of this conundrum—to not pay individuals
for their data. But that creates an interesting gap in the market for a social network that does pay a fair share to its users (perhaps using a different model [than] Huberman and Aperjis’).
Is it possible that such a company could take a significant fraction of the market? You betcha! Either way, Facebook loses out—it’s only a question of when.
All of these arguments are made inside an assumption: that the value of personal data is best measured in money.
Sound familiar?
To me this is partying like it’s 1999.
That was when Eric S. Raymond published The Magic Cauldron
(http://www.catb.org/~esr/writings/
homesteading/magic-cauldron), in which he visited “the mixed economic context in which most open-source developers actually operate”. In the chapter “The Manufacturing Delusion”
(http://www.catb.org/~esr/writings/
homesteading/magic-cauldron),