Big Data—New Problems Or Data Regulation Reprise?

1. Big Data—New Problems Or Data Regulation Reprise? Robert H. Sloan Richard Warner

2. What Is “Big Data”? • We use it to refer to refers to the acquisition and analysis of massive collections of information, collections so large that until recently the technology needed to analyze them did not exist. • Omer Tene & Jules Polonetsky, Privacy In The Age Of Big Data: A Time For Big Decision, 64 Stan. L. Rev. Online 63 (2012). • So (because of the “recently”) a moving target.

3. The Data Explosion

4. Important Characteristics • Diverse types of data analyzed together • “Breadcrumbs” versus edited data • The Internet of things • Long-term retention • Unpredictable analysis, use, distribution • Private ownership of the massive databases • Format standardization for sharability • Healthcare

5. New Privacy Problems in Big Data? “We can determine where you work, how you spend your time, and with whom, and with 87% certainty where you'll be next Thursday at 5:35 p.m.” Information aggregators Our data Businesses Government

6. But James Rule, pre-Big Data • Information processing practices now “share a distinctive and sociologically crucial quality: they not only collect and record details of personal information; they are also organized to provide bases for action toward the people concerned. Systematically harvested personal information, in other words, furnishes bases for institutions to determine what treatment to mete out to each individual . . . Mass surveillance is the distinctive and consequential feature of our times.” • James Rule, Privacy in Peril

7. All the Problems Just Exacerbated? • Yes, but perhaps also no. • Does the rise of big data initiate a “phase change”? • The formation of ice is a phase change. • The molecules in water bounce around. The molecules in ice locked together—like a crowd holding hands. • To push the analogy, do we “lock together” in Big Data in ways that create novel situations? • Many seem to think Big Data heralds a phase change. Are they right? • Let’s look at what it does.

8. Discovery • The Altman example—discovering and using symptomatic footprints. • Defining and detecting footprints play a central role in • Business • Research • Government:--consider the financial crime monitoring system illustrated in the next slide--Information feeds into the government for Big Data Analysis.

9. Foreign governments Voluntary information sharing, Reporting requirements Government Reporting Investigation Surveillance Institution Transparency requirements Privacy and security requirements Investigation Consumers and others seeking services

10. Obama and Big Data • “Aiming to make the most of the fast-growing volume of digital data, the Obama Administration today announced a Big Data Research and Development Initiative. By improving our ability to extract knowledge and insights from large and complex collections of digital data, the initiative promises to help solve some the Nation’s most pressing challenges.” • Office of Science and Technology Policy, Obama Administration Unveils “Big Data” Initiative: Announces $200 Million In New R&D Investments (Executive Office of the President, March 29, 2012), http://www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_press_release.pdf.

11. But Strictly Speaking No Phase Change • There is no point at which the “Big Data” molecules suddenly join to form a new structure. • What we have is the cumulative effect of a many changes of degree: 20__? The mid-20th century state The surveillance state This is difference in kind even if there was no phase change point

12. Private Business “Change in Kind” • Big Data gives some established businesses more power. • It creates new entities with new powers. 20__? Shifts in power to distribute goods, services, benefits The mid-20thprivate power structure Not just more of the same

13. Still, New Privacy Problems? • Changed privacy problems. • A particularly complex and difficult tradeoff problem takes center stage. • Big Data presents a much wider range of both risks and benefits--rom detecting drug interactions to reducing emergency room costs to improving police response times.

14. Three Tradeoff Models • Notice and Choice • Legal regulation • Norm-governed transactions

15. Notice and Choice • The options spread out across a spectrum. • Sloan/Warner: (1) Notice and Choice does not yield free and informed consent without constraints on collection, use, distribution, and retention, (2) and the proposed constraints would make poor tradeoffs. Unconstrained Notice and Choice Highly constrained Notice and Choice

16. What We Have—Contractually Realized Unconstrained Notice and Choice Advertising ecosystem Business Government Consumer Payment system Aggregators The answer to “Who owns the data?” is contractual.

17. Legal Regulation 1 • “Hoofnagle’s assumption”: If the vast majority of individuals oppose a business information processing practice, and the market will not ensure that businesses conform to that preference, then legal regulation is called for to eliminate the practice. • This is not true without massive qualification in terms of constraints and consequences: • Constraints—protection against the tyranny of the majority. • Consequences: conflict with other values (including economically bad outcomes) when realized in practice. • So it is “corrected” individual values that should guide regulation.

18. Legal Regulation 2 • “Any judgments about where and how to draw a line against endless, incremental erosion of privacy requires that most elusive of visions—a view of the whole.” • James Rule, Privacy in Peril • “Corrected” regulation is controversial, slow, inaccurate, and often ineffective. • We are at a critical juncture and need an tradeoff method that yields a workable consensus and that is fast, accurate, and effective.

19. Norms • A value-optimal norm may have a value-optimal evolution or it may not. • That evolution, even if value-optimal, may be undesirable (value change). • Novel situations may arise not governed by norms. • In particular, because of long term retention for unpredictable uses. • Trust and Tragedy of the commons issues.