Communications of the ACM

lated data of one individual isn’t big data. 18 In contrast to Estrin’s work, we do not restrict attention to any particular data vertical. In our case, inversely private data of an individual tends to be on the biggish side10—recall the story of Max Schrems described earlier in this Viewpoint.

References

1. Acquisti, A., John, L., and Loewenstein, G. What is privacy worth? In Privacy Papers for Policy Makers

2010; http://www.futureofprivacy.org/privacy- papers-2010/

2. California S. B. 27. Shine the Light Law. Civil Code x1798.83; http://goo.gl/zxuHUi

3. Estrin, D. What happens when each patient becomes their own “universe” of unique medical data? TedMed

2013; http://www.tedmed.com/talks/show?id=17762

4. Estrin, D. Small data where n = me. Commun. ACM 57,

4 (Apr. 2014), 32–34.

5. Fair and Accurate Credit Transaction Act of 2003, Public Law 108{159, 108th Congress, 117; http://goo. gl/PnpCkv

6. Fair Credit Reporting Act (FCRA), 1970. Title 15 U.S.

Code, sec. 1681; http://www.ftc.gov/os/statutes/fcra.htm

7. Federal Trade Commission. Final Report of the F TC Advisory Committee on Online Access and Security,

2000; http://govinfo.library.unt.edu/acoas/papers/ finalreport.htm

8. Federal Trade Commission. Protecting Consumer Privacy in an Era of Rapid Change, March 2012; http:// tinyurl.com/p6r3cy4

9. Federal Trade Commission. Data Brokers: A Call for Transparency and Accountability, May 2014; http:// alturl.com/dwwy5

10. Gurevich Y., Haiby N., Hudis E., Wing J.M. and Ziklik E.

Biggish: A solution for the inverse privacy problem. Microsoft Research MSR-TR-2016-24 (May 2016); http://research.microsoft.com/apps/pubs/default. aspx?id=266411

11. Gurevich, Y. and Neeman, I. Infon logic: The propositional case. ACM Transactions on Computation Logic 12, 2, article 9 (Jan. 2011).

12. Leon, P.G. et al. Why People Are (Un)willing to Share Information with Online Advertisers. Carnegie Mellon University, Computer Science Technical Report CMU-ISR- 15-106, http://goo.gl/RkqkhJ

13. Or well, G. 1984. Secker and Warburg, London, 1949.

14. Schneier, B. Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World. Norton and Company, 2015.

15. Strom, D. Deborah Estrin wants to (literally) open source your life. I TWorld (May 24, 2013); http://goo. gl/Jsd9CT

16. U.S. Department of Health, Education, and Welfare (HE W). Records, Computers, and the Rights of Citizens. Report of the Secretary’s Advisory Committee on Automated Personal Data Systems (the HE W report), July 1973; https://epic.org/privacy/ hew1973report/

17. Warren, S.D. and Brandeis, L.D. The Right to Privacy.

Harvard Law Review 4, 5 (1890), 193–220.

18. Wikipedia. Big data. (Aug. 2015); https://en.wikipedia.

org/?oldid=675136834

Yuri Gurevich ( gurevich@microsoft.com) is Principal Researcher, Microsoft Research, and Professor Emeritus at the University of Michigan.

Efim Hudis ( efimh@microsoft.com) is Principal Architect at Microsoft, Seattle, WA.

Jeannette M. Wing ( wing@microsoft.com) is Corporate Vice President of Microsoft Research, Redmond, WA.

Copyright held by authors.

FTC report. Here are some additional laws and FTC reports of relevance:

˲ A 2000 report of an FTC Advisory Committee on “providing online consumers reasonable access to personal information collected from and about them by domestic commercial Web sites, and maintaining adequate security for that information” 7;

˲ The 2003 Fair and Accurate Credit Transactions Act providing consumers with annual free credit reports from the three nationwide consumer credit reporting companies; 5

˲ California’s “Shine the light” law of 2003, according to which a business cannot disclose your personal information secretly from you to a third party for “direct marketing purposes” 2; and

˲ A 2014 FTC report that calls for laws making data broker practices more transparent and giving consumers greater control over their personal information. 9

Clearly the law favors transparency and facilitates your access to your inverse private infons.

Market forces. The sticky point is whether companies will share back our personal information. This information is extremely valuable to them. It gives them competitive advantages, and so it may seem implausible that companies will share it back. We contend that companies will share back personal information because it will be in their business interests.

Sharing back personal information can be competitively advantageous as well. Other things being equal, wouldn’t you prefer to deal with a company that shares your personal infons with you? We think so. Companies will compete on (a) how much personal data, collected and derived, is shared back and (b) how convenient that data is presented to customers.

The evolution toward sharing back personal information seems slow. This will change. Once some companies start sharing back personal data as part of their routine business, the competitive pressure will quickly force their competitors to join in. The competitors will have little choice.

There is money to be made in solving
the inverse privacy problem. As shar-
ing back personal information gains
ground, the need will arise to mine large
amounts of customers’ personal data
on their behalf. The benefits of owning
and processing this data will grow, espe-
cially as the data involves financial and
quality-of-life domains. We anticipate
the emergence of a new market for com-
panies that compete in processing large
sets of private data for the benefits of
the data producers, that is, consumers.

The miners of personal data will work on behalf of consumers and compete on how helpful they are to the customers, how trustworthy they are. This emerging market will generate its own pressure on the personal data holders and potentially might find ways to benefit them as well. For example, if you shop at some retailer R your personal data miner M may show you a separate webpage devoted to R, suggest ways for you to save money as you shop there, and show you how R intends to improve your shopping experience. The last part may even be written by R, but—working on your behalf—M may also suggest to you better deals or shopping experiences elsewhere. The retailer R will benefit if it can beat the competition.

Better record keeping. Finally, technology can enhance people’s capacity to take and keep records. For example, your smartphone or wearable device may eventually become a trusted and universal recorder of many things you do. Technology will help people maintain a personal diary effortlessly.

The project “Small Data” lead by Deborah Estrin at Cornell Tech3 pioneers such an approach in the domain of health. “Consider a new kind of cloud-based app that would create a picture of your health over time by continuously, securely, and privately analyzing the digital traces you generate as you work, shop, sleep, eat, exercise, and communicate.” 4