[Busec] TIP: Wed 9/21 Privacy and Behavioral Economics

Sharon Goldberg goldbe at cs.bu.edu
Sat Sep 17 10:25:39 EDT 2011

Topics in Privacy lunch this Wednesday.  Acquisti has done very
interesting work, so this should be interesting. I'm not sure if I'll
be able go, but if you are interested, drop me an email and maybe I'll
come with you.

---------- Forwarded message ----------
From: David Parkes <parkes at eecs.harvard.edu>
Date: Fri, Sep 16, 2011 at 2:43 PM
Subject: [Econcs-general] LAB: TIP: Wed 9/21 Privacy and Behavioral Economics
To: econcs-general at eecs.harvard.edu

Topics in Privacy (TIP) Luncheon
9/21/2011 from noon to 1pm in room K332 at 1737 Cambridge Street, Cambridge,
MA 02138.

Title: Privacy and Behavioral Economics: The Control Paradox and Other

Speaker: Alessandro Acquisti


How do we make decisions about the privacy and security of our personal
information? In this talk, I will first highlight how research in behavioral
economics can help us make sense of apparent inconsistencies in privacy (and
security) decision-making. Then, I will present results from a number of
experiments conducted at Carnegie Mellon University, including a recent
study of the complex relationship between privacy and control. Normatively,
privacy is often associated with an individual's control over her personal
information. However, in a series of experiments, we investigated the effect
that granting more control over information revelation has on individuals'
propensities to share sensitive data. We found that real or perceived
control over information publication increases the likelihood that
individuals will disclose sensitive information, even when the objective
risks associated with such disclosures actually increase. We call this the
privacy control paradox. Our findings highlight that merely granting users
more "control" over their personal information or privacy settings does not
guarantee that they will be able to find a desirable balance between
information disclosure and information protection. In fact, technologies
that make individuals feel more in control over the publication of personal
information may potentially carry the unintended consequence of eliciting
more risky disclosures.


 Alessandro Acquisti is an Associate Professor of Information Systems
and Public Policy at the Heinz College, Carnegie Mellon University, and the
co-director of the CMU Center for Behavioral Decision Research (CBDR). His
research has promoted the application of behavioral economics to the study
of privacy and information security decision making, and the study of
privacy risks and privacy behavior in online social networks. Alessandro has
been the recipient of the PET Award for Outstanding Research in Privacy
Enhancing Technologies, the IBM Best Academic Privacy Faculty Award, and
multiple Best Paper awards. Alessandro's research on privacy is eminently
interdisciplinary: his manuscripts have been published in leading journals
across multiple disciplines (including the Proceedings of the National
Academy of Science, the Journal of Consumer Research, Marketing Science,
Information Systems Research, the Journal of Comparative Economics, ACM
Transactions on the Internet). Several of his findings have been featured in
media outlets such as the New York Times, the Wall Street Journal, the
Washington Post, CNN, NPR, and others. His 2009 study on the predictability
of Social Security numbers (SSNs) was featured in the "Year in Ideas" issue
of the NYT Magazine, and has contributed to the change in the assignment
scheme of SSNs, announced in 2011 by the US Social Security Administration.
His research has been funded by the National Science Foundation, Transcoop
Foundation, Microsoft, and Google. Alessandro holds a PhD from UC Berkeley,
and Master degrees from UC Berkeley, the London School of Economics, and
Trinity College Dublin.

More information is available at
<http://dataprivacylab.org/TIP/schedule.html>. TIP is a weekly session for
brainstorming and discussing any aspect of privacy hosted by the Data
Privacy Lab <http://dataprivacylab.org>.

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Sharon Goldberg
Computer Science, Boston University

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