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Alessandro Acquisti
Heinz College & CyLabCarnegie Mellon University
TRUST Autumn 2009 Conference
The economics (and behavioral
economics) of privacy
Agenda
1. From the economics of privacy…
2. … to the behavioral economics of
privacy3. … and soft paternalism: “nudging”
privacy
The economics of privacy
Protection & revelation of personal data flows involve tangible and intangible trade-offs for the data subject as well as the potential data holder
Some studies Conditioning prices on purchase histories
(Marketing Science 2005)… Impact of breaches on stock market valuation
(ICIS 2006)… Impact of data breach notification laws on
identity theft (WEIS 2008)… Impact of gun owners DB publication on crime
(work in progress)…
However…
Attitudes about privacy (Ostensibly,) top reason for not going online… (Harris
Interactive) Billions in lost e-tail sales… (Jupiter Research) Significant reason for Internet users to avoid
Ecommerce… (P&AB) Actual behavior
Dichotomy between privacy attitudes and privacy behavior Spiekermann et al. 2001, Acquisti & Gross 2006’s Facebook
study
Do people really care for privacy?If they do, can they act on their concerns?
If they don’t (or can’t), should policy-makers do so on their behalf?
A rational model of privacy decision making
Should I mention my sexual kinks on MySpace?
A rational model of privacy decision making
Maybe I’ll find a lover... But what about my future job prospects? And what if my parents happen to log on...
A rational model of privacy decision making
)()()1(
1)1(
1itdiitdi costsuqbenefitsup tt
Privacy
$sWTA
WTP
1. Incomplete information E.g.: download DOB/hometown from social
network >> predict member’s SSN (PNAS 2009)
2. Bounded rationality3. Cognitive/behavioral biases, investigated
by behavioral economics & decision research E.g., optimism bias, hyperbolic discounting,
ambiguity aversion, and so forth
Hence: a behavioral, experimental economics of privacy (and information security)
Hurdles which hamper (privacy) decision making
Some previous and ongoing results (2004-2009) Hyperbolic discounting in privacy valuations (ACM
EC 04)… Over-confidence, optimism bias in online social
networks (WPES 05)… Confidentiality assurances inhibit information
disclosure (JDJM 07)… Individuals more likely to disclose sensitive
information to unprofessional sites than professional sites (JDJM 07)…
Privacy and the illusion of control (ongoing work, with Laura Brandimarte)…
The behavioral economics of privacy
Privacy valuations may be not only context-dependent, but also Malleable to non-normative factors In fact, possibly internally inconsistent
Hence, personal disclosures likely to be influenced by subtle framing, which can Downplay privacy concerns Act like 'alarm bells' – triggering concern for
privacy that is often latent Possible explanation for inconsistencies in
information revelation
Can non-normative factors determine inconsistencies in privacy concerns/valuations?
How framing impacts valuations of personal data
Willingness to accept (WTA) money to give away informationvs.
Willingness to pay (WTP) money to protect information
Hypothesis: People assign different values to their personal
information depending on whether they are focusing on protecting it or revealing it
WTA/WTP in the privacy realm
Valuation of private information likely to change depending on whether trade-off between privacy and money is framed as– A problem of protection (WTP)
▪ Firewalls, anonymous browsing, (signing up for do-not-call list)
– A problem of disclosure (WTA)▪ Grocery loyalty cards, sweepstakes, Internet searches
Experimental design
Experimental subjects asked to choose between 2 gift cards We manipulated trade-offs between privacy protection and
value of cards Subjects endowed with either:
$10 Anonymous gift card. “Your name will not be linked to the transactions completed with the card, and its usage will not be tracked by the researchers.”
$12 Trackable gift card. “Your name will be linked to the transactions completed with the card, and its usage will be tracked by the researchers.”
Subjects asked whether they’d like to switch cards From $10 Anonymous to $12 Trackable (WTA) From $12 Trackable to $10 Anonymous (WTP)
Two versions of the experiment
Survey with hypothetical gift card choices
Field experiment with actual gift cards
Hypothetical survey
“Imagine you have received a gift card…” “You have the option to exchange your
card for…” 2x2 conditions between-subjects design
Initial endowment (anonymous vs. identified) Value of tracked card ($12 vs. $10, and $14 vs.
$10) Run February 2008 at cafeterias in
hospitals in Pittsburgh area 190 participants
Results
0%10%20%30%40%50%60%70%80%90%
100%
$10 Anonymous $12 Identified
% choosing anonymous card
Pearson chi2(1) = 4.3631; Pr = 0.037
Field experiment with actual gift cards
Field experiment. Participants stopped at mall, asked to participate in (unrelated) study, offered real gift card for participation in study
Mall patrons given choice between: $10 anonymous gift card (card number not
recorded) vs. $12 identified card (card number and name
recorded) 349 participants
Design
2x2 conditions between-subjects design Endowment conditions (2):
• Endowed with $10 anonymous card
• Endowed with $12 identified card Choice conditions (2):
• $10 anonymous card listed first
• $10 anonymous card listed second
Results
χ2(3) = 30.66, p < 0.0005
52.1
42.2
26.7
9.7
0
10
20
30
40
50
60
Endowed $10 (n=71) Choice $10 vs. $12(n=83)
Choice $12 vs. $10(n=57)
Endowed $12 (n=62)
% c
ho
osi
ng
an
on
ymo
us
$10
card
χ2 (3) = 30.61, p < 0.0005
Implications
WTP vs. WTA discrepancy in privacy valuations
Implication: What people say their data is worth depends on how problem is framed
Therefore, what “value” for privacy should be used in public policy?
Analogies to environmental policy
Overall implications of these studies
People’s concerns for privacy (and security) depend, in part, on priming and framing This does not necessarily mean that people don’t care for
privacy, or are “irrational,” or make wrong decisions about privacy
Rather, it implies that reliance on “revealed preferences” argument for privacy may lead to sub-optimal outcomes if privacy valuations are inconsistent… People may make disclosure decisions that they stand to later
regret Risks greatly magnified in online information revelation
Therefore, implications for policy-making & the debate on privacy regulation E.g., Rubin & Lenard [2001] vs. Gellman [2001], or Chicago
School approach vs. privacy advocates
Which leads us to soft paternalism
“Soft” or asymmetric paternalism: design systems so that they enhance (and sometimes influence) individual choice in order to increase individual and societal welfare Sometimes, even design systems to “nudge”
individuals, exploiting the very fallacies and biases research has uncovered, and tweaking with their incentives, without diminish user’s freedom
Nudging privacy: using soft paternalism to address and improve security and privacy decisions through policy and technology design that anticipates and/or exploits behavioral/cognitive biases▪ (IEEE S&P, forthcoming)
Soft vs. strong paternalism vs. usability
Consider online social networks users who post dates of birth online
Imagine that a study shows some risks associated with revealing DOBs (e.g., SSN predictions) Strong paternalistic solution: ban public provision of
dates of birth in online profiles “Usability” solution : design a system to make it
intuitive/ easy to change DOB visibility settings Soft paternalistic solution?
Nudging privacy
Saliency of information Provide context to aid the user’s decision - such as
visually representing how many other users (or types of users) may be able to access that information
Default settings By default, DOBs not visible, unless settings are
modified by user Hyperbolic discounting
Predict and show immediately SSN based on information provided
… and so forth
For more info
Google: economics privacy
Visit:
http://www.heinz.cmu.edu/~acquisti/economics-
privacy.htm
Email: [email protected]
However…
Reasons to believe privacy valuations may not
be stable or even consistent
Privacy attitudes vs. privacy behavior dichotomy
▪ Spiekermann et al. 2001, Acquisti & Gross 2006 (Facebook study)
Research in behavioral economics and behavioral
decision research has highlighted that non-normative
factors often affect valuations and decision making in
presence of uncertainty , leading to systematic
inconsistencies in consumers’ preferences
▪ E.g., Simonson & Tversky 1992, Slovic 1995, …
And one big problem with it…
However (one gigantic “however”):
Who are we to say what is “best” for the
user?