and Aaron Roth
Privacy concerns (and mishaps) are escalating in social and economic
settings: many large scale market operations are (in an ad hoc manner)
either negotiating policies for privacy protection, or, conversely,
behaving as brokers for trading private data. This workshop aims to
bring together researchers studying principled methodologies for
dealing with the privacy issues facing modern markets, from the
perspective of both economics and computer science.
This study has recently generated a small literature in the computer
science community, facilitated by the recent advances in "differential
privacy", as a tool for quantifying the harm caused to individuals by
their loss in "privacy". This quantitative theory for privacy provides
for the first time a rigorous tool to allow the formal study of
privacy as an economic quantity.
However, differential privacy forms its own (increasingly technical)
literature, and learning about it might seem to be an imposing
start-up cost for researchers in the EC community interested in
contributing to this literature. One goal of this workshop is to
overcome this startup cost and encourage broader participation in the
study of the economics of privacy. This half day workshop will
begin with a tutorial on differential privacy aimed at the broader EC
community, to be followed by a series of short talks about recent work
in the field.
Call for Participation
Following a tutorial, the workshop will consist of a series of short
talks. We invite the submission of abstracts (500 words or
less), from which we will select a small number (3-5) for
presentation at the workshop. Talks about work in progress and
previously published work are both encouraged. Please
submit your abstracts by April 20
by emailing them to
[at] caltech [dot] edu. Decisions will be made by the end of April
(before the early registration deadline for EC).
||Coffee and Continental Breakfast
||Tutorial on Differential Privacy and Mechanism Design
-- Aaron Roth. See also this survey.
||David Xiao -- "Is Privacy Compatible with Incentives?"
||Mallesh Pai -- "Differential Privacy as a Tool in
Mechanism Design: Approximate Strategyproofness in Large Games"
||Ankit Sharma -- "When Does Differentially Private
||Zhiyi Huang -- "Differentially Private and Truthful
||Gergely Biczók -- "Interdependent Privacy --
Let me Share Your Data"
||Rachel Cummings -- "Individual Preferences for Privacy"
Auction Market for Online Display Advertising"