  This paper is a survey of recent work at the intersection of mechanism design
and privacy. The connection is a natural one, but its study has been
jump-started in recent years by the advent of differential privacy, which
provides a rigorous, quantitative way of reasoning about the costs that an
agent might experience because of the loss of his privacy. Here, we survey
several facets of this study, and differential privacy plays a role in more
than one way. Of course, it provides us a basis for modeling agent costs for
privacy, which is essential if we are to attempt mechanism design in a setting
in which agents have preferences for privacy. It also provides a toolkit for
controlling those costs. However, perhaps more surprisingly, it provides a
powerful toolkit for controlling the stability of mechanisms in general, which
yields a set of tools for designing novel mechanisms even in economic settings
completely unrelated to privacy.
