  The contextual integrity model is a widely accepted way of analyzing the
plurality of norms that are colloquially called "privacy norms". Contextual
integrity systematically describes such norms by distinguishing the type of
data concerned, the three social agents involved (subject, sender, and
recipient) and the transmission principle governing the transfer of
information. It allows analyzing privacy norms in terms of their impact on the
interaction of those agents with one another.
  This paper places contextual integrity in a strict game theoretic framework.
When such description is possible it has three key advantages: Firstly, it
allows indisputable utilitarian justification of some privacy norms. Secondly,
it better relates privacy to topics which are well understood by stakeholders
whose education is predominantly quantitative, such as engineers and
economists. Thirdly, it is an absolute necessity when describing ethical
constraints to machines such as AI agents.
  In addition to describing games which capture paradigmatic informational
norms, the paper also analyzes cases in which the game, per se, does not
encourage normative behavior. The paper discusses two main forms of mechanisms
which can be applied to the game in such cases, and shows that they reflect
accepted privacy regulation and technologies.
