The short 'Death to the Privacy Calculus?' by Bart P. Knijnenburg,
Elaine M. Raybourn,
David Cherry,
Daricia Wilkinson,
Saadhika Sivakumar and
Henry Sloan
comments
The “privacy calculus” has been used extensively to describe how people make privacy-related decisions. At the same time, many researchers have found that such decisions are often anything but calculated. More recently, the privacy calculus has been used in service of machine learning approaches to privacy. This position paper discusses the practical and ethical questions that arise from this use of the privacy calculus. ...
Laufer and Wolfe coined the term “calculus of
behavior” to refer to the cognitive process that under-
lies people’s disclosure decisions.
Many researchers
have since used the term “privacy calculus” to
describe
privacy-related decision behaviors,
and it has become a well-established concept in privacy
research.
Other
researchers, however,
have
demonstrated that people rarely take a truly calculative
approach to privacy decision making, and
are often
prone to take mental shortcuts instead.
We
discuss these departures from rationality, how they
come about, and the impact they have on the presumed
normative
justifications for existing
privacy solutions.
This will lead us to a relatively new type of privacy solution,
user-tailored privacy, which
addresses
some of the
ethical
questions raised by
existing solutions.
User-tailored privacy
uses the privacy calculus
prescriptively, with the
risk/benefit
tradeoff serving as
an objective
function for machine learning
algorithms.
We
will argue that this use of the privacy
calculus
raises
its
own set of
practical and ethical questions
that
may cause
ethical
dilemmas.
In outlining
these questions, we
hope to spark a discussion
of
the
ethical concerns regarding user-tailored privacy
