law and Technology
Perception, law, and Policy
InforMatIon a Wareness offICe seal Courtesy of the Defense aDVanCeD researCh proJeCts agenCy
The U.S. gOVerNMeNT receives more than 100 million tax returns each year. 3 Based on previous behavioral pat- terns, computers select the
very few tax returns that are subjected
to the much-feared auditing process.
Similarly, millions of packages and individuals cross international borders.
Governments are considering the use
of computerized algorithms for the
selection of parcels and people for
additional scrutiny. In addition, governments are considering automated
prediction for a wide range of various
tasks, from insider trading detection
to fighting and preventing violent
crimes. Generally, governments consider automated predictions when
personal information about individuals is available. They are further motivated to take such action when the
antisocial activities they strive to block
are difficult and costly to detect.
Automated prediction is also generating interest in the context of detecting and preventing terrorist activities.
Here, an additional factor enters the
equation: the devastating effects of
successful attacks in terms of human
casualties. These effects, at times, lead
to rash policy decisions, as well as radical changes in public opinion. Some
academics and policymakers are well
aware of these dynamics, and call for
exercising great caution when examining the role of new and possibly invasive policy measures in this context.
They are right to do so. However, in
some cases, automated prediction is
official seal of the decommissioned u.S. information awareness office, which funded
research and development of the canceled total information awareness initiative.
indeed an appropriate measure, given
its hidden benefits.
Automated prediction is perceived
as problematic and even frightening by
a large percentage of the general pub-
lic. This common visceral response is
not always rational and accurate, yet it
is backed by several relevant legal con-
cepts. Automated prediction deserves a
closer look, as it might promote impor-
tant social objectives, such as equality
and fairness. Reexamining automated
prediction should lead to a broader
role for these practices in modern gov-
ernment. Legal impediments blocking
some of these practices should be re-
thought and perhaps removed, even in
view of the negative perception by the