Transparency in Data Mining: From Theory to Practice - Discrimination and Privacy in the Information Society - page 291

assume that the lack of transparency in these projects contributed to this negative
response. This project was famously halted by the U.S. Congress. However, the
development of similar projects continues, under other names and acronyms
(Cate, 2008). Beyond TIA, more limited ventures using similar techniques were
set in place. The most famous and salient examples pertain to airports and
international travel.
At US airports, the DHS is currently using (and further developing) data mining
technology to secure the exit and entry of individuals to and from the country. The
recent DHS Data Mining Reports address the development of the ATS-P
(Automated Target System-Persons) module. The reports explain how various
governmental databases (also those which include personal information) are
analyzed to generate predictions for achieving these objectives. 5 In other words,
personal information within these datasets will be analyzed and used in assessing
future risks of specific individuals. DHS has even more ambitious plans in store. It
is currently testing new systems which will rely on predictions premised on
biological and behavioral information. Such information would be collected in
“neutral settings” to establish a baseline, and thereafter at other crucial settings
such as airports and sporting events. It should be noted that these systems might
not require the collection of personally identifiable information, and thus generate
a different set and form of privacy concerns (EPIC, 2011; McCullagh, 2011).
The predictions, which are premised upon data mining analyses, have real
world implications. They lead to the fact that some travelers will be engaged with
greater security examinations, while others breeze across borders. In most cases,
this would result in inconveniencing some individuals for a few minutes, or even
seconds. In the rarest of occasions (that are often publicized) it might lead to
denial of travel or even incarceration.
17.2.2 Prediction and Data Mining: Technology, Human
Discretion and Policy Decisions
The data mining of personal information includes several crucial elements - of
technology , human discretion and policy . The key technological elements
which can enable this process on the one hand, and generate the most difficult
normative concerns on the other are data mining tools and protocols. For this
discussion, I revert to a somewhat technical definition of data mining; the
“nontrivial process of identifying valid, novel, potentially useful and ultimately
understandable patterns in data” (Fayyad et al., 1996) 6 (yet as I will explain, the
final segment of this definition is probably open for debate). This chapter focuses
on “pattern based” searches (also referred to as “event-based” data mining) (Cate
5 The DHS P RIVACY O FFICE , 2010 D ATA M INING R EPORT (December 2010), noted that data
mining is not yet used, but might subsequently be applied for this objective (at 19).
6 A somewhat different definition from a Congressional report is: “the use of sophisticated
data analysis tools to discover previously unknown, valid patterns and relationships in
large data sets.” (CRS Report).