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fear of terrorist attacks. Various technological tools are used or considered as
means to meet such challenges and curb these risks. Of the tools discussed in the
political and legal sphere, data mining applications for the analysis of personal
information have probably generated the greatest interest. The discovery of
distinct behavior patterns linking several of the 9/11 terrorists to each other and
other known operatives (Taipale, 2004) has led many to ask: What if data mining
had been applied in advance? Could the attacks and their devastating outcomes
been avoided?
Data mining has captured the imagination as a tool which could potentially
close the intelligence gap constantly deepening between governments and their
new targets - terrorists and sophisticated criminals. Data mining is also generating
interest in other governmental contexts, such as law enforcement and policing. In
recent years, law enforcement worldwide has shifted to “Intelligence Led
Policing” (ILP) (Cate, 2008). Rather than merely reacting to events and
investigating them, law enforcement is trying to preempt crime. It does so by
gathering intelligence, which includes personal information, closely analyzing it,
and allocating police resources accordingly - all tasks which data mining could
enhance. It should therefore come as no surprise that, at least in the United States,
data mining initiatives are popping up throughout the regulatory framework
(GAO, 2004).
The visceral feeling of many is that the outcome of data mining analyses, which
enable the government to differentiate among individuals and groups in novel
ways, is extremely problematic. Yet framing the notions behind this strong
visceral response in the form of legal theory is a difficult task. Even though
governmental data mining is extensively discussed in recent literature, an overall
sense of confusion is ever present. Additional thought is still required to properly
articulate the concerns these practices generate, and the context in which they
arise. While mapping out these issues, scholars as well as policymakers must
further establish which paradigms of legal thought are suitable for addressing
these matters. Central potential paradigms are constitutional law, privacy law and
anti-discrimination, yet other fields will surely prove relevant.
This chapter strives to advance the theoretical discussion regarding the
understanding of the problems data mining practices generate. It does so within
the confines of privacy law and interests, which many sense are utterly
compromised by the governmental data mining practices. Within this broader
theoretical realm, the chapter focuses on examining the relevance of a related legal
paradigm in privacy law - that of governmental searches. Examining whether an
intrusive act is a legal or illegal search is a common analytical query invoked
when approaching various governmental actions which might compromise privacy
interests. It is analytically helpful - this chapter will explain - to conceptualize the
privacy harms data mining might cause by using paradigms of thought arising in
"search" related analyses. To some extent and from some perspectives, data
mining compromises the same interests affected by illegal governmental searches.
Yet it does so in a unique and novel way. This uniqueness renders the discussion
of data mining and its detriments difficult and complex. This chapter introduces
three analytical paths for extending the well accepted notion of illegal searches
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