In contrast to twentieth century preventative security logics (collect, analyse, decide), pre-emptive security decisions on so-called ‘low probability, high impact’ events accept the necessity of acting and deciding even where there is residual doubt or incomplete evidence. This matters because conventional preventative measures have been widely criticized in post terrorism event reports, largely on the grounds that they failed to enact a decision where information was incomplete or dispersed (e.g. 9/11 Commission Report 2004; July 7 Inquests 2011).
In response to the failure to act on the basis of incomplete fragments of information, the phrase “actionable intelligence” has become commonplace – with the UK Borders Agency reporting, for example, that their systems must be “good enough to get the information to the front line, to take a decision”. Similarly, following the restructuring of national intelligence in the US, the Director of National Intelligence testified to Senate that “meaningful decisions require us to develop imaginative programs to take full advantage of partial fragmentary information” (US Senate Committee 2011). Yet, despite the growing importance of actionable decisions to security and counter-terror, there remains much work to be done on the changing nature of ‘back room analysis’ and ‘front line decision’ and its effects. To what extent do decisions within the formulation of analytics and automated systems create the parameters for all future ‘front line’ judgement?