40 Pages Posted: 22 Dec 2013 Last revised: 15 Jan 2014
Date Written: December 11, 2013
Profiling is a highly evocative term with multiple meanings, used in both specialist and non-specialist contexts. Drawing attention to the innovative feature of profiling as a form of non-representational, probabilistic knowledge, this paper focuses on machine profiling. It aims to elaborate a suitable definition that captures the main features of this new form of generating and applying knowledge.
The paper is divided in four parts. Part one explores the distinctive elements of profiling. It discusses some existing concepts and distinctions (such as the meaning of organic, human and machine profiling; non-automated and autonomic profiling; group and individual profiling; direct and indirect profiling) and it provides basic information on Knowledge Discovery in Databases and data mining, as key enablers of profiling. It also presents the most relevant sources of profiling, such as behavioural, biometric and location data.
Part two discusses the EU legal framework, including the present discussions on the proposed data protection Regulation and Directive, together with relevant recommendations of the Council of Europe to highlight how profiling is defined and conceptualised in the fields of data protection and antidiscrimination. Part three gives an overview of different domains of application, including the security, law enforcement and counter-terrorism domain, the financial sector, healthcare, employment, marketing, and social media. In the final part, the paper develops a definition of profiling. Building on the work of Mireille Hildebrandt, and taking into account insights from the conceptualisation of profiling in other academic literature, law and policy, and from the application areas, the following definitions are proposed of profiling and related concepts.
Profiling is a technique to automatically process personal and non-personal data, aimed at developing predictive knowledge from the data in the form of constructing profiles that can subsequently be applied as a basis for decision-making.
A profile is a set of correlated data that represents a (human or non-human, individual or group) subject. Constructing profiles is the process of discovering unexpected patterns between data in large data sets that can be used to create profiles. Applying profiles is the process of identifying and representing a specific subject or to identify a subject as a member of a specific group or category and taking some form of decision based on this identification and representation.
Keywords: definition, profiling, data mining, EU legal framework, domains of application
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