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Data Profiling: Understanding 'Where You Go' and 'What You Do' to Define 'Who You Are'

Explore the concept of profiling, its origins, impact on decision-making, ethical concerns, and the role of technology in surveillance and data analysis. Learn about the basis of decisions made using individual and mass data, the effectiveness and ethical problems associated with profiling, and the implications of EU data protection laws. Discover the evolving landscape of profiling in the age of Web 2.0, self-generated profiles, and the democratization of information.

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Data Profiling: Understanding 'Where You Go' and 'What You Do' to Define 'Who You Are'

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  1. Data ProfilingDo "Where You Go" and "What You Do" Become "Who You Are"?” Ralf Bendrath University of Bremen

  2. Wikipedia • Profiling, the extrapolation of information about something, based on known qualities, may refer specifically to: • Stereotypes • Offender profiling • Racial profiling • Gender bias • Cultural bias • Performance analysis in (software engineering)

  3. Bruce Schneier • To profile is to generalize. It’s taking characteristics of a population and applying them to an individual.

  4. Roger Clarke • Profiling is (…) a means of generating suspects or prospects from within a large population, and involves inferring a set of characteristics of a particular class of person from past experience, then searching data-holdings for individuals with a close fit to that set of characteristics.

  5. General Idea • Model of population classes • Information about individual • Sorting individual into a class • Acting on these classes

  6. Origins of Profiling • Middle Ages: Inquisition • 1800: criminal profiling • 1900: early biometrics • today: forensic psychology • requires intense manpower

  7. Technologies of Surveillance Observing Recording Distributing Deciding

  8. Surveillance as Decisions • „Dataveillance“ (Clarke) • „Social sorting“ (Gandy) • „Digital discrimination“ (Lyon)

  9. Basis of Decisions: Individual Data • Income • Shopping history • Search records • Movements • Relationships • …

  10. Basis of Decisions: Mass Data • Data from large populations • Correlation analysis • Modelling

  11. Data  Profiles / Models • „urban hipster“ • „rural conservative“ • „silver surfer“ • „chronic complainer“ • „credit risk“ • „terrorist suspect“

  12. Effectiveness Problems • Individual data basis • wrong information? • Modelling error • millions of Amazon buyers • too few known terrorists! • Probabilistic error • profile ≠ individual • false positives / false negatives

  13. Ethical Problems • Treating humans as objects, as data sets • Decisions by machines that affect real humans • Discrimination reified in machinery

  14. EU Data Protection Directive 1995 Article 15: Automated individual decisions „Member states shall grant the right to every person to not be subject to a decision which (…) is solely based on automatic processing of data intended to evaluate certain personal aspects relating to him (…).“

  15. Web 2.0 Issues • self-generated profiles • gossip and chatter about others • public  democratization of profiling? • future of reputation (Solove) • lots of data, but not standardized • semantic web?

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