Practical approaches to big data privacy over time

Micah Altman, Alexandra Wood, David R O’Brien and Urs Gasser in International Data Privacy Law: “

  • Governments and businesses are increasingly collecting, analysing, and sharing detailed information about individuals over long periods of time.
  • Vast quantities of data from new sources and novel methods for large-scale data analysis promise to yield deeper understanding of human characteristics, behaviour, and relationships and advance the state of science, public policy, and innovation.
  • The collection and use of fine-grained personal data over time, at the same time, is associated with significant risks to individuals, groups, and society at large.
  • This article examines a range of long-term research studies in order to identify the characteristics that drive their unique sets of risks and benefits and the practices established to protect research data subjects from long-term privacy risks.
  • We find that many big data activities in government and industry settings have characteristics and risks similar to those of long-term research studies, but are subject to less oversight and control.
  • We argue that the risks posed by big data over time can best be understood as a function of temporal factors comprising age, period, and frequency and non-temporal factors such as population diversity, sample size, dimensionality, and intended analytic use.
  • Increasing complexity in any of these factors, individually or in combination, creates heightened risks that are not readily addressable through traditional de-identification and process controls.
  • We provide practical recommendations for big data privacy controls based on the risk factors present in a specific case and informed by recent insights from the state of the art and practice….(More)”.