Fairness and Data Protection Impact Assessments

Atoosa Kasirzadeh, Damian Clifford

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

In this paper, we critically examine the effectiveness of the requirement to conduct a Data Protection Impact Assessment (DPIA) in Article 35 of the General Data Protection Regulation (GDPR) in light of fairness metrics. Through this analysis, we explore the role of the fairness principle as introduced in Article 5(1)(a) and its multifaceted interpretation in the obligation to conduct a DPIA. Our paper argues that although there is a significant theoretical role for the considerations of fairness in the DPIA process, an analysis of the various guidance documents issued by data protection authorities on the obligation to conduct a DPIA reveals that they rarely mention the fairness principle in practice. Our analysis questions this omission, and assesses the capacity of fairness metrics to be truly operationalized within DPIAs. We conclude by exploring the practical effectiveness of DPIA with particular reference to (1) technical challenges that have an impact on the usefulness of DPIAs irrespective of a controller's willingness to actively engage in the process, (2) the context dependent nature of the fairness principle, and (3) the key role played by data controllers in the determination of what is fair.
Original languageEnglish
Title of host publicationAEIS '21
Subtitle of host publicationProceedings of the 2021 AAAI/ACM Conference on AI, Ethics and Society
PublisherAssociation for Computing Machinery (ACM)
ISBN (Electronic)9781450384735
Publication statusPublished - Jul 2021
Event2021 AAAI/ACM Conference on AI, Ethics, and Society - Virtual event USA
Duration: 19 May 202121 May 2021

Publication series

NameProceedings of the AAI/ACM Conference on AI, Ethics, and Society
PublisherAssociation for Computing Machinery (ACM)


Conference2021 AAAI/ACM Conference on AI, Ethics, and Society
Abbreviated titleAEIS '21

Keywords / Materials (for Non-textual outputs)

  • ethics of artificial intelligence
  • regulation of artificial intelligence
  • fairness principle
  • algorithmic fairness
  • general data protection regulation
  • data protection impact assessments


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