Classification
Data Protection and Privacy Compliance
Overview
Article 35 of the EU General Data Protection Regulation (GDPR) mandates that organizations conduct a Data Protection Impact Assessment (DPIA) when processing data that is likely to result in a high risk to the rights and freedoms of natural persons. DPIAs are systematic processes designed to identify, evaluate, and mitigate privacy risks associated with data processing activities, particularly those involving new technologies such as AI. The requirement applies to processing operations that involve large-scale use of sensitive data, systematic monitoring, or profiling. While DPIAs are powerful tools for risk management and accountability, a limitation is that the assessment's quality and effectiveness depend heavily on organizational expertise and resources. There is also some ambiguity in determining what constitutes "high risk," which can lead to inconsistent application across sectors and jurisdictions.
Governance Context
Article 35 is embedded within the GDPR and is directly enforceable in all EU member states. It obliges controllers to carry out a DPIA before initiating processing likely to result in high risk, such as large-scale processing of special categories of data or systematic monitoring of public areas. Obligations include: (1) documenting the nature, scope, context, and purposes of processing; (2) assessing necessity and proportionality of the processing; (3) identifying and evaluating risks to data subjects' rights and freedoms; and (4) specifying measures to address and mitigate those risks. Organizations must also consult with supervisory authorities, such as the ICO in the UK, if residual risks remain after mitigation. Both the French CNIL and German BfDI provide sector-specific DPIA lists and templates, illustrating the need for tailored approaches. Failure to comply can result in significant administrative fines under Article 83 of the GDPR.
Ethical & Societal Implications
DPIAs play a critical role in safeguarding individual rights by proactively identifying and mitigating privacy risks, especially in high-impact AI applications. They foster transparency, accountability, and trust in data processing activities. However, if DPIAs are treated as mere formalities or are inadequately conducted, significant ethical risks remain-such as discrimination, loss of autonomy, or unauthorized surveillance. Societal implications include the potential chilling effect on innovation if requirements are misunderstood or inconsistently enforced, as well as the risk of undermining public confidence in digital services.
Key Takeaways
Article 35 requires DPIAs for processing likely to pose high privacy risks.; DPIAs are essential for identifying, assessing, and mitigating risks in AI systems.; Supervisory authorities provide guidance but expect organizations to justify DPIA decisions.; Failure to conduct a DPIA where required can result in significant regulatory penalties.; Effective DPIAs require expertise, cross-functional collaboration, and ongoing review.; Ambiguity in 'high risk' definitions can lead to inconsistent compliance.