How do AI conformity assessments differ from DPIAs?

AI conformity assessments differ from Data Protection Impact Assessments (DPIAs) primarily in their broader scope. While DPIAs are specifically concerned with assessing the risks associated with data processing activities to ensure compliance with data protection regulations, AI conformity assessments encompass a wider array of considerations. These assessments evaluate compliance with various regulatory standards relating to AI technologies, which may include ethical considerations, safety, transparency, accountability, and performance, in addition to data privacy.

The breadth of AI conformity assessments reflects the recognition that AI systems can pose a wide range of potential risks, not just those related to privacy. This comprehensive approach helps to ensure that AI technologies are developed and deployed responsibly, taking into account the diverse impacts they may have on society, individuals, and the environment. This contrasts with the narrower focus of DPIAs, which center on how personal data is handled and protected.

Other options, such as focusing solely on data privacy, being limited to product safety, or being restricted to governmental use, do not accurately capture the comprehensive nature of AI conformity assessments. These options incorrectly suggest that AI conformity assessments have limitations that they do not possess, thus reinforcing the understanding of their broader applicability in the regulatory landscape concerning AI technologies.