{"id":16909,"date":"2025-03-18T11:56:38","date_gmt":"2025-03-18T10:56:38","guid":{"rendered":"https:\/\/www.dp-institute.eu\/?p=16909"},"modified":"2025-03-18T12:16:33","modified_gmt":"2025-03-18T11:16:33","slug":"ai-voor-dpos-extra-module","status":"publish","type":"post","link":"https:\/\/www.dp-institute.eu\/en\/ai-voor-dpos-extra-module\/","title":{"rendered":"AI for DPOs: Extra Module!"},"content":{"rendered":"

The link between AI and data protection continues to evolve. That\u2019s why DPI has expanded the AI for DPOs<\/strong><\/a> training with an extra module that brings practical insights even closer. As it becomes increasingly clear that data protection plays a role in AI projects from start to finish, we go beyond theory to explore how you, as a DPO<\/strong>, can make a difference.<\/p>\n

We begin with a synthesis of the previous modules and apply it to generative AI<\/strong>. Do language models contain personal data? How do regulators assess this? We will analyze various publications from authorities, including the opinion of the EDPB<\/strong>, which was published at the request of the Irish authority.<\/p>\n

Next, we take a close look at the AI project lifecycle<\/strong>. Where and when should a DPO<\/strong> be involved, and what specific aspects should you assess? We base our approach on the NIST Risk Management Framework<\/strong>, which builds on OECD methodology<\/strong>. From the initial planning of an AI system and data collection to deployment and monitoring<\/strong>\u2014what risks should you identify, and what guidelines already exist? Topics covered in this context include:<\/p>\n