Outside of the engineering community, the term ‘AI Model’ is often treated as if it has only one meaning. In regulations, it can be interpreted either narrowly or broadly. Blogs, articles, and news frequently described it either in vague or anthropomorphic terms. While these high-level explanations are helpful for introducing basic ideas to a wide audience, they become less useful when we need to apply them to real-world projects. At that point, the lack of terminological precision makes it difficult to clearly understand how AI models actually operate and how they relate to key concepts like personal data and intelligence.
Of course, we can't solve these complex issues in a short webinar. However, Albert will offer an engineering-focused perspective on some of the main issues around personal data in AI models. The aim of this webinar is to give a practical reference point for audience without detailed technical background, who nonetheless may need to provide guidance to management or make decisions in this area.
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