Ethics & Privacy
6 talks from the 2026 edition.
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Catch the LLM if you Can: Watermarking LLMs ▶ Recording 📝 Transcript
Subhosri Basu
With Large Language Models (LLMs), generating high-quality text and images is easy and so is misusing it. As AI-generated content becomes harder to distinguish from human generated content, developers are...
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Is digital sovereignty a new buzzword in AI development? ▶ Recording 📝 Transcript
Dr. Maria Börner
AI development usually focuses on feasibility and implementation, but a new buzzword is now being used: 'sovereignty'. While customers are excited about it, what does it mean for them and for AI developers? In this...
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Is my AI Recruiting biased? - How to evaluate these systems ▶ Recording 📝 Transcript
Sebastian Krauss
AI recruiting systems are increasingly used to filter, rank, and select applicants at scale. Yet their deployment raises essential questions: How reliable are these models in real hiring environments, and how do we...
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No, you can't 'eval' your way to fairness ▶ Recording 📝 Transcript
Laura Summers
Fairness is fundamentally not tractable to classic optimisation techniques. It's not a state of the world, it's an experience of it. No technology is fair in a vacuum - fairness can only be understood when a...
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Why Did The Model Do That? Debugging the Ghost in the Machine ▶ Recording 📝 Transcript
Cosima Meyer
Why did the model say "No"? In an era where machine learning models increasingly influence high-stake decisions, "trust me" isn't a sufficient explanation. Yet, the logic behind many model decisions remains a black...
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Your Data Is Leaking: A Hands-On Introduction to Differential Privacy with OpenDP ▶ Recording 📝 Transcript
Shlomi Hod, Marcel Neunhoeffer
Data analysis and machine learning often involve sensitive information. But how can we ensure that our analyses and releases do not inadvertently reveal information about the individuals in our data? Traditional...