🤝In AI We Trust: Data Poisoning, Misinformation, and Secure Agents

The Story

Welcome to the Madrid ML Meetup! 🤗 If you're concerned about AI's fine print, this talk is for you. We'll begin with **adversarial machine learning** and **data poisoning**: how the data a model learns from can be used to manipulate it. Then we'll examine the factuality of LLM responses: why they can be convincing and false at the same time, even without an attack, and how to assess them. Finally, we'll move from answers to actions: what happens when agents rely on harnesses, skills, and tools to act on our behalf, and what permissions, boundaries, and controls we should put in place.🤝 Our speaker, [Javier Carnerero Cano](https://www.linkedin.com/in/ccano-javi/), is a Research Scientist at IBM Research and an Academic Visitor at Imperial College London. He holds a PhD in AI security from Imperial College London. His current work focuses on LLM factuality, data-source trust, data poisoning, misinformation, safeguards, and agentic-skills security, including collaboration with NASA on evaluating and correcting AI-generated scientific content. The event is organized by **Machine Learning Circle**, **Universidad Politécnica de Madrid**, **Universidad Rey Juan Carlos**, and **ARQUIMEA Research Center**, in collaboration with the **Madrid City Council**. 🏦

Get There

Similar Events