Privacy-breaking pattern analysis isn't new - but AI has just made it accessible to everyone. Tools that were once complex, specialized, and limited to well-resourced actors are now available to anyone with access to large language models. Your carefully crafted privacy protections, designed to withstand traditional analysis, are about to face a wave of AI-powered pattern recognition that puts sophisticated privacy-breaking capabilities into everyone's hands.

Through live demonstrations, you'll watch as simple AI tools reconstruct user identities from "anonymous" chat data, rebuild social networks from encrypted messages, and expose organizational structures from metadata we thought was safe. What once required deep expertise in statistical analysis can now be done with a few prompts to an LLM.

We'll explore how traditional privacy approaches fail against these democratized threats, and examine modern defenses like differential privacy and federated learning. You'll leave understanding both the scale of this new challenge and practical steps to protect your systems. Whether you're building communication tools, handling sensitive data, or protecting user privacy, this talk will show you why yesterday's privacy tools won't survive in a world where sophisticated pattern analysis is available to all.

Key Takeaways:
- How traditional privacy and anonymization tools fail against basic AI analysis
- Understanding the new ways AI can reconstruct identities and relationships
- Practical architectures and techniques for building AI-resistant privacy systems