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Latest Updates on AI Safety Work at Jinesis AI Lab

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About this event

What to expect

Hear directly from leading AI safety researchers at Jinesis AI Lab in this comprehensive Toronto meetup covering the latest developments in adversarial defence, interpretability, and democratic AI governance.

Zhijing Jin will present her lab's complete research agenda, offering deep insights into current work spanning multiple critical areas of AI safety. Whether you're concerned about alignment challenges, interested in making AI systems more transparent, or exploring how to protect democratic processes from AI-driven threats, this session provides a rare opportunity to engage with cutting-edge research and ask questions directly.

This hybrid event welcomes both in-person attendees at the Industrious Office space in downtown Toronto and remote participants via livestream. The evening begins with food and networking, followed by a substantive presentation and Q&A session, concluding with open discussions where you can connect with other AI safety researchers, practitioners, and concerned citizens.

What You'll Learn

  • Current research approaches to adversarial defence against AI system manipulation
  • Latest techniques in AI interpretability and transparency
  • Emerging threats to democratic processes and proposed safeguards
  • The broader research agenda at Jinesis AI Lab
  • Practical considerations for safer AI development

Event Format

6:00-6:30 PM — Food, networking, and introductions
6:30-7:30 PM — Research presentation by Zhijing Jin with Q&A
7:30-9:00 PM — Open discussions and deeper conversations

Can't attend in person? Join the live stream on YouTube starting at 6:30 PM EDT to participate remotely.

Who Should Attend

This event suits anyone interested in AI safety — from technical researchers and ML engineers to policy professionals, ethicists, and concerned citizens. Whether you're deeply familiar with alignment research or just beginning to explore how we can ensure AI systems serve human interests, you'll find value in both the formal presentation and informal discussions.

This session is part of the recurring AI Safety Thursdays series, a weekly gathering examining fundamental questions about AI alignment, risk measurement and mitigation, and responsible development practices. The Toronto AI safety community brings together diverse perspectives on these critical challenges facing

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