AI and security experts debate the complex relationship between open source and AI, weighing the foundational role of open source in innovation against the significant security challenges of both proprietary and open models, and exploring the difference between 'secure' and 'securable' systems.
Experts Jeff Crume and Josh Spurgin explore the critical security and governance challenges posed by autonomous AI agents. They detail common threats like prompt injection, data poisoning, and model theft, and discuss governance issues such as bias, transparency, and accountability, providing a set of actionable safeguards to build secure, trustworthy, and compliant AI systems.
Tech leader and investor Michelle Yi discusses the critical technical aspects of building trustworthy AI systems. She delves into adversarial attack and defense mechanisms, including red teaming, data poisoning, prompt stealing, and "slop squatting," and explores how advanced concepts like Constitutional AI and World Models can create safer, more reliable AI.