Is Your AI Deployment Risky? How to Address AI Safety, Security, and Reliability Risks

Summary: The video discusses a webinar that focuses on AI deployment risks, specifically addressing AI safety, security, and reliability risks. Presenters from Haz Labs and HackerOne emphasize the importance of understanding and managing these risks in the context of AI systems. They explain the roles of safety, security, and reliability in AI risk management, and highlight the need for collaboration across different teams and ongoing testing to ensure robust AI deployments.

Keypoints:

• The session is recorded and the recording will be available on the website and YouTube channel.
• Participants are encouraged to submit their questions using the Q&A box or Zoom chat.
• Key themes include framing AI risk, operationalizing AI risk management, and exploring the roles of Haz Labs and HackerOne.
• AI risks encompass reliability, safety, and security, requiring an understanding of how these dimensions interact.
• A large percentage of organizations are deploying generative AI, yet only a fraction are embedding risk assessments in design.
• Operationalizing AI risk management involves creating a code of conduct that defines expected behaviors for AI systems.
• Threat modeling is essential to identify vulnerabilities and entry points to defend against potential attacks on AI systems.
• An AI risk council can help oversee risk management across diverse teams including security, product, R&D, and legal departments.
• The collaboration between human testers and AI tools enhances the effectiveness of red teaming and vulnerability assessments.
• Finally, establishing a continuous monitoring and feedback loop is crucial for maintaining the robustness of AI systems throughout their lifecycle.