Navigating the Risks of Building Generative AI Services
This ML Conference Whitepaper explores the critical risks of deploying Generative AI services and provides key strategies for securing AI-driven systems. Authored by industry expert Jeff Watkins, this whitepaper introduces the STOIC framework—highlighting threats like data theft, adversarial attacks, and model poisoning. With real-world case studies and actionable countermeasures, this guide is essential for businesses looking to innovate with AI while safeguarding their assets.
Table of Contents
- Introduction – Overview of Generative AI risks
- Building Secure AI – Opportunities & security challenges
- STOIC Threats – Stolen, Tricked, Obstructed, Infected, Compromised
- Protecting AI Services – Security strategies & best practices
- Governance & Compliance – Ethical AI & regulatory considerations
- Threat Modeling & Testing – Identifying vulnerabilities & securing AI
- Conclusion – Key takeaways for safe AI implementation
- References – Further reading & resources
