Demystifying AI Risk: An Actionable Framework Aligning Business Needs to Risks and Mitigations
• Presentation
Publisher
Software Engineering Institute
Topic or Tag
Abstract
While most business leaders and data teams are excited about AI, leaders of governance / risk functions (e.g.: security, privacy, legal, ethics, etc.) are concerned about the unintended consequences (risks!) of AI. This lack of alignment is among the main reasons for the slow adoption of AI in large organizations.
To address this chasm between AI supporters and detractors, this talk will walk through an operationalizable framework to confidently manage AI risks:
- What components make up AI?
- How do the subsystems of AI work together as an AI system?
- What are the risks of using AI?
- What threats can cause each risk to be realized?
- Which controls can mitigate each risk? Which AI component do they need to be applied to?
Omar Khawaja leads Databricks' Field Security practice globally, teaches at Carnegie Mellon’s CISO program, sits on the boards of HITRUST and FAIR Institute, spent 9 years as CISO of a $26B enterprise and is leading a team that developed an actionable AI security framework for 12,000 enterprise data platform customers at Databricks.