For safety issues, the main focus of red teaming engagements is to stop AI systems from generating undesired outputs. This could include blocking instructions on bomb making or displaying potentially disturbing or prohibited images. The goal here is to find potential unintended results or responses in large language models (LLMs) and ensure developers are mindful of how guardrails must be adjusted to reduce the chances of abuse for the model.
On the flip side, red teaming for AI security is meant to identify flaws and security vulnerabilities that could allow threat actors to exploit the AI system and compromise the integrity, confidentiality, or availability of an AI-powered application or system. It ensures AI deployments do not result in giving an attacker a foothold in the organization’s system.
Working with the security researcher community for AI red teaming
To enhance their red teaming efforts, companies should engage the community of AI security researchers. A group of highly skilled security and AI safety experts, they are professionals at finding weaknesses within computer systems and AI models. Employing them ensures the most diverse talent and skills are being harnessed to test an organization’s AI. These individuals provide organizations with a fresh, independent perspective on the evolving safety and security challenges faced in AI deployments.