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Do you ever feel the weight of responsibility for harnessing the power of AI security tools while ensuring they don’t become vulnerabilities themselves? We’re supposed to make things better, not worse, right?

Ask Yourself: What is my vision for how and where Functional AI can be designed, managed, deployed, and controlled so that risks and vulnerabilities are significantly lowered for my organization, and can even be quantified to show the improvements?

Before Starting:

To help get ready to get ready:

Intention: Draft your goals to empower my team to effectively supervise AI security agents, maximizing their potential while mitigating risks.
Preparation: Gather data on current security practices and potential AI integration points. Hint: You can have a generative AI model do this initial research for you in less than 1 minute.
Collaboration: Engage key stakeholders across IT and security to develop a clear strategy. If internal stakeholders are “stuck” then connect with your colleagues on social media to get a fresh take on things.

Starting:

Define success: Clearly outline how we will measure the effectiveness of AI agent supervision. Success Criteria helps everyone!
Transparency: Establish a framework for transparent and explainable AI decision-making. (Let’s avoid the indecision maze or the wild west approach, right?)
Human oversight: Prioritize human oversight and intervention as a safeguard against unexpected AI behaviors. Consider a lunch and learn or a free form discussion on AI and Automation Supervision. (Yes, they must be supervised; they’re not magic.)

Strategies:

Leverage industry best practices and frameworks like NIST SP 800–161 [See 1 below].
Invest in training for your team on AI bias and responsible AI development [See 2 below].
Continuously monitor and audit AI agent performance and results [See 3 below]. It’s not too early to draft your ideas on paper for Responsible and Ethical AI practices (invite the legal team to the fun as well).

Warnings:

Overreliance on AI can lead to blind spots. Maintain human expertise. Avoid the “switch it on and see what happens” approach.
Unchecked bias in AI algorithms can exacerbate existing security vulnerabilities. Avoid the “write a check and forget about it” sentiment in management; champion a responsible culture.
Inadequate training and oversight can lead to unintended consequences. Even if you outsource much of the work, negotiate thorough documentation as leave behinds so that your internal teams and managers can manage it.

Continue the Conversation:

Leading AI agent supervision for Security Leaders requires a proactive approach. Let’s discuss how to navigate this evolving landscape. What challenges have you faced? Share your experiences in the comments below!

I’d love to connect on LinkedIn: https://www.linkedin.com/in/joshua-j-durkin/