AI Governance Fails without Auditability
Experts in #cybersecurity know that real security comes from end-to-end traceability of auditable artifacts. By extension, auditability requires transparency and independent verification of the systems being audited.
With the rise of #agentic_AI, many non-experts are touting the "safety" they feel with AI agents that have been given what they believe are clear instructions that will be followed by the agents. Without fear-mongering, be aware that #AI_governance fails without auditability because:
- Many frontier-class agents are aligned to the SaaS providers, not to you.
- None of the frontiers model providers offer real traceability, transparency, or data provenance to end users (meaning you).
- You're trusting the agent to do what you've told it, or not to do something you've prohibited, but you can't actually audit an agentic system you don't fully control or verify what it's doing under the hood.
Agentic AI can be useful, but always remember Quis custodiet ipsos custodes? applies. Think about how systems fail, then ask yourself "Who guards the guards?" within your AI implementation. Once you do that, it's painfully self-evident that expecting any #AI_agent or #AI_model to audit itself is a #data_breach waiting to happen.
The solution you implement is fundamentally less important than asking the right questions in the first place. Asking those types of questions is still a human job, and will remain so for a long time to come.
