Tell Mistakes From Manipulation Before You Respond
Understand how to differentiate between ordinary generative AI failures and deliberate manipulations before acting on AI outputs. This lesson teaches you to classify errors based on their source, assess connected workflows, and apply the right controls and escalation steps using the AI Risk Management Worksheet and NIST frameworks. You'll develop skills to ensure trustworthy AI use in sensitive environments by recognizing risks and tailoring your responses accordingly.
We'll cover the following...
The AI Risk Management Worksheet already forces a hard move when evidence no longer supports intended use. The common mistake is treating GenAI problems as one bucket called bad output, then reacting the same way every time. That mistake usually comes from fluency, because a polished paragraph feels like a single kind of thing even when the failure behind it is not. Under time pressure, teams also collapse the workflow into one step, paste text, get an answer, move on. The workflow still branches, even if nobody says so out loud.
A draft incident triage summary is sitting in a ticket, and it needs to be cleaner fast. A teammate is about to paste the summary into a GenAI assistant and ask for recommended next actions. They are also ready to shrug off any ...