Looks Good to Me: Catching the AI Data Errors Nobody Questions

**Free Event \| Thursday\, October 29 \| 2–3:30 p\.m\. CT**

AI is awesome at handing over good-looking results. When it goes off

the rails, you notice. But when the results look perfect, that's when

you should worry.

[Benjamin Schatz](https://www.linkedin.com/in/benjaminschatz), Director of Data & Analytics at Craig Frames, builds

data platforms that put the entire warehouse in executives' hands,

and they run their own requests without going through him. So how

does he know the AI isn't just telling them what they want to hear?

Ben will break down why AI gets it wrong no matter how many times you

tell it to "make no mistakes," and the checks he uses to catch it:

adversarial agents, provenance tracking, request auditing, and user

prompt training.

Let's talk about what you're running into and how to keep it from causing

problems.

Add to Outlook Calendar:

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Add to Google Calendar:

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