AI doesn't lie - at least, not intentionally. It just sounds completely confident while filling in the gaps with whatever seems most plausible. And in a world where AI outputs are increasingly being used to inform high-stakes decisions, the ability to spot what's wrong, before it reaches a stakeholder, is becoming one of the most important skills a data professional can have.

In this episode, Derek Gibson joins Dr Genevieve Hayes to share practical strategies for identifying unreliable AI outputs and building the defences necessary to keep AI-generated misinformation from reaching your stakeholders.

In this episode, you'll discover:

1. Why AI is not a truth tool and what that means for how you use it [03:21]
2. The red flags that signal an AI output shouldn't be trusted [12:21]
3. A simple prompting habit you can develop to reduce AI mistakes [16:13]
4. Why the skill of verifying AI outputs is one you need to build yourself [24:25]

Guest Bio

Derek Gibson is a decision scientist, analytics educator, and has recently wrapped up his long career in financial services at Wells Fargo. He serves on the Wake Forest University MS Business Analytics Advisory Board. He is also a co-author of Data Duped: How to Avoid Being Hoodwinked by Misinformation and author of the upcoming Data, AI, and the Noise: Searching for Truth in Information and Algorithms.

Links

• Connect with Derek on LinkedIn
• Derek's website
• Connect with Genevieve on LinkedIn
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