Epic AI Fails

Free Mini Conference and L&D Happy Hour
in Chicago

Thursday, October 1st

3:30 – 7:30 p.m. CDT

Clark Street Ale House

742 N Clark St, Chicago IL, 60654

Before you invest more time in AI, learn from true stories about what doesn’t work.

Join us October 1 as L&D professionals discuss AI approaches that went sideways, and the practical lessons you can take from their sometimes-painful experiences. Bring your own stories to share and connect with peers during a free happy hour!

No selling and no cost! Just learning and connection (plus drinks and snacks) with L&D peers.

These engaging speakers will each share a 20- to 30-minute session:

Chad Udell of SparkLearn

Technically Correct and Completely Useless: What Frontline AI Failures Actually Teach Us

Emily Hoffmann of Fredrickson Learning

The Illusion of Progress: What AI at Work Gets Backward

Shylee Garrett of Meta

Before You Feed the AI: What L&D Needs to Know About Knowledge Quality

Read on below to learn more about the sessions.

Technically Correct and Completely Useless: What Frontline AI Features Actually Teach Us

Chad Udell – CEO, SparkLearn

Most AI failures in frontline learning don’t look like failures. Nothing blows up and the output reads just fine. The SOP summary is “accurate.” The generated micro-course is well structured but just a little “off”. The chatbot answers the question confidently, but just wrong enough to erode trust.

I’ve spent the last couple of years watching organizations bolt AI onto messy content, shared tablets, spotty connectivity, and governance nobody wrote down, then act surprised when it goes sideways.

AI is a layer, not a foundation, and it will happily remix your chaos at scale. You’ll leave with a short checklist of the questions to ask before your next AI pilot, so your fail story stays a lot less epic than mine.

The Illusion of Progress: What AI at Work Gets Backward

Emily Hoffmann – Fredrickson Learning

Human factors research in aviation and medicine has explored what happened when automation took over parts of expert work: pilots losing manual skills they still needed, surgical residents who stopped getting hands-on practice, clinicians following a wrong recommendation because it came from the system. Much of it maps onto questions L&D is asking now. How does someone become a senior designer if AI does the junior work? What is left of the job? How would we know if AI is making our decisions worse? This talk goes through the epic fails those fields already had, what they learned from them, and whether the comparison to our situation holds