Keynote: It AI-n't What You Think!
summary
Argues AI often hallucinates—calling factual profiles wrong—and labels that behavior alternative information, not truth; shows a chatbot-caused Air Canada refund lawsuit from 2022 as a real-world consequence. Demonstrates AI as an effective code investigator (it finds 15 issues in a sample where only 5% of programmers spot problems) but warns generated solutions can be overcomplicated, commented-over, or fragile; compares adoption timelines to 25 years between horses and cars.
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chapters (14)
- 0:00Keynote introduction
- 1:51AI fascination vs skepticism
- 4:41Clarke’s laws on tech
- 7:53AI revolutionary or evolutionary
- 11:49AI’s slow evolution history
- 17:52AI trust and information issues
- 23:37AI coding strengths weaknesses
- 31:00AI for ideas not solutions
- 41:25Accountability in AI solutions
- 48:30AI black swan predictions
- 51:45Building trust in AI
- 53:51Adapting to change
- 57:28Problem solver not coder
- 1:00:05Q&A
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