Tuesday, September 1, 2026
8:30 AM – 9:00 AM | Conference Hall
PLENARY LECTURE by Jonathan Bisson
"AI: Hype(r)fiction or (R)evolution?"
Synopsis
AI is everywhere, making it hard to separate hype from reality. This pushes people to either chase every new tool or reject AI completely. But there is a better way: a discriminating approach that gets real value from these tools without falling for the excitement or the knee-jerk reaction.
In natural products research, AI can help mine literature, annotate MS/NMR data, elucidate structures, and write grants. Yet the limits are real. These models struggle with novelty, accuracy, and reproducibility, often inventing fake references or faulty mechanisms. If you know the science, AI gives you real value. If you cannot tell when it is bluffing, it just gets you to the wrong answer faster.
With abundant computing, lab automation, and natural language interfaces now accessible to individual labs, change is happening whether we want it or not. This presentation gives you practical tools to prepare yourself and your data, helping you know when to reach for a fancy new AI tool and when simple linear regression or better experimental design is actually what you need.
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