🚨 CLICK HERE TO RSVP 👈
This year, OpenAI started letting people connect their medical records and Apple Health data to ChatGPT.
Since 2024, Americans can buy a continuous glucose monitor without a prescription.
For most of the Quantified Self movement's history, answering a question with your own data meant manual logs and spreadsheets. Today a sensor collects the data and an AI model analyzes it on demand.
That leaves every founder building in this space with one hard question: when an AI's answer changes what someone eats or takes, how do they know it's right?
Gary Wolf has spent nearly 20 years watching people try to answer questions with their own data.
He co-founded Quantified Self with Kevin Kelly, joined the WIRED editorial team in 1994, became the first executive producer of Wired Digital, and launched Wired News. His New York Times Magazine cover story on self-tracking brought the practice to a mainstream audience, and his TED talk on the subject has been watched more than a million times.
His current work is about AI and personal data. He's researching a cryptographic protocol to prove where sensor data came from at the moment it's recorded, and writing essays on how people talk to AI chatbots.
His new book, The Quantified Self: Learning to Observe, lays out a method anyone can use to test a question against their own data.
On Thursday, October 15, Gary joins Startup Grind to talk about what AI changes for people using their own data, and what that means for the founders building those products.
🚨 CLICK HERE TO RSVP 👈
WHAT YOU'LL LEARN
What AI changed for self-trackers: The analysis Quantified Self members once did by hand, and what a user can now do in one conversation with a model.
When to trust a model's answer: How to tell when an AI reading of your sleep or blood sugar holds up, and what a user needs before acting on it.
Proving where data came from: Gary's research on verifying sensor data at the moment it's recorded, and what it means