No Hacks with Slobodan Manic

Slobodan "Sani" Manić

234: OpenAI's Dots Are Cute. What They Do With Your Data Is Not.

OCT 2, 202614 MIN

Description

OpenAI's new agents, dots, are fuzzy balls with eyes that you name and dress. They also sign into websites with your saved passwords and read the email you connect. I went through OpenAI's pages to see what the face is covering. What a dot reads can train the model unless you find the switch, and websites are told nothing. I would not give one my logins or my card. Chapters 00:00 Sam Altman's pitch, and what a dot is 01:42 Do you need one? 02:36 Where the face came from 04:33 Launch day, and why now 07:05 Under the costume: your data 08:37 A model that looks for another way 10:06 What the cute is for 11:09 What websites are told 12:39 Through the web, or over it 14:01 The verdict Key Takeaways The face is how it gets sold. OpenAI had characters on the side in April. Meta made the character the product, and three weeks later OpenAI did too. What a dot reads can train the model by default. The setting is "Improve the model for everyone", and it covers the apps you connect, email included. OpenAI publishes no way for a website to recognise a dot. Its instructions tell the user to try their computer when a website blocks one. What to Do In ChatGPT, open Settings, then Data controls, and uncheck "Improve the model for everyone". Before you give any agent your logins or a card, ask what it does that you needed. If you run a website, send it to me at nohacks.co/ai-accuracy. I'll put one question your customers ask to the AI assistants and send you what they said. It's free. The newsletter is at nohacks.co/subscribe. Sources & Links From OpenAI Introducing dots Dots privacy FAQ Dots, computers and apps OpenAI's crawlers GPT-6 Astra test results Mentioned in the episode Thomas Germain, BBC, on Meta's Muse The Tech Report, with Ed Zitron Better Offline FTC on Joe Camel, 1997 No Hacks runs no sponsorships and is funded by advisory and audit work.  If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit