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