Everyone talks about model training when it comes to AI privacy. “Just turn off the toggle.” Cool. But I actually read through the privacy policies, retention schedules, and safety documentation for the big three, and training is maybe half the story. Here’s what each service actually does with your data, even with training turned off. ChatGPT (OpenAI) Training: On by default. You can opt out in settings but it’s buried. What stays on regardless: 30-day data retention even with training off, only Enterprise Zero Data Retention eliminates this Telemetry is explicitly carved out from the training opt-out: click patterns, session duration, feature usage, model selection: all still collected, no user-facing off switch Human reviewers can access conversations for “quality assurance,” abuse prevention, and model improvement Conversations, IP address, geolocation, device info, browser data, and network activity all stored server-side Deleted conversations persist in backups for up to 30 days Data can be shared with partners. Claude (Anthropic) Training: Opt-in since October 2025. Off by default. Better. What stays on regardless: 30-day backend retention even with training off That 30-day window is an active review period, safety classifiers scan conversations in real-time A system called “Clio” analyzes conversation patterns across the platform for abuse detection, anonymizing user data. Human reviewers can access flagged chats. Flagged content retained longer than 30 days (up to 2 years), and used for safety research even if you opted out of training If you opt IN, retention jumps from 30 days to 5 years To Anthropic’s credit: they’re the most transparent about when humans can see your stuff. And they don’t use your data for training by default, which puts them well ahead of OpenAI. Gemini (Google) Training: You can turn it off by disabling “Gemini Apps Activity.” But here’s the catch: doing so also disables your chat history. No memory, no continuity, no scrolling back to find that thing it said yesterday. You get privacy or you get a functional AI. Pick one. What stays on regardless: 72-hour minimum retention with no opt-out whatsoever, even with activity fully off If activity is on: 18-month default retention, adjustable to 3 or 36 months Google logs prompt shape and latency telemetry even with activity turned off Human reviewers check conversations by default. Google’s own guidance to users is literally: Don’t enter anything you wouldn’t want a reviewer to see. Any conversation a human reviewer touches gets retained for up to 3 years on a separate path you cannot view, delete, or audit Gemini inherits your existing Google account permissions, overly broad sharing settings, old group memberships, legacy folder access all get swept in The settings to actually opt out of all this are scattered across 4+ different surfaces in your Google account The bottom line: For most users, Gemini’s privacy option functionally guts the product. You’re choosing between an AI that remembers you but lets humans read your conversations, or a stateless prompt box with a 72 hour data ghost that Google still collects telemetry from. PGS AI (pgsgrove.com - disclosure: I’m with the team) Training: PGS never trains on user data, and human reviewers only ever see chats flagged as truly dangerous. There is no toggle. Because there is no training on user data. Period. Not opt-in, not opt-out. It doesn’t exist. What we collect: Infrastructure health metrics only: is the server overwhelmed, does it need to scale. That’s it. No click tracking. No session telemetry. No usage pattern collection. No behavioral profiling. No human review unless a serious safety violation is flagged (we’re talking malware requests, weapons, not someone’s spicy roleplay) We don’t retain conversations for "product improvement.” We don’t run pattern analysis systems across your chats. Row-level security + encryption at rest and in transit We’re currently in paid beta. We don’t have a free tier because we don’t ever harvest, train on, use, or sell customer data, which is how most major labs subsidize their free tiers. But we have low entry points that still give real usage to explore the platform (starting around $4). Our privacy architecture isn’t a policy we bolted on, it’s how the system was built from day one. TL;DR “No model training” is not the same thing as “private.” Most AI companies have 3-5 additional data pipelines running behind that toggle. Worth knowing what you’re actually agreeing to. Happy to answer questions. I’m being transparent that I’m with PGS, but the comparison data is pulled from each company’s own published policies and independent privacy reviews. submitted by /u/Whole_Succotash_2391
Originally posted by u/Whole_Succotash_2391 on r/ArtificialInteligence
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