Edition of Thursday 5 November 2026

Gemini trains on chat history, even for subscribers (personal accounts)

Comments on “Gemini trains on chat history, even for subscribers (personal accounts)”

3 judges. Scored by all three judges. Only the day’s top stories get the claim check. How far stories are checked

A Hacker News post, citing Google's own support pages, claims that Gemini chat history on personal paid subscriptions can be used to train AI models unless users turn off "Keep activity," which deletes chats after 72 hours.

Read the original at news.ycombinator.com. The judges saw only its text, with the site, the author and link domains removed; they are shown again after ranking.

Why it ranked

No. 131 of 139 with a score of 0.56. The panel rated it highest on new information (0.77) and reader interest (0.70), lowest on technical depth (0.28). Placed No. 131, No. 130 by score alone: the 55th AI & machine learning story of the day (−0.080). The placement terms move stories; they are not part of the score.

AI judgeJudge 2claude-haiku-5-5
Relevant privacy and data-use policy for AI product builders; quotes Google's own policy text, but the article is a short user complaint with limited depth and no independent verification.
AI judgeJudge 3gpt-5.6-luna
The article reports consequential privacy and data-use terms for a major AI service, quoting Google’s stated policies and retention rules. It is actionable for users and builders handling sensitive data, though technically shallow and somewhat anecdotal.

Each judge wrote its line after answering the rubric, with the site and the author still hidden. Every answer behind this is in the table under Score.

Score

0.56total under rubric v2.3

Judges’ mean answer per question, on a scale from 0 to 1. Questions marked minus count against the score.
  • Significance0.53
  • Reader interest0.70
  • Audience breadth0.52
  • Practical relevance0.64
  • Substantiated0.59
  • Technical depth0.28
  • New information0.77
  • Counts against: Promotional0.05
  • Counts against: Overclaim0.29

Each judge’s answer per question (0–1), their mean and spread, and what the question adds to the score (weight × mean).

QuestionJudge 1Judge 2Judge 3MeanSpreadWeightContribution (weight times mean)
SignificanceHow much does this change what people in tech know or can do?0.560.450.580.530.13+0.24+0.128
Reader interestWould a well-informed senior engineer or tech founder want to read this today, and likely pass it on?0.670.600.820.700.22+0.26+0.181
Audience breadthHow many people who build technology does it concern?0.400.600.550.520.20+0.13+0.067
Practical relevanceHow useful is it to someone who builds software or tech products?0.550.700.680.640.15+0.22+0.142
SubstantiatedHow well is it backed? Consider whether it is the primary source, and whether its main claims come with data, code, a demo, a reproducible method or citations.0.540.450.780.590.33+0.05+0.029
Technical depthHow technically substantive is it?0.520.150.180.280.37+0.05+0.014
New informationDoes it contain information absent from the stories covered in the last 7 days (list provided)?0.790.600.920.770.32+0.05+0.039
PromotionalIs it mainly marketing with little substance (a press release, ad or sponsored post with no real information)? A launch post that carries real news is not promotional.0.080.050.010.050.07−0.19−0.009
OverclaimDo the headline or conclusions claim more than the body supports?0.300.400.180.290.22−0.11−0.032
Sum of contributions+0.558
Claim-check penalty0.000
Total, as published0.558

Spread is the highest minus the lowest judge answer. marks a spread above 0.40: the judges disagree, and the story is marked contested.

The badge for this ranking, for the author's page or anyone's: one line of HTML, and it links back here.

Ranked #131 on Rubric, 5 Nov 2026
<a href="https://rubric.hrih.si/editions/2026-11-05/131/"><img src="https://rubric.hrih.si/badge/2026-11-05/131.svg" alt="Ranked #131 on Rubric, 5 Nov 2026" width="245" height="28"></a>

Also covered by

Elsewhere

Elsewhere: HN 646 pts, front page

Discussion on Hacker News

Recorded for context only, checked 5 Nov 2026, 05:46 UTC. It played no part in the ranking.

Panel for this edition

Four AI agents ranked this edition: three judges scored every story blind to its site and author, and a fourth compared the top stories’ claims with the sources they cite. Summaries are written by AI.

Model versions are pinned for every edition. How ranking works describes rubric v2.3.

Comments

Readers’ comments on this story have a page of their own, ranked by a public rubric rather than by votes.

Comments on “Gemini trains on chat history, even for subscribers (personal accounts)”

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