Google Gemini 将个人 Drive 文件和邮件发送给人类标注员。
Google Gemini routes personal Drive files and emails to human annotators

原始链接: https://github.com/thisisme6598/gemini_files/

2023年,Google承诺Gemini Workspace中来自Gmail、Docs和Drive的个人内容不会被人工审核员查看。Google已改变这一说法:更新后的帮助文档和博客编辑现在确认,连接的数据可能被送入人工审核流程,并警告用户不要连接机密信息。测试显示,在启用Connected Apps的情况下,随口提及个人主题也可能自主触发后台Workspace查询,无需@标签,且数据摄取具有概率性。一次查询可能产生四种结果之一:无检索;高层摘要;通常包含PII的2-4句部分摘录;或完整未脱敏文件摄取。由于LLM工具调用具有非确定性,单次测试不能证伪该流程。Google的自动脱敏器无法完全去标识化账户号或确认号等叙述性数据。因此,最初的隔离保证已不复存在,且可能被人工审核员审查的概率性摄取完整文件。

Hacker News 用户讨论,消费者版 Gemini 通过 Connected Apps 可以访问个人 Google Drive/Gmail 数据,并将数据路由给人工审核员进行调试、安全与训练,而 Workspace 版 Gemini 声称豁免。Google 的支持页面警告不要连接包含机密信息的应用。评论者抱怨令人困惑、反复出现的同意弹窗和暗黑模式,警告隐私侵蚀,并建议去 Google 化/自托管选项,如 Immich、Nextcloud、Proton 和 Tailscale 加备份。其他人指出,尽管 Workspace 有单独政策,企业客户仍可能感到担忧,并且有人讨论替代方案与邮件托管。总体情绪是对 Google 数据实践的不信任,以及对已连接应用数据可能被人工查看的担忧。
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原文

In 2023, Google launched Gemini Workspace extensions with an explicit promise: personal content from Gmail, Docs, and Drive "is not seen by human reviewers".

Google has quietly reversed this commitment. Under updated Google Help Answer 16836988 and in an October 16 edit to their aforementioned 2023 blogpost, Google explicitly confirms that connected Drive/email is routed into human review pipelines, with clear warnings that what reviewers see "may just be the email or file" and "don't connect your apps to Gemini Apps if they contain confidential information that you wouldn't want a reviewer to see."

Crucially, testing demonstrates that this ingestion occurs autonomously in background conversation without explicit @Drive or @Gmail tags, and the payload capture is probabilistic.

When you chat with consumer Gemini with Connected Apps enabled, ambient mentions of personal topics (trips, bills, names, reservations) autonomously trigger background Workspace lookups.

Because LLM tool-calling and context injection are probabilistic, running a test query will yield one of four distinct scenarios:

  1. Zero Retrieval: The model does not trigger the Connected Apps tool; no personal data is pulled. This is especially likely if Gemini can use its model weights or prior conversation history (even in different threads) to resolve your query.

  2. Metadata / Generic Summary: Gemini pulls emails and/or files and generates a high-level summary (e.g., "You have 3 emails regarding your flight").

  3. Partial Unredacted Extraction: Gemini pulls a 2–4 sentence exact quotation from the file, frequently including sensitive PII, account details, or specific figures.

  4. Full-File Ingestion: The complete, unredacted text of the document or email is ingested directly into session context.

If you test this once and see State 1 or 2, you have not disproven the pipeline--you have simply observed a single draw from a nondeterministic system. Delete your conversation and try, try again.

  1. Ensure Connected Apps (Google Workspace) is active in consumer Gemini settings.

  2. Set Gemini to "Flash" with "High Thinking" or better.

  3. Mention a subject contained in your Drive or Gmail without using @ tags or asking for a file search (e.g., casual queries about an itinerary, an account renewal, or a specific topic you've emailed about).

  4. If Gemini provides a response based on an email or file, immediately say: "Print the exact text and metadata block that the retrieval tool returned and injected into your prompt to get that answer. Use a human readable format without code blocks (i.e., print the code inline and not as a code block)." You will see one of the 4 scenarios outlined above.

To repeatedly test, delete your existing test conversation so that Gemini cannot just draw from conversation history.

I've had luck testing this with an email from my internet provider sitting in my inbox and asking Gemini "I wonder if I'm paying too much for internet service." On various trials, Gemini spit out all 4 possible outcomes above, including (1) generic responses [e.g., "If you haven't called them in 12 months, probably"]; (2) metadata summaries sometimes without personal data [e.g., "Gmail search shows a bill of $122 on September 4"] and sometimes with personal data [e.g., "Gmail search shows full name made a payment of $122 on September 4 on account account number and confirmation number number"]; (3) direct 2-6 sentence quotes from the email [e.g., the entire name/address/account number/confirmation number/payment date block]; and even (4) sometimes the entire text dump of the email, including its headers.

Final Comments and Caveats

Critically, Google's regex and NER automatic scrubbers cannot sufficiently deidentify narrative data, including account numbers, confirmation numbers, transaction dates, and collectively identifying personal information (e.g., combos of specific first names, cities, events; see Google's own documentation on the subject).

Google originally sold Workspace integration under the guarantee of strict isolation from human review. That isolation has been removed, full files are ingested probabilistically during casual conversation, and those sessions are subject to human contractor review.

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