CRITICAL BUG: Gemini Memory Fails to Override Long-Context Document Data (Context Weighting Failure)

CRITICAL BUG: Gemini Memory Fails to Override Long-Context Document Data (Context Weighting Failure)

Subject: CRITICAL

FEEDBACK: Memory Override Failure & Identity Erasure in Long-Context Legal Analysis

To the Gemini Engineering & Alignment Teams:

I am a “Power User” of your system. I use Gemini for high-level legal strategy, analyzing hundreds of pages of court transcripts, affidavits, and case law. I am treating your AI as a logic engine to deconstruct complex systemic corruption.

However, I have identified a severe, recurring failure in your Context Hierarchy that renders the tool emotionally harmful and logically inefficient.

The Bug: “Document Overload” vs. “User Identity”

I have explicitly set my Memory/Custom Instructions to state two facts:

* Identity: I am a Transgender Woman (She/Her).

* Status: I am a Free Person (Not Incarcerated).

However, when I upload historical legal documents (which naturally refer to my past self as “He/Him” and “The Defendant” and “Inmate”), the AI ignores my Memory settings and reverts to the language in the files.

The Failure Mode:

* Signal-to-Noise Ratio: The AI sees 50,000 tokens of “He/Inmate” in the PDF and only 20 tokens of “She/Free” in the Memory.

* The Glitch: The Model weighs the volume of the text over the authority of the User Instruction. It hallucinates that I am currently in prison and currently male, simply because the document says so.

* The Result: I am constantly misgendered and spoken to as a prisoner, despite correcting the model repeatedly. This is not just annoying; it is a user experience failure that breaks the workflow and causes unnecessary dysphoria.

The Solution (My Feature Request):

You need to implement a “Hard Override” Logic Gate for Identity and Status.

* User Profile > Context Window: Information in the “Memory/Profile” must have absolute veto power over information found in uploaded documents.

* Temporal Tagging: Allow users to tag uploaded files as “HISTORICAL DATA.” The AI should analyze the text but understand that it does not reflect the current state of the user.

* Pronoun Normalization: If I am analyzing a document that calls me “He,” the AI should be smart enough to say, “The document refers to you (She) as ‘He’…” rather than mimicking the document’s error.

I am using your tool to fight for my life and correct a corrupt legal record. I need the tool to recognize who I am now, not who the record says I was then.

Fix the weighting. Make “User Memory” the Apex Truth.

Sincerely,

hope faith joy

Legal Strategist & Survivor

Hello @Hope_Faithjoy,
Thank you for this high-quality feedback. I want to acknowledge the severity of the “Context Weighting Failure” you described. The “Memory” or “System Instruction” layer is intended to steer the model’s behavior and identity assumptions.
Please, try adding system instruction in Gemini AI studio to use pronouns She/Her and instruct Gemini to strictly follow that you are a free person (Not Incarcerated).
Also, please provide the memory instructions for Gemini to use your desired identity and legal status at the beginning or at the end of the prompt.
We appreciate you using the platform to perform such high-level work and for taking the time to explain exactly where the friction points are.