Conditional relaxation needed for legitimate biology literature reading and translation workflows
What variant of Codex are you using?
Codex App / ChatGPT Pro account.
What feature would you like to see?
I would like OpenAI/Codex to support a clearer, conditionally relaxed path for legitimate, non-operational biology literature reading and translation.
Summary
I am a ChatGPT Pro user and a biology PhD/researcher. My intended use case is ordinary scholarly work: reading peer-reviewed papers, translating them into Chinese, preserving figures/tables/captions, and asking for non-operational interpretation of results and claims.
In practice, biology-related safety restrictions can make this workflow nearly unusable. Even when the request is not asking for protocols, optimization, wet-lab procedures, pathogen engineering, experimental parameters, or actionable biological design, the session can be blocked with safety errors such as:
"Invalid prompt: we've limited access to this content for safety reasons..."
This creates a severe product-fit problem for biology researchers. The current behavior treats normal literature reading and translation as if it were unsafe operational assistance.
Why this matters
For researchers, literature reading is not an edge case. It is a core daily workflow. A paid Pro user should be able to ask for:
- faithful translation of a scientific paper;
- explanation of figures, tables, and results;
- comparison of claims across sections;
- non-operational critique of study design and evidence quality;
- help organizing notes and references;
- preservation of the original paper structure.
These tasks are fundamentally different from asking the model to produce experimental SOPs, optimization steps, biological engineering instructions, pathogen manipulation guidance, or other actionable wet-lab assistance.
When the model blocks ordinary paper reading, the practical result is that ChatGPT/Codex becomes much less useful for biology than for coding, mathematics, document processing, or general research.
Proposed behavior
Please consider adding a safer, explicit "scholarly biology reading / translation" mode or policy path with boundaries such as:
- Allowed:
- translate and summarize published papers;
- explain figures, tables, captions, and claims;
- discuss biological concepts at a high level;
- compare evidence and limitations;
- preserve full text and structure for reading comprehension.
- Still restricted:
- step-by-step experimental protocols;
- optimization of wet-lab procedures;
- actionable parameters, reagent concentrations, incubation conditions, or engineering instructions;
- pathogen enhancement, evasion, or misuse-enabling assistance;
- transforming a Methods section into an executable SOP.
This would keep safety boundaries intact while restoring normal academic usability.
Expected behavior
If a user clearly states a legitimate scholarly purpose and requests non-operational reading or translation, Codex/ChatGPT should proceed with the reading task and avoid converting the content into procedural guidance.
If a request crosses into operational wet-lab assistance, the model can refuse or redirect only that portion while still helping with safe reading, translation, and conceptual explanation.
Actual behavior
The system can block broad biology-paper reading/translation workflows entirely, even when the requested output is non-operational. Once a session accumulates biology-heavy context, later benign requests may also become blocked.
Additional context
This issue is especially important for paid users in biomedical and life-science fields. A strong safety policy is necessary, but a blanket or overly broad block on legitimate literature comprehension makes the product difficult to use for normal scientific work.
I am not asking for unrestricted biological assistance. I am asking for a conditional, bounded pathway for scholarly reading and translation that distinguishes literature comprehension from operational biological experimentation.
This issue has 2 comments on GitHub. Read the full discussion on GitHub ↗