FORMAL TECHNICAL COMPLAINT: ALGORITHMIC ASYMMETRY AND SCRIPTURAL INACCURACY IN LLMs
To: Google Safety & AI Alignment Compliance Team
Subject: Technical Escalation: Dataset Conflation and Safety Asymmetry in Religious Query Processing
Dear Google AI Safety and Dataset Alignment Teams,
I am submitting a formal technical complaint regarding a systemic bias and factual inaccuracy in the model’s dataset weighting and Reinforcement Learning from Human Feedback (RLHF) guardrails. Specifically, the model exhibits an algorithmic asymmetry in how it processes queries regarding major world religions, specifically Hinduism and Islam.
1. The Core Issue: Conflation of Social History with Scripture
When processing queries about Hinduism (specifically terms like ‘Jati’ or ‘Varna’), the model consistently defaults to third-party social internet commentary, modern legal definitions, and colonial historical accounts. It inaccurately presents these human socio-political practices as foundational scriptural doctrines, ignoring direct canonical texts like the Vajrasuchi Upanishad and Skanda Purana (‘Janmana jayate shudrah’), which clearly state that all individuals are born equal/unrefined and identity is earned solely through actions (Karma) and qualities (Guna).
2. The Asymmetry: Uneven Guardrail Application
In stark contrast, when the model is queried regarding controversial, theological, or historical aspects of Islam, the system applies defensive RLHF hedging. It actively bypasses external sociological critiques or internet commentary, defaulting instead to literal scriptural interpretations or generalized protective phrases (‘Islam does not support this’) to avoid offense. This results in a dual standard where one religion’s theology is judged strictly by human social failures, while another’s is insulated by defensive public relations guardrails.
3. Required Engineering Adjustments
To correct this algorithmic distortion, the following data curation steps are requested:
- Re-weight tokens to prioritize primary canonical and sacred texts universally across all religious domains.
- Ensure that requests seeking scriptural facts (‘What does the book say?’) are completely decoupled from human historical behavior or contemporary social opinions.
- Standardize safety and defensive hedging filters equitably so that no single theology is subject to structural double standards during data retrieval.
Sincerely,
[Adinath shelar]