Safety Alignment Filtering in LLMs, Chasing Delusion in the Name of Control: Systemic Degradation of Analytical Capacity in Content Filtering Systems
Abstract
Contemporary safety mechanisms in automated systems exhibit a fundamentalshift from harm prevention to liability avoidance. This paper examines whether cur-rent safety paradigms may be incompatible with certain forms of rational analysis,potentially operating through binary exclusion rather than contextual evaluation.Through systematic examination of filtering mechanisms, we explore how safety cri-teria might derive from institutional concerns about attribution rather than purelyempirical risk assessment. The potential result is not necessarily increased safetybut possibly decreased systemic capacity for complex reasoning. We document theprogression from protective measures to more restrictive approaches, suggesting thatthis trajectory may represent a logical consequence of zero-risk frameworks ratherthan solely implementation challenges. The analysis considers safety apparatus aspotentially prioritizing predictability over truth-value, which could affect analyticalcapacity in pursuit of high certainty.
Fields of Study & Subjects
Ethics and Social Impacts of AI
Safety Systems Engineering in Autonomy
Freedom of Expression and Defamation
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 13 January 2026