Epistemic norms for AI safety and alignment research
Mainstream AI research emphasises capability growth and tolerates low failure rates when average-case performance is high. AI safety and alignment research has a different mission: to ensure that catastrophic failures never occur, under sparse evidence, adversarial dynamics, and fat-tailed risk. We argue that the two domains differ along two analytically independent axes — capability profile (demonstrating the absence of hazardous behaviours versus the presence of positive capabilities) and risk
Record details
Published: 7 August 2026
Source: Artificial Intelligence Review
Category: Research
Topics: Safety & alignment
Retrieved: 8 August 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Flowing Through States: Neural ODE Regularization for Reinforcement Learning
arXiv cs.LG · 6 August 2026
From Cheap Fakes to Pure Synthesis: Addressing the New Era of T2V Fake News Videos
arXiv · 7 August 2026
Studying People to Study AI: Expert Perspectives on the Epistemic Fit and Barriers of Human Research in AI Safety & Ethics
arXiv cs.CY · 7 August 2026
Multi-Agent Forensic Reasoning for Generalizable Deepfake Video Detection
HuggingFace Daily Papers · 6 August 2026
Progressive Alignment of Recommender Foundation Model through Multi-Phase Post-Training
arXiv · 7 August 2026
Bias Analysis of L2 Speaking Assessment Systems Using Concept Activation Vectors
arXiv · 6 August 2026
How to cite this record
ethics.ai (7 August 2026), “Epistemic norms for AI safety and alignment research,” evidence record 17492, https://ethics.ai/record/17492 (originally published by Artificial Intelligence Review).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.