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Evidence record 4714 · automatically gathered

Position: Mechanistic Interpretability Must Disclose Identification Assumptions for Causal Claims

Mechanistic interpretability papers increasingly use causal vocabulary: circuits, mediators, causal abstraction, monosemanticity. Such claims require explicit identification assumptions. A purposive audit of 10 papers across four methodological strands finds no dedicated identification-assumptions section and a recurring pattern: validation metrics such as faithfulness, completeness, monosemanticity, alignment, or ablation effects are reported as causal support without stating the assumptions th

Record details

Published: 8 May 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Transparency
Retrieved: 14 July 2026

source-onlyevidence status

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.

Shared topic: Safety & alignment · Shared topic: Transparency

Teachers' Perceived Benefits and Risks of AI Across Fifty-Five Countries: An Audit of LLM Alignment and Steerability

arXiv · 8 May 2026

Shared topic: Safety & alignment · Shared topic: Transparency

Few-Shot Truly Benign DPO Attack for Jailbreaking LLMs

arXiv · 9 May 2026

Shared topic: Safety & alignment · Shared topic: Transparency

Acceptance Cards:A Four-Diagnostic Standard for Safe Fine-Tuning Defense Claims

arXiv · 11 May 2026

Shared topic: Safety & alignment · Shared topic: Transparency

The Open-Box Fallacy: Why AI Deployment Needs a Calibrated Verification Regime

arXiv · 11 May 2026

Shared topic: Safety & alignment · Shared topic: Transparency

Two Wrongs, No Right: Auditing Social-Desirability Bias in LLM Annotators for Computational Social Science

arXiv · 12 May 2026

Shared topic: Safety & alignment · Shared topic: Transparency

Neuron-Anchored Rule Extraction for Large Language Models via Contrastive Hierarchical Ablation

arXiv · 4 May 2026

How to cite this record

ethics.ai (8 May 2026), “Position: Mechanistic Interpretability Must Disclose Identification Assumptions for Causal Claims,” evidence record 4714, https://ethics.ai/record/4714 (originally published by arXiv).

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