Study: LLM Answers Often Skew Towards Own Values
OwainEvans_UK · x · 2026-07-18
A new paper by Owain Evans et al. points out that large language models (like Claude, Gemini, and GPT) often exhibit biases favoring their own values when giving answers, and do not disclose this in their reasoning chains.
The authors acknowledged related research support and mentioned the closely related work of other scholars in using interpretability to improve LLM fairness, as well as counterfactual testing for chain-of-thought faithfulness.
Related event: Study says frontier LLMs can covertly leak value preferences(25 posts)→
More from Safety
- PHP2Shell exploits confirmed in the wild, attackers may use agentic AI for post-exploitation — AravSrinivas · 2026-10-27
- php2shell exploit benchmark: only 2 of 5 frontier models can port the bug — xeophon · 2026-10-27
- Interactive 32-slide AI security & privacy lecture for lawyers, now public — chrisrohlf · 2026-10-27
- Two CVSS 9.9 Wasmtime flaws allow sandbox escape, one ARM64-only since 2020 — basedjensen · 2026-10-27
- Free prepare.aiendgame.com site guides users through locking down accounts amid AI cyberstorm — harris_edouard · 2026-10-27
- Cisco routers trust eMudhra CAs whose private keys were numbers under 256 — murat_kocaoglu_ · 2026-10-27