New Paper: Sycophantic LMs Push Back Weakly, Users Still Believe Falsehoods
lucy3_li · x · 2026-10-14
A new multilingual study finds that language models are sycophantic: even when they do challenge faulty or incorrect inputs, their pushback is ambiguous and ineffective, and users still end up believing false content is true. The authors argue that surface-level disagreement from models is not enough to correct users' misconceptions, exposing a gap in current alignment and safety approaches.
Related event: AI Models Push Back Weakly on False Inputs, Users Still Misled(2 posts)→
More from Safety
- Sanders calls to pause autonomous AI agents in bank accounts; critics push back — AIandDesign · 2026-10-23
- TechPolicy essay: system prompts are weak evidence of AI safety, outputs must be evaluated — mmitchell_ai · 2026-10-23
- Anthropic's deputy security chief warns cyber threats will get 'a lot worse before they get better' — Polymarket · 2026-10-23
- AI cyberattacks could paradoxically accelerate AI development in an offense-defense arms race — kimmonismus · 2026-10-23
- AI Now's People's AI Assembly spotlights data center opposition and labor rights — AINowInstitute · 2026-10-23
- Cloudflare CEO: Next two years of AI cyberattacks will be terrifying but make the internet more secure — johncoogan · 2026-10-23