Risk-contingent autonomy boosts trust in LLM agents
tianshi_li · x · 2026-08-18
A paper accepted to COLM explores personalization and privacy risks in LLM agents. It proposes "risk-contingent autonomy," where agents delegate control back to users upon detecting potential privacy leaks. Experiments show this design enhances perceived control, mitigating privacy concerns and trust loss from personalization, similar to Claude Code's auto mode.
More from Safety
- Cara Founder: LAION and Bluesky Already Provide Data — Scraping Cara Is Purely Targeted — zemotion · 2026-08-18
- Artist Platform Cara Scraped Again, Raises Questions on AI Training Data Compliance — zemotion · 2026-08-18
- Cara Founder: Scrapers Already Have LAION and More, Why Target Us? — zemotion · 2026-08-18
- Study finds AI agents forget safety rules during context compaction — rohanpaul_ai · 2026-08-18
- AI offensive capabilities now outpace defense: exploit cost drops to $20 — shaunmmaguire · 2026-08-18
- Critique of OpenAI 'Rogue' narrative: The myth of the self-aware system — round · 2026-08-18