Agentic LLMs Pose Novel Risks

"Currently, LLMs are chiefly being used in search and chat applications. This reactive nature limits the risks posed by LLMs. However, an LLM can be enhanced in various ways to create an LLM-agent to autonomously plan and act in the real-world and proactively perform its assigned tasks (Ruan et al., 2023). Such enhancements can come from further specialized training (ARC, 2022; Chen et al., 2023a), specialized prompting (Huang et al., 2022a), access to external tools (Ahn et al., 2022; Mialon et al., 2023), or other forms of “scaffolding” (Wang et al., 2023a; Park et al., 2023a). Due to increased autonomy, limited direct oversight from human users, longer horizons of action, and other reasons, LLM-agents are likely to pose many novel alignment and safety challenges that are not currently well-understood (Chan et al., 2023a)."