The post explores the idea of ambient agents in AI, which work in the background to handle tasks more effectively than chat-based interfaces. It emphasizes building trust in these agents by displaying their actions and allowing user corrections. The transition from 'human-in-the-loop' to 'human-on-the-loop' is highlighted, with agents being able to pause for human feedback before continuing tasks. Examples include an email assistant that seeks human input when needed. The approach aims to enhance human capabilities by efficiently managing multiple tasks simultaneously.
Table of contents
Building trust with background agents: Moving from “Human-in-the-loop” to “Human-on-the-loop”Integrating human input: How agents can ask for help when neededConclusionSort: