CONTEXT CONTROLS FOR AI SYSTEMS

Summary

A concise design requirement for systems that draw from chats, files, memory, and connected services. Users should be able to see the active context boundary and deliberately separate private or high-consequence material. The sequence keeps context inclusion and exclusion, memory, and connected tools connected to lived context.

What it maps

Context inclusion and exclusion, memory, connected tools, sensitive work, data separation, transparency, user control, and the ability to reset or compartmentalise. It also tracks how context inclusion and exclusion and memory reinforce or constrain one another over time.

Why it matters

Invisible context can create surprising outputs, privacy spillover, and false confidence about what the system knows. Clear controls preserve consent, reduce leakage, and improve the interpretability of results. That clarity supports more deliberate choices about context inclusion and exclusion and memory in practice.