Human-AI Collaboration

Autonomy Spectrum

Provide a spectrum of autonomy levels - from passive suggestions to full autonomy - that users can adjust per task type, enabling granular control over how independently an AI agent operates.

What is Autonomy Spectrum?

The Autonomy Spectrum pattern replaces binary AI controls (on/off, assist/don't assist) with a graduated range of independence levels. Traditional AI interactions are either fully manual or fully automated, but agentic workflows demand nuance. A user might want their email agent to auto-sort messages without asking, but require explicit approval before sending any reply. This pattern provides four core levels - Observe & Suggest, Propose & Confirm, Act & Notify, and Full Autonomy - adjustable per task type. The key insight is that trust isn't global: users develop different comfort levels for different domains based on the agent's track record. By making autonomy granular and visible, this pattern prevents the all-or-nothing dynamic where a single bad experience causes users to abandon the agent entirely.

Example: Microsoft Copilot - Context-Dependent Autonomy

Microsoft Copilot showing different autonomy levels across email drafting and document formatting tasks

Copilot operates at different autonomy levels depending on context - suggesting text completions (Level 1), drafting full emails for review (Level 2), or auto-formatting documents (Level 3). Users experience different levels of AI independence without explicit configuration.

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