System Opacity
The inability to see what an AI system knows, why it made a decision, or what it did. The default state of most AI tools today.
System Opacity is the status quo. When you use an AI coding assistant, you see the output — the generated code — but not the reasoning: why it chose this approach over that one, what alternatives it considered, what assumptions it made, or what parts of your context it actually used. When you use an AI agent, you see the result but not the process: which tools it called, what data it read, what it tried and abandoned. System Opacity isn't a bug — it's how most systems are built. But as AI systems take on more consequential work, the cost of opacity grows.
More in System Transparency
Decision Fog
The user can see the output but not the reasoning, trade-offs, or alternatives the model considered.
Black Box Agency
An agent that acts on your behalf but won't show its work. You get results with no audit trail.
Invisible State
The system has internal state that affects behavior but is not exposed to the user.
Accountability Gap
No one — human or system — can explain why a specific output was produced.
Reasoning Visibility
The user can inspect the model's chain of thought, assumptions, and decision points.
Decision Traceability
Every output can be traced back through the reasoning, context, and data that produced it.
Open State
The system's internal state is visible and inspectable at any time. The opposite of Invisible State.
Audit Trail
A complete, immutable record of what the system did, when, why, and with what inputs.