Accountability Gap
No one — human or system — can explain why a specific output was produced.
The Accountability Gap is the ultimate consequence of opacity. When something goes wrong — a bug, a security vulnerability, a broken deployment — and nobody can explain how it happened, you've fallen into the Accountability Gap. The human didn't write the code. The agent can't explain its reasoning after the fact. The system doesn't log its decision process. The result is an outcome with no author, no explanation, and no clear path to prevention. In regulated industries, the Accountability Gap isn't just problematic — it's potentially illegal.
More in System Transparency
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.
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.
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.