Explainability tells you why a model produced an answer. Accountability proves what the system actually did with it. They're complementary — but in an audit, only accountability holds, because it can't be edited after the fact.
Explainability answers 'how did the model reach this output?' — valuable for debugging, fairness, and trust in the model itself. Accountability answers 'can you prove what the system did in production, and that the record wasn't altered?' — the question a regulator or auditor actually asks. A beautifully explained decision with no verifiable record of what happened next is still unprovable. iTechSmart focuses on accountability: every autonomous action is sealed into a tamper-evident, independently verifiable ProofLink receipt.
Accountability: proves the action happened as claimed
Accountability: tamper-evident and independently verifiable
Accountability: the evidence an audit or regulator requires
Both together: understand the reasoning AND prove the outcome
Explainability alone: describes reasoning, proves nothing about execution
Explainability alone: can be re-generated or reinterpreted after the fact
Neither: 'the AI decided' with no record and no rationale
For understanding a model, yes. For proving what a system did in production, no — explanations aren't tamper-evident and don't verify that an action happened. Accountability adds the verifiable record.
Understanding the model is good. Proving what it did is non-negotiable. See how accountability works.
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