The Delegation Blind Spot: Auditing Product Decisions from Agent Choices
Successful agent execution need not identify which future product improvement its user would value. We present a decision-specific audit that maps a declared observation channel and product-value contrast to compatible intervals and witness populations. Its foundations are established identification and decision theory; the contribution is an executable measurement workflow and a controlled study of its limits. A frozen experiment makes 4,800 requests to two pinned model snapshots on shared synthetic tasks. All 36 conservative primary intervals remain unresolved despite different execution accuracy. An exploratory 2,400-call follow-up records supplied preferences and resolves three of nin...
| Authors | Shivam Gupta |
|---|---|
| Primary category | cs.AI |
| Published | 22 September 2026 |
| Last updated at source | 22 September 2026 |
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