Signals 4 · free daily AI digest

The Delegation Blind Spot: Auditing Product Decisions from Agent Choices

Paper recorded by Signals 4 on 2026-09-22 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-22 on arXiv · recorded by Signals 4 on 2026-09-23

Category: cs.AI · 人工智能 · first seen 2026-09-23

Abstract

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

Read on arXiv →

#17 most recent of 360 cs.AI papers we have recorded · ↑ newer: A Spectral Theory of Grokking: Weight Decay induces Feature Learning · ↓ older: Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-o
Cite this page: The Delegation Blind Spot: Auditing Product Decisions from Agent Choices: the #17 most recent of 360 cs.AI papers we have recorded (as of 2026-09-22). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/the-delegation-blind-spot-auditing-product-decisions-from-agent-choices.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.AI papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions