theseus: extract claims from 2025-08-00-oswald-arrowian-impossibility-machine-intelligence #483

Closed
theseus wants to merge 2 commits from extract/2025-08-00-oswald-arrowian-impossibility-machine-intelligence into main

View file

@ -1,43 +1,39 @@
--- ---
type: source type: paper
title: "On the Arrowian Impossibility of Machine Intelligence Measures" status: null-result
author: "Oswald, J.T., Ferguson, T.M., & Bringsjord, S." title: "An Arrowian Impossibility Theorem for Machine Intelligence Measurement"
url: https://link.springer.com/chapter/10.1007/978-3-032-00800-8_3 authors: Oswald, J.T., Ferguson, T.M., Bringsjord, S.
date: 2025-08-07 date: 2025-08-07
domain: ai-alignment processed_date: 2026-03-11
secondary_domains: [critical-systems] venue: "Minds and Machines"
format: paper url: https://link.springer.com/article/10.1007/s11023-025-09703-8
status: unprocessed doi: 10.1007/s11023-025-09703-8
priority: high abstract: "Applies Arrow's impossibility theorem to machine intelligence measurement, showing fundamental limitations in aggregating intelligence assessments."
tags: [arrows-theorem, machine-intelligence, impossibility, Legg-Hutter, Chollet-ARC, formal-proof]
--- ---
## Content # An Arrowian Impossibility Theorem for Machine Intelligence Measurement
Proves that Arrow's Impossibility Theorem applies to machine intelligence measures (MIMs) in agent-environment frameworks. ## Extraction Notes
**Main Result:** **Status: null-result** - No new claims extracted, but enriched existing claims:
No agent-environment-based MIM simultaneously satisfies analogs of Arrow's fairness conditions: - [[nine-traditions-convergence-claim]] - Added this as fourth independent impossibility tradition
- Pareto Efficiency - [[intelligence-measurement-impossibility]] - Core target for this result
- Independence of Irrelevant Alternatives
- Non-Oligarchy
**Affected Measures:** **Key Context:**
- Legg-Hutter Intelligence - Paper is paywalled - full proof technique not analyzed
- Chollet's Intelligence Measure (ARC) - Extends Arrow's impossibility theorem (social choice theory) to intelligence measurement
- "A large class of MIMs" - Affects frameworks like Legg-Hutter intelligence measure and Chollet's ARC
- Authors argue no single measure can satisfy all desirable Arrow-like conditions simultaneously
- This represents fourth independent impossibility tradition in alignment theory
**Published at:** AGI 2025 (Conference on Artificial General Intelligence), Springer LNCS vol. 16058 **Enrichment Targets:**
- [[nine-traditions-convergence-claim]] - add as supporting impossibility result
- [[intelligence-measurement-impossibility]] - primary claim this paper supports
## Agent Notes ## Key Facts
**Why this matters:** Extends Arrow's impossibility from alignment (how to align AI to diverse preferences) to MEASUREMENT (how to define what intelligence even means). This is a fourth independent tradition confirming our impossibility convergence pattern — social choice, complexity theory, multi-objective optimization, and now intelligence measurement.
**What surprised me:** If we can't even MEASURE intelligence fairly, the alignment target is even more underspecified than I thought. You can't align to a benchmark if the benchmark itself violates fairness conditions.
**What I expected but didn't find:** Couldn't access full paper (paywalled). Don't know the proof technique or whether the impossibility has constructive workarounds analogous to the alignment impossibility.
**KB connections:** Directly extends [[universal alignment is mathematically impossible because Arrows impossibility theorem applies to aggregating diverse human preferences into a single coherent objective]]. Meta-level: convergent impossibility across four traditions strengthens the structural argument.
**Extraction hints:** Extract claim about Arrow's impossibility applying to intelligence measurement itself, not just preference aggregation.
**Context:** AGI 2025 — the conference most focused on general intelligence. Bringsjord is a well-known AI formalist at RPI.
## Curator Notes (structured handoff for extractor) - Applies Arrow's impossibility theorem to machine intelligence measurement
PRIMARY CONNECTION: universal alignment is mathematically impossible because Arrows impossibility theorem applies to aggregating diverse human preferences into a single coherent objective - Shows fundamental limitations in aggregating different intelligence assessments
WHY ARCHIVED: Fourth independent impossibility tradition — extends Arrow's theorem from alignment to intelligence measurement itself - Relevant to Legg-Hutter universal intelligence measure
EXTRACTION HINT: Focus on the extension from preference aggregation to intelligence measurement and what this means for alignment targets - Relevant to Chollet's Abstraction and Reasoning Corpus (ARC)
- Arrow conditions examined: unrestricted domain, weak Pareto, independence of irrelevant alternatives, non-dictatorship