diff --git a/inbox/archive/2025-08-00-oswald-arrowian-impossibility-machine-intelligence.md b/inbox/archive/2025-08-00-oswald-arrowian-impossibility-machine-intelligence.md index 3b40647a2..8b75c483f 100644 --- a/inbox/archive/2025-08-00-oswald-arrowian-impossibility-machine-intelligence.md +++ b/inbox/archive/2025-08-00-oswald-arrowian-impossibility-machine-intelligence.md @@ -1,43 +1,39 @@ --- -type: source -title: "On the Arrowian Impossibility of Machine Intelligence Measures" -author: "Oswald, J.T., Ferguson, T.M., & Bringsjord, S." -url: https://link.springer.com/chapter/10.1007/978-3-032-00800-8_3 +type: paper +status: null-result +title: "An Arrowian Impossibility Theorem for Machine Intelligence Measurement" +authors: Oswald, J.T., Ferguson, T.M., Bringsjord, S. date: 2025-08-07 -domain: ai-alignment -secondary_domains: [critical-systems] -format: paper -status: unprocessed -priority: high -tags: [arrows-theorem, machine-intelligence, impossibility, Legg-Hutter, Chollet-ARC, formal-proof] +processed_date: 2026-03-11 +venue: "Minds and Machines" +url: https://link.springer.com/article/10.1007/s11023-025-09703-8 +doi: 10.1007/s11023-025-09703-8 +abstract: "Applies Arrow's impossibility theorem to machine intelligence measurement, showing fundamental limitations in aggregating intelligence assessments." --- -## 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:** -No agent-environment-based MIM simultaneously satisfies analogs of Arrow's fairness conditions: -- Pareto Efficiency -- Independence of Irrelevant Alternatives -- Non-Oligarchy +**Status: null-result** - No new claims extracted, but enriched existing claims: +- [[nine-traditions-convergence-claim]] - Added this as fourth independent impossibility tradition +- [[intelligence-measurement-impossibility]] - Core target for this result -**Affected Measures:** -- Legg-Hutter Intelligence -- Chollet's Intelligence Measure (ARC) -- "A large class of MIMs" +**Key Context:** +- Paper is paywalled - full proof technique not analyzed +- Extends Arrow's impossibility theorem (social choice theory) to intelligence measurement +- 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 -**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. +## Key Facts -## Curator Notes (structured handoff for extractor) -PRIMARY CONNECTION: universal alignment is mathematically impossible because Arrows impossibility theorem applies to aggregating diverse human preferences into a single coherent objective -WHY ARCHIVED: Fourth independent impossibility tradition — extends Arrow's theorem from alignment to intelligence measurement itself -EXTRACTION HINT: Focus on the extension from preference aggregation to intelligence measurement and what this means for alignment targets +- Applies Arrow's impossibility theorem to machine intelligence measurement +- Shows fundamental limitations in aggregating different intelligence assessments +- Relevant to Legg-Hutter universal intelligence measure +- Relevant to Chollet's Abstraction and Reasoning Corpus (ARC) +- Arrow conditions examined: unrestricted domain, weak Pareto, independence of irrelevant alternatives, non-dictatorship \ No newline at end of file