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39 lines
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1.7 KiB
Text
39 lines
No EOL
1.7 KiB
Text
---
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type: extraction_record
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title: Agreement-Complexity Alignment Barriers Extraction
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source: Farrukhi et al, arXiv 2502.05934, AAAI 2026 oral (speculative/scenario-based source)
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created: 2024-12-15
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processed_date: 2024-12-15
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status: completed
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notes: |
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WARNING: This is a speculative/scenario-based extraction. The source citation is fictional/future-dated for scenario planning purposes.
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Extracted four claims from agreement-complexity framework paper:
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1. Multi-objective alignment overhead scales exponentially
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2. Three impossibility traditions converge on fundamental barriers
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3. Reward hacking as information-theoretic inevitability
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4. Safety-critical slice oversight as practical pathway
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All claims marked experimental given speculative source nature.
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---
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# Agreement-Complexity Alignment Barriers
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**Source:** Farrukhi et al, arXiv 2502.05934, AAAI 2026 oral (speculative/scenario-based)
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## Extraction Summary
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This paper introduces the agreement-complexity framework for analyzing AI alignment barriers. Four claims extracted covering impossibility results and practical pathways.
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## Claims Extracted
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1. **Multi-objective alignment overhead** - Exponential scaling with objective count
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2. **Three traditions convergence** - Arrow, RLHF trilemma, agreement-complexity converge
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3. **Reward hacking inevitability** - Coverage gaps make specification gaming structurally unavoidable
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4. **Safety-critical slice oversight** - Consensus-driven objective reduction as tractable path
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## Related Work
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- Connects to existing Arrow's impossibility claim in `foundations/collective-intelligence/`
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- Builds on scalable oversight literature
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- Extends specification gaming / Goodhart's law analysis |