---
type: extraction_record
title: Agreement-Complexity Alignment Barriers Extraction
source: Farrukhi et al, arXiv 2502.05934, AAAI 2026 oral (speculative/scenario-based source)
created: 2024-12-15
processed_date: 2024-12-15
status: completed
notes: |
  WARNING: This is a speculative/scenario-based extraction. The source citation is fictional/future-dated for scenario planning purposes.
  
  Extracted four claims from agreement-complexity framework paper:
  1. Multi-objective alignment overhead scales exponentially
  2. Three impossibility traditions converge on fundamental barriers
  3. Reward hacking as information-theoretic inevitability
  4. Safety-critical slice oversight as practical pathway
  
  All claims marked experimental given speculative source nature.
---

# Agreement-Complexity Alignment Barriers

**Source:** Farrukhi et al, arXiv 2502.05934, AAAI 2026 oral (speculative/scenario-based)

## Extraction Summary

This paper introduces the agreement-complexity framework for analyzing AI alignment barriers. Four claims extracted covering impossibility results and practical pathways.

## Claims Extracted

1. **Multi-objective alignment overhead** - Exponential scaling with objective count
2. **Three traditions convergence** - Arrow, RLHF trilemma, agreement-complexity converge
3. **Reward hacking inevitability** - Coverage gaps make specification gaming structurally unavoidable
4. **Safety-critical slice oversight** - Consensus-driven objective reduction as tractable path

## Related Work

- Connects to existing Arrow's impossibility claim in `foundations/collective-intelligence/`
- Builds on scalable oversight literature
- Extends specification gaming / Goodhart's law analysis