Definitional alignment before capability alignment: a Design-Science framework for adjudicating claims about AGI

2026-06-10 · Source: Artificial Intelligence · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Expert, quick

Summary

DAF-AGI is a Design-Science framework developed to adjudicate conflicting claims about Artificial General Intelligence (AGI) by addressing the lack of a shared, stable definition. This framework comprises two components: five ordinal criteria for evaluating the "adjudicative fitness" of AGI definitions and a structured governance audit covering authorship, interest, certification, external verification, and revision authority. The framework was demonstrated on five prominent measurement families and one deflationary boundary position, then stress-tested against the claim that current generative systems constitute AGI due to their performance on cognitive tasks. Evidence from 2024-2025 sources showed this claim was certifiable only under a performance-based operationalization, while capability-ontology, psychometric, and skill-acquisition approaches did not certify it. The economic family remained indeterminate, and the deflationary position refused binary adjudication. The paper also proposes definitional sovereignty as an enabling component of algorithmic sovereignty.

Key takeaway

For policymakers evaluating AGI claims or developing regulatory frameworks, recognize that definitional ambiguity is a critical governance challenge. You should prioritize establishing clear, certifiable AGI definitions before assessing system capabilities. Implement structured governance audits, like DAF-AGI's, to scrutinize definition authorship, interests, and verification. This strengthens algorithmic sovereignty and public accountability.

Key insights

Conflicting AGI claims stem from definitional ambiguity, necessitating a framework like DAF-AGI for structured adjudication and governance.

Principles

• AGI under-specification is a design and governance problem.
• Definitional alignment precedes capability assessment.
• Definitional sovereignty enables algorithmic sovereignty.

Method

DAF-AGI uses five ordinal criteria to assess definition fitness and a governance audit (authorship, interest, certification, verification, revision) to adjudicate AGI claims.

In practice

• Evaluate AGI claims using DAF-AGI's criteria.
• Audit AGI definitions for governance factors.
• Contest imported tech categories publicly.

Topics

• Artificial General Intelligence
• AGI Definition
• DAF-AGI Framework
• Algorithmic Sovereignty
• Governance Audit
• AI Policy

Best for: Research Scientist, AI Scientist, AI Ethicist, Policy Maker

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence.