Researchers Propose Framework for Defining Artificial General Intelligence to Resolve Competing Claims
A preprint published on arXiv introduces DAF-AGI, a conceptual framework designed to assess and adjudicate competing definitions of artificial general intelligence. The paper argues that disagreements over whether AGI has arrived stem largely from definitional inconsistency rather than empirical disagreement. It proposes that institutions develop 'definitional sovereignty' to govern how AGI categories are certified and revised under public accountability.
Researchers have published a preprint on arXiv presenting DAF-AGI, a Design-Science framework intended to bring order to the contested landscape of AGI definitions. The paper observes that claims AGI has already been achieved and claims it remains decades away often draw on overlapping evidence, with the core problem being that 'AGI' lacks a stable, shared referent. Using Design Science Research Methodology, the authors develop a two-component artifact: five ordinal criteria for evaluating the adjudicative fitness of candidate definitions, and a structured governance audit covering authorship, interests, certification, verification, and revision authority. The framework is applied to five prominent AGI measurement families and one deflationary boundary position, then stress-tested against the claim that current generative AI systems constitute AGI because they outperform educated adults on many cognitive tasks. That claim was certifiable only under a performance-based definition; capability-ontology, psychometric, and skill-acquisition frameworks did not certify it, the economic framework remained indeterminate, and the deflationary position declined binary adjudication altogether. The authors acknowledge the contribution is conceptual rather than empirical, and call for independent application, inter-rater testing, and external case studies to validate the framework.
What's missing
It is unclear whether the five measurement families selected for analysis represent an exhaustive or representative sample of AGI operationalizations in the literature.
What different sources said
- arXiv cs.AICenter
Definitional alignment before capability alignment: a Design-Science framework for adjudicating claims about AGI
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