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

The article introduces DAF-AGI, a conceptual framework for evaluating claims regarding artificial general intelligence (AGI) by establishing ordinal criteria and a governance audit process. It critiques the ambiguity in defining AGI by stress-testing various operationalizations against claims that current generative systems outperform well-educated adults, revealing that such claims are only certifiable through performance-based metrics. This framework is significant for practitioners as it provides a structured approach to adjudicating AGI definitions and emphasizes the need for definitional sovereignty in algorithmic governance.