CONCEPT
Behavioral Assessment
The replacement framework for the ghost question — evaluating AI systems by the observable properties of their performance rather than by hidden metaphysical facts about their interiors.
Behavioral assessment is the practical methodology that follows from Rylean dissolution of the ghost question. Once we stop asking whether the machine 'really' thinks, the tractable questions are about what the machine observably does: how flexibly, how reliably, under what conditions, with what failures. Behavioral assessment is not a lowered standard. It is the application of the same criteria we use for human intelligence — flexibility, purposefulness, context-sensitivity, self-correction — to machine performance, with attention to how those criteria apply across different domains and different dispositional profiles. It is the methodology the AI debate needs and the ghost question has been preventing.
In The You On AI Field Guide
The assessment has empirical structure. It asks: across what range of conditions does the disposition hold? What is the failure mode when it breaks down? How reliably does it self-correct? How does the profile compare to human expert performance in the same domain? These are questions with empirical answers, and the answers have direct practical implications for how