EXD.Preface:6 - Assurance, limits and practical consequences

Recognize a promising explanation when its question, needed connection and use conditions are explicit enough to choose a constructive move. Assure the particular result with the relevant criterion: verify the mathematical derivation; check whether the recipient reconstructed the selected relation; inspect a recommendation’s actual premises; or examine a later unaided task when that is the claimed outcome.

A smooth paraphrase, positive reaction or correct number can motivate further inquiry without proving the underlying relation was reconstructed. Conversely, a recipient can understand a recommendation and decline it. Preserve the actual response and the assistance used; distinguish demonstrated results from stipulated examples and expected gains.

The principal trade-offs are useful detail against effort, guidance against the independent contribution sought, responsiveness against interruption, and additional comparison against the value of a sufficient incumbent. Prefer the smallest change that addresses a consequential difficulty. Endless elaboration, repeated elicitation after an explicit answer and unsupported certainty all consume the resource the explanation needs.

The examples favor explicit relations, short exchanges and inspectable outcomes. Tacit, affective, embodied and culturally situated understanding may require other forms and criteria. A recipient’s unfamiliar terminology or access needs are conditions for design, rather than evidence of general incapacity. The human–AI profile further limits what can be inferred from an AI’s output.

In practice the language changes where repair is directed and when work stops. It supplies a warranted connection, a worked correspondence, a coordinated expression, an adapted exchange, a supported retry or a justified comparison. It returns a missing subject basis, a changed decision or a stronger assurance question to the work that can answer it.