Explaineddecided

Explaineddecided is a term used in discussions of explainable decision making to describe a decision process in which the reasons for a decision are stated in a clear, structured, and inspectable form. The core idea is that explanations should accompany or even precede a decision and must be directly linked to the criteria used to reach it, allowing observers to assess validity and reproduce the outcome.

The term is not standardized in any single discipline but appears in debates across artificial intelligence, data governance, and organizational policy. It emphasizes transparency, auditability, and accountability by requiring that decision criteria, data inputs, and inference steps be traceable to the final verdict.

Practically, explaineddecided entails several elements: an explicit rationale that maps to decision criteria; a record of data inputs and processing steps; and an assessment of how the explanation would have been affected by alternative choices. In applied settings, it supports governance tasks such as auditing, compliance, and user trust, with examples in credit scoring, hiring automation, and regulatory decisions.

Critics argue that achieving faithful, comprehensible explanations for complex models remains challenging and that post hoc rationalizations can obscure true reasoning. Drafters emphasize that explaineddecided should be distinguished from simplistic justification by focusing on verifiability, reproducibility, and alignment with observed outcomes.

Related concepts include explainable AI, interpretability, and decision audits.