Decisionslike

Decisionslike is a neologism used to describe artifacts, datasets, or processes that are organized to resemble human decision making. In this sense, a decisionslike object presents options, criteria, trade-offs, and prospective outcomes in a structured, decision-centric format rather than as raw data or fixed conclusions. The term is not standard in mainstream literature but appears in discussions about decision support, explainability, and AI reasoning designs.

Etymology and usage: The term combines decision with like to indicate resemblance to decision processes. It is predominantly used in academic or speculative contexts to discuss how information can be structured to mimic or reveal decision making, rather than to prescribe a particular method.

Characteristics: Typical features include a catalog of alternatives, explicit criteria or preferences, weights or scores, predicted outcomes, and an explicit rationale or justification for recommended choices. Decisionslike artifacts often include provenance trails showing how a conclusion was reached and how different options were evaluated.

Formats and examples: Examples may include decision trees or decision logs presented in narrative form, scenario analyses, or AI system outputs that foreground the reasoning steps as actions with justification. It can be applied to decision support systems, policy analysis, or auditing processes to improve transparency.

Applications and implications: Benefits include improved traceability, accountability, and the ability to audit decisions. Critics warn that without standardized definitions, the term can be vague, and misinterpretations may arise between decision-like representations and genuine deliberation.

See also: decision theory, explainable AI, decision log, traceability. Notes: the concept remains niche and evolving, with no single canonical definition.