Reviewability

Reviewability is the degree to which a decision, process, or artifact can be examined, questioned, and validated by independent observers. It emphasizes transparency, traceability, and accountability, enabling stakeholders to understand how conclusions were reached, on what evidence, and under which assumptions. Reviewability is pursued across disciplines, from law to software engineering and data science.

Key dimensions include transparency (visibility of inputs, logic, and criteria), traceability (ability to follow a decision from inputs to outcome), reproducibility (consistency of results when procedures are repeated), explainability (comprehensible rationales), and auditability (recordkeeping suitable for independent review). Different domains balance these dimensions differently according to legal, technical, and ethical requirements.

In data science and artificial intelligence, reviewability refers to the capacity to inspect how models produce outputs, verify data provenance, reproduce experiments, and audit performance. Practices such as data sheets for datasets, model cards, versioned datasets, and fully instrumented pipelines improve reviewability and support accountability and safety.

In public administration and law, reviewability governs whether decisions are subject to external scrutiny, appeal, or judicial review. Standards typically require reasoned decisions, lawful authority, and adequate notice, with mechanisms to challenge or reform outcomes where appropriate.

To enhance reviewability, organizations implement audit trails, thorough documentation, code and design reviews, change management, and external audits. Tools such as version control, reproducible pipelines, explainability techniques, and standardized reporting help stakeholders assess and challenge outcomes.

Limitations include trade-offs with privacy and security, the cost of implementing comprehensive review processes, and the reality that some complex systems cannot be fully explained. The goal is to maximize usefulness of reviewability while protecting essential constraints.