CARE – A Governance Reference Framework for Explainable, Reviewable and Appealable Decisions

CARE (Civic Accountability, Review & Explainability) is an open, governance-first reference framework for AI-assisted and automated decision-making systems that affect people directly. As algorithmic and AI-driven systems increasingly influence public administration, welfare decisions, compliance, and access to rights, CARE addresses a critical structural gap: the lack of operational governance that ensures decisions remain explainable, reviewable, and appealable in practice. CARE is not a product, AI model, or software implementation. It is a technology-agnostic governance architecture that defines the conditions under which decision systems remain legitimate, accountable, and human-centred across sectors and jurisdictions. Core contributions: - Operational governance for AI-assisted and automated decision systems - A unified Explainable → Reviewable → Appealable decision chain - Explicit design for human vulnerability and low-capacity contexts - Technology-agnostic and sector-independent applicability - Public, citable reference architecture enabling reuse, scrutiny, and institutional adoption CARE is designed to complement existing regulation (e.g. AI governance, administrative law, digital rights frameworks) by translating high-level principles into practical structural requirements before, during, and after decisions are made. The framework is published openly to support transparency, responsible system design, and the protection of individuals subject to automated or AI-assisted decisions. Author / Originator: Nick Vejle Status: Public reference framework (open publication) Intended use: Governance, policy, public sector systems, responsible AI design