Algorithmic Transparency
Algorithmic transparency is the practice of making accessible and intelligible information available about where, why, and how algorithmic or AI systems are used, what role they play in decisions, which data and safeguards are involved, who is accountable, and what limitations or routes for review exist. It does not always require public disclosure of source code.
Transparency must be meaningful to its audience. A technical document that citizens or decision-makers cannot interpret may satisfy disclosure without creating understanding. Effective algorithmic transparency therefore combines public information, internal documentation, role clarity, proportional detail, and legitimate protection for security, privacy, confidential information, and system integrity.
Foreign-affairs institutions use public authority while also handling sensitive information. They must balance legitimate confidentiality with the need to explain when automated tools influence services, analysis, prioritization, or public-facing interaction. Clear transparency strengthens accountability and trust, while poorly designed disclosure can expose sensitive operations or create a false impression that a complex system is fully understood.
Algorithmic transparency appears in public AI registers, algorithmic transparency records, system and model cards, procurement documentation, impact assessments, decision notices, internal inventories, citizen explanations, audit materials, and policies describing when AI may be used in official work.
Closely related entries kept separate because each carries a distinct institutional meaning.
- Auditability
Auditability is the degree to which a system, process, or decision can be independently examined and reconstructed using reliable records of inputs, outputs, actions, changes, identities, approvals, rules, and relevant context. Auditability enables accountability and learning, but it requires records that are complete, protected, interpretable, and accessible to authorized reviewers.
- AI Register
An AI register is a structured and maintained inventory of AI or algorithmic systems used, procured, developed, piloted, or authorized by an organization. It records information needed for governance, such as purpose, owner, provider, data, users, risk level, decision role, deployment status, safeguards, assurance evidence, review dates, and retirement or exit arrangements.
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