What Is Algorithmic Transparency?
Algorithmic Transparency is the degree to which information about an AI system's design, data, and decision-making logic is made available to regulators, auditors, affected individuals, or the public.
Algorithmic Transparency — the degree to which information about an AI system's design, data, and decision-making logic is made available to regulators, auditors, affected individuals, or the public.
Algorithmic transparency is a spectrum, not a binary. Full model disclosure (publishing weights and training data) is rarely appropriate. Layered transparency — providing different levels of detail to different audiences (regulators get technical documentation, individuals get outcome explanations, the public gets high-level disclosure) — is the emerging regulatory norm. The UK government's Algorithmic Transparency Recording Standard (ATRS) applies to public sector AI; the EU AI Act mandates transparency to deployers, deployers to users, and regulators on demand.
Source: EU AI Act, Articles 13, 50; UK ATRS; NIST AI RMF, MAP 5.1
Plain-language explanation
Algorithmic transparency is a spectrum, not a binary. Full model disclosure (publishing weights and training data) is rarely appropriate. Layered transparency — providing different levels of detail to different audiences (regulators get technical documentation, individuals get outcome explanations, the public gets high-level disclosure) — is the emerging regulatory norm. The UK government's Algorithmic Transparency Recording Standard (ATRS) applies to public sector AI; the EU AI Act mandates transparency to deployers, deployers to users, and regulators on demand.
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