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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