Human AI Governance

AI governance beyond policy

AI governance is not only defined in policy and regulation. It is shaped in everyday decisions about how systems are built, used, and managed.

This site brings together perspectives from across that work to show how governance is practised in real contexts.

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A large, transparent glass sphere etched with intricate circuit-like patterns and faint ethical symbols, resting on a brushed aluminum pedestal in a minimalist conference room. Around it, sleek dark tables and softly glowing screens display muted graphs and policy diagrams, all slightly out of focus. Cool daylight filters through tall frosted windows, creating soft, diffused reflections on the sphere’s surface and gentle shadows across the table. Photographic realism with a clean, modern aesthetic, captured at eye level with a shallow depth of field so the sphere is in crisp focus. The mood is thoughtful and professional, evoking calm, systematic reflection about AI governance and responsible decision-making in a neutral, contemporary space.

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An orderly network of transparent glass cubes, each containing a softly glowing abstract icon representing data, regulation, security, and fairness, arranged on a matte charcoal surface like a structured cityscape. Narrow corridors between cubes form precise grid lines. Overhead, a cool, diffused studio light creates crisp, controlled shadows and subtle reflections on the glass edges, emphasizing clarity and structure. Photographic realism with a slightly elevated angle, using the rule of thirds to highlight a central cube marked with a balanced scale symbol. The atmosphere is calm, analytical, and professional, suggesting methodical AI governance frameworks and the careful balancing of competing values within a clean, modern environment.

About

Human AI Governance explores how AI governance is practised across different roles and contexts.

Most discussions of AI governance focus on regulation, ethics, and compliance. These are important, but they do not capture how governance actually happens in practice. Decisions about AI systems are shaped by many people: researchers, engineers, product teams, consultants, policymakers, and others. Much of this work is not labelled as governance, even though it directly affects how systems behave and what outcomes they produce.

This site documents that distributed reality.

Through interviews, explainers, and curated resources, it brings together perspectives on how responsibility, control, trust, and trade-offs are handled in real settings. The aim is not to provide a single framework, but to make visible the different ways governance is understood and enacted.

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