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| title: AIGov AI Governance Lab | |
| emoji: 🧭 | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: static | |
| pinned: false | |
| short_description: Interactive AI governance engineering prototype | |
| tags: | |
| - ai-governance | |
| - responsible-ai | |
| - ai-safety | |
| - compliance | |
| - risk-management | |
| # AIGov AI Governance Lab | |
| An interactive static prototype for exploring observable governance signals in AI systems. | |
| The lab evaluates engineering-level signals related to: | |
| - system impact | |
| - decision autonomy | |
| - human oversight | |
| - post-deployment monitoring | |
| - traceability | |
| - technical documentation | |
| ## Purpose | |
| The prototype demonstrates how AI governance requirements can be translated into observable and testable system controls. | |
| It is intended as an engineering and educational demonstration. | |
| It is not a legal compliance assessment and does not classify systems under any specific regulation. | |
| ## Approach | |
| AIGov treats governance as an engineering discipline. | |
| The aim is to make governance requirements: | |
| - observable | |
| - testable | |
| - reproducible | |
| - traceable | |
| - integrated into technical workflows | |
| ## Implementation | |
| The application runs entirely in the browser using HTML, CSS and JavaScript. | |
| No server-side compute or external API is required. | |
| ## Limitations | |
| The scoring model is deterministic and intentionally simplified. | |
| A governance score should not be interpreted as a legal conclusion, regulatory classification, or validated measure of production-system risk. | |
| ## AIGov | |
| AIGov builds infrastructure for transparent, auditable, and accountable AI systems. | |
| Website: https://govbase.dev | |
| GitHub: https://github.com/AIGovDev | |
| ## License | |
| Apache-2.0 | |