Add AIGov organization card
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README.md
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---
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title: AIGov
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emoji: 🧭
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short_description: Practical AI governance infrastructure
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---
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# AIGov
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AIGov builds infrastructure for transparent, auditable, and accountable AI systems.
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We focus on practical AI governance engineering across model evaluation, agent reliability, traceability, lifecycle controls, and regulatory readiness.
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## What we work on
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- AI governance and compliance infrastructure
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- evaluation and monitoring of AI systems
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- agent reliability and execution-trace analysis
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- transparency and auditability
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- lifecycle governance
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- model and system documentation
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- responsible AI engineering
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## Current Hugging Face work
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AIGovDev is used to publish selected public demos, datasets, models, and curated resources related to AI governance and responsible AI.
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Public work will include:
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- interactive governance demonstrations
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- evaluation datasets
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- responsible AI benchmarks
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- agent reliability tooling
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- governance-oriented ML experiments
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## Approach
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We treat AI governance as an engineering discipline.
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The goal is not only to document AI systems, but to make governance requirements observable, testable, reproducible, and integrated into technical workflows.
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## Focus areas
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### Evaluation
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Methods and tooling for assessing model and system behaviour, including reliability, failure modes, and response-level evaluation.
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### Agent governance
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Observable execution traces, tool-use behaviour, verification, failure handling, and reliability signals in agentic systems.
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### Traceability
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Technical mechanisms for reconstructing how AI systems behaved, what evidence was used, and how decisions were produced.
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### Responsible AI
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Practical implementation of transparency, accountability, oversight, monitoring, and risk-management principles.
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## Public resources
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This organization will progressively publish:
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- Spaces
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- datasets
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- models
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- collections
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- research-oriented prototypes
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## AIGov
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AIGov is developed by AIMLGov, s.r.o.
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Website: https://govbase.dev
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GitHub: https://github.com/AIGovDev
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