Term
Model Governance
Definition
Model Governance is a set of processes that ensure AI model development, usage, and auditing adhere to specific rules and ethical standards. It helps maintain the reliability, compliance, and transparency of AI systems.
Where you’ll find it
In AI, Model Governance is typically outlined in policy documents or embedded in AI platforms through compliance checklists, audit trails, or reporting systems. It may not be a visual feature but is part of the regulatory and operational framework of AI tools and platforms.
Common use cases
- When establishing a new AI project, ensure all developmental and operational procedures follow ethical guidelines and legal requirements.
- Regularly audit AI models to detect and rectify any bias, ensuring fairness in automated decisions.
- While updating AI systems, assess compliance with the latest laws and ethics around AI usage.
Things to watch out for
- Lack of clarity on local regulatory requirements can lead to compliance issues.
- Misunderstandings about the scope of responsibility, especially regarding who is responsible for upkeep of governance protocols.
- Possible conflicts between built-in model governance in AI platforms and external regulatory demands that may need additional adjustments.
Related terms
- AI Ethics
- Compliance Audit
- Bias Detection
- Regulatory Compliance
- Transparency in AI
Pixelhaze Tip: Start your AI projects with a clear Model Governance framework in the planning stages to avoid legal and ethical pitfalls later on. This proactive approach ensures compliance and builds trust with users and clients.