Overview
- Responsible AI
- Making sure AI systems are transparent and trustworthy
- Mitigating potential risk and negative outcomes
- Throughout whole AI lifecycle: design, development, deployment,
monitoring, evaluation
- Security
- Ensure that confidentiality, integrity, and availability are maintained
- On organizational data and information assets and infrastructure
- Governance
- Ensure to add value and manage risk in the operation of business
- Clear policies, guidelines, and oversight mechanisms to ensure AI systems align with legal and regulatory requirements
- Improve trust
- Compliance
- Ensure adherence to regulations and guidelines
- Sensitive domains such as healthcare, finance, and legal applications
Detailed Pages
Responsible AI
GenAI Challenges
Governance for AI
Compliance for AI
Security and Privacy for AI
MLOps