Definition
An AI audit involves a rigorous, structured review of machine learning models and their deployment pipelines. It assesses fairness, transparency, accountability, and security to identify potential biases or risks. Audits are critical for maintaining trust with stakeholders and regulators, ensuring that automated decisions do not violate legal or moral guidelines. This process often includes testing datasets, reviewing algorithmic logic, and evaluating impact on affected populations.
Summary
A systematic evaluation of AI systems to ensure compliance with ethical standards, regulatory requirements, and performance benchmarks.
Key Concepts
- Compliance
- Bias Detection
- Transparency
- Accountability
Use Cases
- Regulatory compliance checks for financial AI
- Fairness assessment in hiring algorithms
- Security vulnerability scanning in deep learning models