Machine Learning Audits

Machine Learning Audits are thorough evaluations of how AI models make decisions. They assess whether the models are accurate, fair, and unbiased, and check for potential risks or errors. These audits involve examining data sources, algorithms, and outputs to ensure the AI operates ethically and reliably. By conducting these reviews, organizations can identify issues, improve model performance, and build trust with users while complying with regulations. Essentially, it’s a process to verify that AI systems work as intended and do not cause harm or unintended consequences.