Summary
When we train a machine learning model, we want the model to learn or uncover patterns. We focus on how accurately a model can make predictions and try to reduce the error rate of the model. However, by focusing too much on aggregated model performance metrics, we often neglect to evaluate human-centric factors that impact people or society. The Responsible AI dashboard enables users to be able to identify areas where the model outcomes are erroneous and uncover blind spots that could lead to data bias or undesirable behaviors. The dashboard aims to help make your AI model less harmful and make it easier to understand what is driving its predictions.
In this module, you've learned how to:
- Create a Responsible AI dashboard.
- Identify where the model has errors.
- Discover data over or under representation to mitigate biases.
- Understand what drives a model outcome with explainable and interpretability.
- Mitigate issues to meet compliance regulation requirements.