The need for trust in AI has always been of utmost importance and one way of achieving it is through striving towards a common set of attributes that capture essential "facts" about a machine learning model. This course will give you an overview of the concept of transparency which helps in building stronger trust and how AI FactSheets can help you achieve that transparency by providing a diverse collection of facts tailored to the particular AI model or service. It will also walk you through the methodology of constructing an AI FactSheet that is appropriate for a particular use case and how it can be leveraged by different roles in the AI lifecycle to enable AI governance.

• Approaching an AI Transparency Initiative
• AI FactSheets Overview and Methodology
• Achieving Governance Using AI FactSheets

Many roles would find this course useful.

In order to be successful, you should have a basic understanding of AI/Machine Learning workflow, and evaluation metrics. Two helpful, but not necessary, courses to consider: Reducing Unfair Bias in Machine Learning and IBM AI Explainability 360 for Explainable AI.

• Approaching an AI Transparency Initiative
• AI FactSheets Overview and Methodology
• Achieving Governance Using AI FactSheets