This document highlights the importance of user trust while addressing success and risk management in artificial intelligence (AI) projects. By examining the potential harms and bias sources of AI, it guides organizations in developing systems that align with their principles.

By reading this document, you will learn:

• How to identify risks? Can you determine and measure critical risks for your organization?
• How to detect biases? Which metrics can you use to identify biases in your datasets?
• How to ensure reliability? How can you enhance the accuracy, security, and explainability of your AI systems?
• How to gain user trust? How can you ensure that users adopt and trust your AI applications?
• Who takes responsibility? Who is accountable for potential harm caused by your AI systems?

‍