Microsoft Responsible AI Principles Explained for Engineers
How to Turn Responsible AI Principles into Real, Enforceable Systems Industry leaders in the tech industry are moving forward with artificial intelligence in all areas. Relatively, AI systems started to influence healthcare, insurance claims, hiring, credit scoring, fraud detection, and customer interactions by making decisions in respective areas. These are all the domains where decisions made by the AI system are very critical, though if mistakes happen, it will not be considered only as technical bugs, but it can lead to real-world harm, regulatory violations, and loss of trust in the system. Microsoft defines a set of responsible AI principles to guide the development and deployment of AI systems. These responsible AI principles help to reduce the mistakes made by the AI system. These principles provide a strong ethical and governance foundation. However, many engineering teams struggle with a critical gap.
Continue reading on DZone
Opens in a new tab

![[MM’s] Boot Notes — The Day Zero Blueprint — Test Smarter on Day One](/_next/image?url=https%3A%2F%2Fcdn-images-1.medium.com%2Fmax%2F1368%2F1*AvVpFzkFJBm-xns4niPLAA.png&w=1200&q=75)

