The importance of responsible and explainable AI
1. The importance of responsible and explainable AI
AI has significant potential to help solve challenging problems, including advancing medicine, understanding language, and fueling scientific discovery. To realize that potential, it's critical that AI is used responsibly. To that end, Google has established principles that guide Google AI applications, best practices to share our work with communities outside of Google, and programs to operationalize our efforts. These principles are grounded in: bold innovation, responsible development and deployment, and collaborative progress, together. Although these are Google's own guiding AI principles, we urge other organizations to develop their own set of principles that encourage responsible AI development. It's also important for organizations to debug and improve ML model performance and help others understand their model's behavior. Organizations building ML models also need help with detecting and resolving bias, drift, and other gaps in their data and models. In addition, having human interpretable explanations of your ML models will help grow end-user trust and improve transparency. Explainable AI is Google Cloud's set of tools and frameworks to help you understand and interpret predictions made by your machine learning models. These tools are natively integrated with several Google products and services to ensure transparent AI development.2. Let's practice!
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.