E-Books →Machine Learning for High-Risk Applications

It's an ambitious undertaking that requires a diverse set of talents, experiences, and perspectives. Data scientists and nontechnical oversight folks alike need to be recruited and empowered to audit and evaluate high-impact AI/ML systems. Author Patrick Hall created this guide for a new generation of auditors and assessors who want to make AI systems better for organizations, consumers, and the public at large.
Learn how to create a successful and impactful responsible AI practice
Get a guide to existing standards, laws, and assessments for adopting AI technologies
Look at how existing roles at companies are evolving to incorporate responsible AI
Examine business best practices and recommendations for implementing responsible AI
Learn technical approaches for responsible AI at all stages of system development