Responsible AI @ Microsoft - Governance, Standards, Learnings

How does Microsoft govern AI as both a powerful tool and a potential weapon? See the framework they use to move from abstract principles to concrete practice.

#1about 2 minutes

Responsible AI is more than just legal compliance

Regulation shapes AI governance, but true responsibility also involves code, shared learnings, and operational standards.

#2about 3 minutes

Establishing foundational principles for AI development

Microsoft's AI strategy began by proactively addressing risks and establishing core principles like fairness, privacy, and security.

#3about 3 minutes

Addressing new risk vectors in generative AI

Generative AI introduces unique risks like jailbreaks, prompt injection, and harmful content that require continuous mitigation efforts.

#4about 2 minutes

Using the NIST framework to structure AI risk management

The NIST AI framework provides a standardized approach to map, measure, manage, and govern AI risks effectively.

#5about 4 minutes

Building a diverse and collaborative governance model

Microsoft's hub-and-spokes model for responsible AI relies on diverse teams and thorough documentation to share learnings and prevent duplicated efforts.

#6about 3 minutes

Structuring the office of responsible AI for impact

The Office of Responsible AI is organized into three key pillars—engineering, policy, and research—to address the multifaceted nature of AI governance.

#7about 3 minutes