The 4 Pillars of Responsible AI
Key Takeaways:- Understand the four pillars of responsible AI: fairness, efficacy, transparency, and accountability.
- Learn how to create processes and controls that ensure responsible AI development.
- Discover best practices for building and scaling responsible AI initiatives at your enterprise.
Description
Building responsible AI systems requires more than good intentions—it demands a structured approach that transforms principles into actionable practices. Fairness, efficacy, transparency, and accountability are the four pillars of responsible AI, but translating these concepts into real-world processes and controls can be challenging. Without a clear governance playbook, enterprises risk exposing themselves to bias, operational inefficiencies, and regulatory scrutiny.
In this presentation, Alayna Kennedy, Manager of AI Governance at Mastercard, will share a comprehensive playbook for implementing responsible AI practices. You’ll learn how to integrate fairness, efficacy, transparency, and accountability into your AI development lifecycle, establish robust governance controls, and apply best practices to build trustworthy AI systems. This session is designed for AI leaders looking to foster a culture of responsibility and compliance while driving innovation.
Presenter Bio
Alayna runs the AI governance team at Mastercard, where she is responsible for providing guidance to all the creators of AI products. Previously, she was AI Ethics Board Education Manager at IBM, having moved into ethics from being a machine learning researcher.