Video description
Join us for an event focused on the many aspects of designing, deploying, and maintaining responsible AI. Event chair and responsible AI expert Rumman Chowdhury offers overarching context, stitching together shorter tech talks and conversations with industry leaders.
What you’ll learn and how you can apply it
- Discover what responsible AI includes (and what it doesn’t)
- See what responsible AI looks like in action, from data to deployment to debugging
- Learn how to debug your ML model
- Explore real-world applications of responsible AI
- Understand what industry leaders think about when they think about responsibility
This course is for you because…
- You're a machine learning engineer or data scientist interested in responsible AI.
- You’re engaged in conversations about ethics and AI.
- You're wondering how to improve your own AI and machine learning.
- You're responsible for implementing fair or ethical AI practices in your role or project and looking for hands-on examples.
Recommended follow-up:
- Read Responsible Machine Learning (report)
- Read AI and the Law (report)
- Read Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (book)
Table of contents
- Rumman Chowdhury: Keynote—Responsible AI in Practice
- Aileen Nielsen: What’s Still Missing from the Responsible AI Movement
- Triveni Gandhi: So You Built a Fair Model…Now What? (Sponsored by Dataiku)
- Patrick Hall: Real-World Strategies for Model Debugging
- Joshua Williams: Lightning Talk—A Bayesian Model of Cash Bail Decisions
- Kristian Lum: Lightning Talk—Algorithmic Fairness: Choices, Assumptions, and Definitions
- Marcin Detyniecki: Can AI Design a Fairer Future? (Sponsored by AXA)
- Joaquin Quiñonero Candela and Rumman Chowdhury: Building Responsible ML Solutions in Social Media
Product information
- Title: AI Superstream: Responsible AI
- Author(s):
- Release date: June 2021
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 0636920586494
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