Episode 228 - AI Ethics: How Developers Can Build Fairer Systems

Are you building AI models and systems? Then you need to understand AI ethics! In this episode of Two Voice Devs, Allen Firstenberg welcomes Parul, a Senior Production Engineer at Meta, to dive deep into the world of AI ethics. Learn why fairness and bias are critical considerations for developers, and discover practical techniques to mitigate bias in your AI systems.

Parul shares her experiences and passion for AI ethics, detailing how biases in training data and system design can lead to unfair or even harmful outcomes. This episode provides concrete examples, actionable advice, and valuable resources for developers who want to build more ethical and equitable AI.

More Info:

* Fairlearn: https://fairlearn.org/

* AIF360: https://aif360.readthedocs.io/en/stable/

* what-if tool: https://pair-code.github.io/what-if-tool/

Timestamps:

00:00:00 Introduction

00:00:20 Guest Introduction: Parul, Meta

00:02:22 What is AI Ethics?

00:06:13 Why is AI Ethics Important?

00:08:15 AI Systems vs. AI Models

00:09:52 Examples of Bias in AI Systems

00:12:23 Minimizing Biases: Developer Responsibility

00:14:53 Tips for Minimizing Unfairness and Biases

00:19:40 Fairness Constraints: Demographic Parity

00:23:17 The Bigger Picture: Roles & Responsibilities

00:29:23 Monitoring: Bias Benchmarks

00:32:00 Open Source Frameworks for AI Ethics

00:34:02 Call to Action & Closing

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