Introduction to Auditing AI Systems

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Ayodele Odubela

1:19:10

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01 - Introduction

01 - Welcome to the new world of AI audits.mp4

00:40

02 - 1. New Paradigm of AI Audits

01 - What is an AI audit.mp4

04:26

02 - How are audits used.mp4

04:08

03 - The state of AI legislation.mp4

03:10

04 - Ethics of scoring and classifying humans.mp4

04:04

03 - 2. Why Audit AI Systems

01 - AI audit limitations and opportunities.mp4

03:33

02 - Development workflows.mp4

03:56

03 - AI performance.mp4

03:47

04 - Statistical parity.mp4

02:33

04 - 3. Data for AI Audits

01 - Data for auditing AI.mp4

03:20

02 - Sources of bias in data.mp4

03:19

03 - Types of bias and data sampling methods.mp4

04:18

05 - 4. Principles for AI Audits

01 - Why explainability matters.mp4

03:43

02 - Levels of transparency.mp4

03:54

03 - Responsible AI principles Compliance.mp4

04:28

04 - Preparing for AI regulation.mp4

03:34

06 - 5. Model Audits

01 - Types of model audits.mp4

02:15

02 - Stages of a model audit.mp4

02:56

03 - Model audit Home loans.mp4

02:54

04 - Auditing training data.mp4

03:17

05 - Audit outcomes Explainability statements.mp4

02:20

06 - Continuous audits.mp4

02:26

07 - Conclusion

01 - Generative AI.mp4

05:33

02 - Next steps.mp4

00:36

Description

AI regulation is here, so you may be wondering how to adapt. And if you’re an enterprise organization, startup, or AI practitioner, you probably already know that there are very few existing training resources for technical teams. In this course, instructor Ayodele Odubela gives you a hands-on overview of how to assess AI for bias and discrimination to create fairer AI systems.

Explore the fundamentals of the latest regulations governing the use of AI technology, as well as how to navigate the different phases of AI audits in technical terms. Learn how federal discrimination laws can impact AI systems, how to audit both high- and low-risk AI, and how to collect, develop, or purchase benchmark data for auditing and policy review. Ayodele shows you the basics of calculating model fairness and what principles to prioritize and why, including explainability, transparency, compliance, and documentation. Upon completing this course, you’ll be more aware of how to use generative AI tools to mitigate algorithmic bias.

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Artificial Intelligence

Accounting

Financial Accounting

Ayodele Odubela

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Linkedin Learning

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.