Mostly good information. but cannot get on board with the Inverse Ratio Recruiting method proposed. There are better ways to solve this problem than to change the algorithm to promote 70% black, 15% Latino,10% Asian, and 5% White. This in itself SKUS the data. Absolutely not!!!! This promotes Bias. Unbelievable that this would even be suggested.
Foundations of Responsible AI
With Ayodele Odubela
Liked by 637 users
Duration: 2h 30m
Skill level: Intermediate
Released: 8/2/2022
Course details
How well do you understand the issues around algorithmic bias and unfairness? In this course, data scientist and AI ethicist Ayodele Odubela teaches you the principles of responsible AI, as well as the frameworks necessary to apply RAI techniques in AI systems. Ayodele explains modern AI development and problems in machine learning (ML) that differ from software engineering. She discusses big data and where it comes from, then covers several important points of data awareness and literacy. Ayodele goes over ethical frameworks, consequence scanning, fairness, accountability, and more. She also explains fairness-related harms, why they arise, why they matter, and what you can to avoid or mitigate them. Plus, Ayodele offers a detailed description of human rights as related to AI.
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Meet the instructor
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Daimeian Underwood
Daimeian Underwood
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Contents
What’s included
- Practice while you learn 2 exercise files
- Test your knowledge 8 quizzes
- Learn on the go Access on tablet and phone
- Stay up to date Continuing Education Units
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