AI Ethics: Disability-Centered Frameworks
49mIntermediate2023-12-21
Authors
Yonah Welker
Course details
Building disability- and neurodiversity-centered AI systems helps not only the over one billion people with impairments globally, but everyone else, as well. In this course, technology explorer and public voice for the algorithmic spectrum Yonah Welker guides you through disability and AI bias, as well as systems and risks. Learn about disability-centered data, models, knowledge frameworks, and policies. Plus, explore positive ways forward.
Skills covered
Responsible AIArtificial Intelligence (AI)One-Off
Concepts
0. Introduction
- 01 - Disability-centered systems and algorithms
- 02 - What you should know
1. Disability and AI Bias
- 03 - How AI algorithms support people with disabilities
- 04 - Why disabilities can be challenging for algorithms
- 05 - How systems can be inaccurate
- 06 - What factors lead to errors
- 07 - Assess your problem and objectives
2. Understanding Systems and Risks
- 08 - AI system categories
- 09 - AI regulation and protections
- 10 - How risk categories are unique for people with disabilities
- 11 - Assess your systems, categories, and risks
3. Disability-Centered Data
- 12 - How data is used in AI systems
- 13 - How bias can enter data
- 14 - Assess your data
4. Disability-Centered Models
- 15 - How AI models impact people with disabilities
- 16 - How bias can affect AI models
- 17 - Assess your AI models
5. Disability-Centered Knowledge Frameworks and Policies
- 18 - Adopting ethical frameworks, guidelines, and memorandums
- 19 - Disability-centered framework parameters
- 20 - Additional tools and frameworks
- 21 - Assess resources and memorandums
Conclusion
- 22 - A way forward