AI Fairness for People with Disabilities: Point of View
We consider how fair treatment in society for people with disabilities might be impacted by the rise in the use of artificial intelligence, and especially machine learning methods. We argue that fairness for people with disabilities is different to fairness for other protected attributes such as age, gender or race. One major difference is the extreme diversity of ways disabilities manifest, and people adapt. Secondly, disability information is highly sensitive and not always shared, precisely because of the potential for discrimination. Given these differences, we explore definitions of fairness and how well they work in the disability space. Finally, we suggest ways of approaching fairness for people with disabilities in AI applications.
Focus: AI and Disability/Outliers
Source: IBM
Readability: Intermediate
Type: Website Article
Open Source: No
External URL: https://arxiv.org/abs/1811.10670
Keywords: N/A
Learn Tags: Bias Data Collection/Data Set Design/Methods Disability Ethics Fairness Inclusive Practice Small Data
Summary: A discussion of the challenges persons with disabilities face with current AI systems and the approaches that need to be adopted to ensure fairness in AI development.