Artificial Intelligence Fairness in the Context of Accessibility Research on Intelligent Systems for People Who Are Deaf or Hard of Hearing

We discuss issues of Artificial Intelligence (AI) fairness for people with disabilities, with examples drawn from our research on HCI for AI-based systems for people who are Deaf or Hard of Hearing (DHH). In particular, we discuss the need for inclusion of data from people with disabilities in training sets, the lack of interpretability of AI systems, ethical responsibilities of access technology researchers and companies, the need for appropriate evaluation metrics for AI-based access technologies (to determine if they are ready to be deployed and if they can be trusted by users), and the ways in which AI systems influence human behavior and influence the set of abilities needed by users to successfully interact with computing systems

Focus: AI and Disability/Outliers

Source: ACM ASSETS 2019

Redability: Expert

Type: PDF Article

Open Source: Yes

SharePoint URL: https://ocaduniversity.sharepoint.com/teams/Team_WeCount/Shared%20Documents/Resources%20and%20Tools/Literature%20(curated)/Artificial%20Intelligence%20Fairness%20in%20the%20Context%20of%20Accessibility%20Research%20on%20Intelligent%20Systems%20for%20People%20who%20are%20Deaf%20or%20Hard%20of%20Hearing.pdf

Keywords: Artificial intelligence, fairness, people with disabilities, people who are Deaf or Hard of Hearing (DHH).

Learn Tags: Bias Disability Ethics Fairness Inclusive Practice

Summary: This paper covers some emerging issues in AI fairness for people with disabilities, both in the context of AI mainstream technologies and in new AI-based access technologies for people with disabilities.