Fairness Issues in AI Systems that Augment Sensory Abilities

TL;DR

This paper discusses unique fairness challenges in AI systems that augment sensory abilities, focusing on accessibility, ethical, and privacy issues, which are less prominent in other AI applications.

Contribution

It highlights specific fairness issues in sensory augmentation AI systems, emphasizing challenges in data accessibility, ethical decision-making, and privacy considerations.

Findings

Identifies accessibility challenges in data and models.

Raises ethical concerns in conveying sensory information.

Highlights privacy risks for users and others.

Abstract

Systems that augment sensory abilities are increasingly employing AI and machine learning (ML) approaches, with applications ranging from object recognition and scene description tools for blind users to sound awareness tools for d/Deaf users. However, unlike many other AI-enabled technologies, these systems provide information that is already available to non-disabled people. In this paper, we discuss unique AI fairness challenges that arise in this context, including accessibility issues with data and models, ethical implications in deciding what sensory information to convey to the user, and privacy concerns both for the primary user and for others.