Understanding Personalized Accessibility through Teachable AI: Designing and Evaluating Find My Things for People who are Blind or Low Vision
Cecily Morrison, Martin Grayson, Rita Faia Marques, Daniela Massiceti, Camilla Longden, Luguang Wen, Edward Cutrell
Abstract
The opportunity for artificial intelligence, or AI, to enable accessibility is rapidly growing, but widely impactful applications can be challenging to build given the diversity of user need within and across disability communities. Teachable AI systems give users with disabilities a way to leverage the power of AI to personalize applications for their own specific needs, as long as the effort of providing examples is balanced with the benefit of the personalization received. As an example, this paper presents the design and evaluation of Find My Things, an end-to-end application that can be taught by people who are blind or low vision to find their personal things. Through synthesis of the design process, this paper offers design considerations for the teaching loop that is so critical to realizing the power of teachable AI for accessibility.