All tagged machine learning
ACADIA Conference, 2022. Vanguard Paper Award Runner-Up
A key technological weakness of artificial intelligence (AI) is adversarial images, a constructed form of image-noise added to an image that can manipulate machine learning algorithms but is imperceptible to humans. Over the past years, we developed Adversarial Architecture: A scalable systems approach to design adversarial surfaces, for physical objects, to manipulate machine learning algorithms.
Supersense is a mobile assistive technology application for visually impaired people & blind (VI&B) Mobile artificial intelligence systems present a significant opportunity for improving the lives of more than 300 million VI&B by reducing the challenges in their everyday life such as navigation, orientation and mobility (O&M), reading, and more. Accessibility-enabled applications often yield poor and overwhelming experiences for VI&B who has different needs and drastically different ways of interacting with mobile technology. In making Supersense, we adopted a user-centered design process and introduced several guidelines for designing accessibility-first applications. The projectis funded by the MIT DesignX program, the National Science Foundation, and the Veteran Affairs. It has reached more than one hundred thousand blind users globally.
