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According to the World Health Organization, more than one billion people worldwide have disabilities. The field of disability studies defines disability through a social lens, which considers people disabled to the extent that society creates accessibility barriers.
A Center for Neural Data Science Seminar Series
A Center for Neural Data Science Seminar Series
This session covers the foundational knowledge of GPUs, including their architecture, functionality, and applications in computing. It provides an introduction to GPU computing through the lens of the Marlowe SuperPod and prepares learners for advanced topics such as GPU-accelerated data science and machine learning.
Location: CoDa W401
This session covers the foundational knowledge of GPUs, including their architecture, functionality, and applications in computing. It provides an introduction to GPU computing through the lens of the Marlowe SuperPod and prepares learners for advanced topics such as GPU-accelerated data science and machine learning.
Location: CoDa W401
For example, computer vision might give people who are blind a better sense of the visual world, speech recognition and translation technologies might offer real-time captioning for people who are hard of hearing, and new robotic systems might augment the capabilities of people with mobility restrictions. Considering the needs of users with disabilities can help technologists identify high-impact challenges whose solutions can advance the state of AI for all users. At the same time, ethical challenges such as inclusion, bias, privacy, error, expectation setting, simulated data, and social acceptability must be considered. In this lecture, I will define these seven challenges, provide examples of how they relate to AI for Accessibility technologies, and discuss future considerations in this space.
