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Wednesday, December 1 • 12:30pm - 1:30pm
Emerging AI Technologies for Inclusion of Underserved Populations

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The development of AI models has often been siloed and associated with lack of representative data samples across different social classes and cultures. Conventional deep learning models often do not perform well when there is such undersampling of data. This can impact marginalized populations as the data curation is not representative or inclusive of all groups. In this panel, we discuss how curating new datasets and corpora representing the Hispanic population, can contribute to inclusive AI systems that mitigates biases towards underserved populations and move towards democratizing AI. The panel group will discuss this across different case studies in: long-term health tracking, disease classification in dementia and its subtypes, and population diversity in biological models, and cognitive behavioral changes from wearable sensors across diverse demographics.

Chair: Dhireesha Kudithipudi (UT San Antonio)

Mohamad Habes (UT Health, San Antonio)
Dhireesha Kudithipudi (UT San Antonio)
Paula Kay Shireman (UT Health, San Antonio)
Amina Qutub (UT San Antonio)

avatar for Dhireesha Kudithipudi

Dhireesha Kudithipudi

University of Texas at San Antonio


Amina Qutub

UT San Antonio
avatar for Mohamad Habes

Mohamad Habes

UT Health, San Antonio

Paula Kay Shireman

UT Health, San Antonio

Wednesday December 1, 2021 12:30pm - 1:30pm PST
Virtual Zoom link coming soon!