Developing advanced user-focused interfaces and design methods that are shaping the future of technology.
Principal Investigator(s): J. Bern Jordan Hernisa Kacorri Amanda Lazar
Funder: HHS / ACL / National Institute on Disability, Independent Living, and Rehabilitation Research Other
Research Areas: Accessibility and Inclusive Design > Data Privacy and Sociotechnical Cybersecurity > Human-Computer Interaction
Exploring and developing strategies to individualize generative artificial intelligence (AI) systems to make them provide better results tailored to each individual with a disability (starting with AI systems for visual question answering for blind people); identifying and more deeply understanding the failures in technology use by people who are older and developing design strategies to allow more seniors to understand products out of the box -- especially those technologies that are critical to independent living and engagement.
Research Areas: Accessibility and Inclusive Design > Future of Work > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval
Principal Investigator(s): Wayne G. Lutters
Funder: New York University Other
Research Areas: Future of Work > Human-Computer Interaction > Library and Information Science
The Democratizing Data project supports federal agencies in understanding how their data assets are being used. Novel machine learning algorithms interrogate over 90 million publications to identify data usage, which is presented via a search and discovery platform with three interaction styles: interactive dashboards, Jupyter Notebooks, or direct API.
Eight seed grants from UMD's new TRAILS institute aim to diversify stakeholders in developing and governing AI, while using the emerging technology for societal good. Illustration courtesy of Maryland Today via iStock
Photo courtesy of Insight Into Diversity magazine
From left, Drs. Amanda Lazar, J. Bern Jordan, and Hernisa Kacorri. Photo by Craig Taylor.