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  <title><![CDATA[MS Defense by Shujian Xu]]></title>
  <body><![CDATA[<p><strong>THE SCHOOL OF INDUSTRIAL DESIGN</strong> </p><p><strong>GEORGIA INSTITUTE OF TECHNOLOGY</strong> </p><p><strong>Under the provisions of the regulations for the degree</strong> </p><p>&nbsp;</p><p><strong>MASTER OF INDUSTRIAL DESIGN</strong> </p><p><strong>on</strong></p><p><strong>Wednesday, April 8, 2026</strong></p><p><strong>12:30 p.m.&nbsp;– 1:30 p.m. EST</strong> </p><p><strong>West Architecture 155</strong></p><p><strong>Teams Link: &nbsp;</strong><a href="https://teams.microsoft.com/meet/28959647861551?p=6HwF8MBfHQv4LLu7fK" target="_blank" title="https://teams.microsoft.com/meet/28959647861551?p=6HwF8MBfHQv4LLu7fK">https://teams.microsoft.com/meet/28959647861551?p=6HwF8MBfHQv4LLu7fK</a></p><p>Meeting ID: 289 596 478 615 51</p><p>Passcode: ye9CD3cr</p><p><strong>Shujian&nbsp;Xu</strong></p><p>will present a thesis defense entitled<strong>, </strong></p><p><strong>"Exploring the Role of AI in Accessible Design: Opportunities, Limitations, and Workflow Integration"</strong></p><p>&nbsp;</p><p><strong>  Advisor: </strong></p><p>Dr. Leila Aflatoony, Georgia Tech School of Industrial Design </p><p><strong>Committee: &nbsp;</strong></p><p>Dr. Leandro Miletto Tonetto, Georgia Tech School of Industrial Design</p><p>Dr. Morris Huang, University of Colorado Denver</p><p>&nbsp;</p><p><strong>Faculty and students are invited to attend this presentation. </strong></p><p>&nbsp;</p><p><strong>Abstract &nbsp;</strong></p><p><br>Artificial Intelligence (AI) tools are increasingly being integrated into design workflows, supporting different stages of the design process. However, their role in accessible design remains underexplored – a domain where design decisions require deep engagement with diverse user needs, lived experiences, and contextual conditions, as well as a higher standard of reliability and safety.</p><p>This study investigates how AI is currently used in accessible design processes, the types of support it provides, and the challenges and gaps that emerge from its use. Through semi-structured interviews with 17 expert designers and researchers, the study examines AI’s role within real-world workflows, as well as designers’ perspectives on authorship, trust, control, and evaluation.</p><p>A thematic analysis of the interviews reveals that AI functions as a multi-layered form of support across accessible design&nbsp;activities, while also reshaping the role of human judgment and responsibility in the process. At the same time, its use introduces critical gaps and risks in accessibility contexts, and highlights the need for better support of interaction, collaboration, workflows, and trust. Based on these insights, this thesis proposes design guidelines for future AI tools to better support accessible design, addressing current limitations while enabling more responsible, context-aware, and empowering design practices.</p>]]></body>
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