NSF2020: EAGER: Collaborative Research: Enhancing Employment for Neurodiverse Individuals through Next-Generation, AI-Enabled Assessments of Visuospatial Cognition

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Each year in the United States, approximately 70,000 new adults on the autism spectrum will seek employment. At the same time, employers in technology, finance, healthcare, and many other critical job sectors seek highly skilled and highly trained individuals to fill specialized positions. With support from the DRK-12 Program in the Division of Research on Learning and the NSF 2026 Fund Program in the Office of Integrated Activities, this research will investigate new tools and methods for matching individual job-seekers on the autism spectrum to employment opportunities that leverage their unique cognitive skills, with a focus on visuospatial cognitive skills. Numerous jobs require strong visuospatial cognitive skills, such as visual inspection and quality control, process monitoring, document review, surveillance, software testing, and data visualization, to name a few. Many people on the autism spectrum show strengths in visuospatial cognitive skills, but these strengths are not fully understood, including how they differ from person to person and how they map onto workplace-relevant capabilities. Understanding visuospatial cognitive skills in individuals on the autism spectrum or other neurodiverse conditions has high potential impact for enhancing the neurodiversity of the workforce by enabling more effective programs for the recruitment, selection, and retention of such candidates in the public and private sectors. This NSF2026 EAGER project enriches the NSF2026 Idea Machine winning entry Harnessing the Human Diversity of Mind. It seeks to develop and evaluate integrated, AI-enabled technologies for measuring a person’s visuospatial cognitive skills in new ways and then using these measurements to predict performance on workplace-relevant tasks. The research conducted during this two-year project will include conducting a large pilot study with individuals on the autism spectrum and neurotypical individuals, in which participants will be given several visuospatial tests, and detailed data about their actions will be recorded using sensors such as eye trackers and cameras. Then, data mining and machine learning techniques will be used to extract meaningful patterns from these rich streams of behavioral data, and analyses will be conducted to examine how these patterns in foundational behaviors map onto individual skills and interests in realistic, workplace-relevant activities. This research will also gather and analyze detailed feedback from industry partners to identify specific job types and sectors that would benefit from recruiting employees who are strong in visuospatial cognitive skills. In addition, this project will involve neurodiverse students and staff in many of its activities, in particular by involving graduate trainees supported by the NSF Research Traineeship in Neurodiversity Inspired Science & Engineering (NISE) and by leveraging the skills of neurodiverse interns at the Frist Center for Autism & Innovation at Vanderbilt University's School of Engineering.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.