Research
Applied research and education.
SUPPORTING DISCIPLINE — NOT A STANDALONE COMMERCIAL PRODUCT
Investigations, evaluation, education, collaboration, and capability development that inform PAII’s applied work.
Applied Research, Education & Real-World AI
PAII is working with William & Mary faculty and student organizations to develop an applied AI internship and experiential learning opportunities grounded in real organizational problems.
William & Mary’s School of Computing, Data Sciences & Physics, the university’s first new school in more than 50 years, brings together computer science, data science, applied science, and physics in an interdisciplinary academic environment focused on research, innovation, and real-world readiness.
Within that school, William & Mary has launched a new Applied AI major designed to help students apply AI responsibly to real-world challenges across disciplines and professional settings.
The direction of that program closely aligns with PAII’s own work: applying AI to genuine organizational problems, integrating AI into useful workflows, evaluating outputs and limitations, preserving human judgment, and building systems that improve the quality of human decisions.
PAII provides a practical environment where students can help design, test, evaluate, and improve AI-enabled systems intended to organize complex information, reduce unnecessary cognitive load, strengthen workflow reliability, and support better human decisions.
Human judgment remains in control of consequential decisions.
Investigations and institutional memory
The Book of PAII is PAII’s internal institutional record: founding case studies, incidents and the lessons drawn from them, and validated workflow improvements entered with named credit to whoever found them. It is how PAII’s methods change when the evidence says they should. It is maintained internally.
Education and collaboration
PAII welcomes conversations with faculty, student organizations and research collaborators about applied AI problems grounded in real organizational work.
Propose a collaboration