AI research and design that prioritizes human thriving.
We study how AI systems reason, persuade, inherit cultural assumptions, and act where human judgment matters. As an independent 501(c)(3) nonprofit, we connect technical evaluation with expertise in language, culture, policy, and history.
Current work. Katherine Elkins and Jon Chun lead the Modern Language Association team in NIST CAISI and the Schmidt Sciences HAVI Archival Intelligence initiative.
We test how models handle rules, negation, persuasion, and ethical judgment; compare governance regimes; and study oversight for autonomous systems. The Wisdom Test asks which religious and philosophical traditions frontier models reproduce or leave out.
We form focused teams around questions that require technical researchers, humanists, social scientists, policy scholars, and cultural institutions to work together.
We publish methods, code, and research that others can inspect and extend, from model-evaluation protocols to tools for narrative analysis and endangered archives.