This OpenAI Forum session focused on how AI is accelerating research across disciplines—especially in the humanities and social sciences, where it’s enabling new ways to test theories, analyze culture, and train students in computational methods. The program framed AI as a powerful scientific tool that can compress long research timelines by handling tasks that may require deep, sustained reasoning and large-scale synthesis. Katherine Elkins shared “applied humanities” projects that model emotional arcs in novels, compare how translations reshape narrative patterns, and surface meaningful peaks and shifts that often align with what close-reading tends to notice. She also showed how students are using AI to explore cultural datasets—ranging from storytelling structures and social media dynamics to bias investigations in image generation, legislative text mining, and network/knowledge-graph analysis. Marco Uytiepo described how deep learning accelerates nanoscale brain-imaging analysis, turning months or years of manual reconstruction into days and helping researchers study circuit features linked to memory. Leonardo Impett argued that modern computer vision models don’t just analyze images—they embody a “machine visual culture,” and researchers can use art-historical methods to study both visual media and the cultural lens of the algorithms themselves. The event ended with a live Q&A where participants discussed responsible use with domain experts, creative uses of generative tools in storytelling, examples where AI changes research direction (not just speed), translation effects, long-term implications for analyzing AI-generated imagery, global archival preservation, and practical first steps for bringing AI methods into labs and classrooms.

The session explored how AI is reshaping education, beginning with OpenAI’s Olivia Pavco-Giaccia outlining why teaching and learning sit at the core of the company’s mission and how student adoption—now more than 40% of ChatGPT users worldwide—has accelerated AI’s integration into campuses, leading to large-scale deployments such as ChatGPT EDU across the CSU system and emerging research partnerships aimed at improving learning outcomes. She emphasized moving beyond fears of cheating to unlock personalized learning support, including early progress with Study Mode. Columbia University’s Moran Cerf, then connected AI to cutting-edge neuroscience and behavioral research, detailing how AI literacy is now essential for executives and students alike, and sharing striking findings from brain-interface studies that reveal how humans make decisions, process memories, and respond to engagement—insights he believes could transform pedagogy and human–AI collaboration. Miami Dade College’s Beth Muturi followed with a pragmatic model for “humanizing AI,” showing how community-embedded capstone projects allow students to build real AI solutions for local organizations, expanding opportunity and practical skill development. UC Berkeley’s Greg Neimeyer proposed a holistic AI pedagogy organized around three modes—minus AI, plus AI, and times AI—arguing that education must balance embodied human experience, critical engagement with AI, and transformational uses of intelligent systems to sustain meaning, collaboration, and truth in an AI-saturated era. Finally, UCLA’s Tina Austin presented her “Autumn Bloom’s” framework, a recursive, discipline-flexible alternative to Bloom’s taxonomy that shifts assessment away from grading AI-generated output and toward evaluating students’ comparative reasoning, critique, and metacognitive understanding, offering a path for assignments that integrate, challenge, or intentionally exclude AI depending on pedagogical need.

The session on leadership-driven AI initiatives showcased how universities and partners are weaving AI into research, education, operations, and culture. Brown University highlighted its broad academic footprint, flagship institutes, and an associate provost for AI leading efforts that range from the Human RGNOME Project’s massive RNA-mapping work for new therapies, to governance work on the AI Bill of Rights, to biosecurity collaborations with the U.S. government amid fears of AI-enabled biological threats. Brown is also grappling with how to integrate AI into teaching—acknowledging that students are ahead of faculty, redesigning assignments with the assumption that AI will be used, and emphasizing fundamental knowledge and in-class, no-AI assessments—while deploying AI across operations from communications and HR to investment analysis and workflow efficiency. Tim Kashani then traced his path from rock guitarist and filmmaker to AI educator, explaining how he uses narrative, comedy, and experiential learning to help students and artists experiment with AI as a creative and ethical tool, culminating in projects like Earth 3.0 and new programs such as Story Accelerator that support uplifting, impact-driven storytelling with AI in partnership with philanthropies. Finally, Siobahn Day Grady described how North Carolina Central University, an HBCU, is operationalizing AI through its new Institute for Artificial Intelligence and Emerging Research, funded by Google.org and housed in the provost’s office, with the mantra “AI is for everyone.” She outlined efforts to change campus culture via AI literacy workshops, new academic programs, seed grants, and practitioner cohorts for students, faculty, and staff; to integrate AI into operations and state-level policy work; and to ensure that both the campus and surrounding community—including older adults and those on the wrong side of the digital divide—gain AI fluency and are not left behind as AI transforms every sector.

Siya from OpenAI and Angela Virtu from American University's Kogod School of Business present a detailed overview of what it means to become an "AI-native university." They discuss the rollout of ChatGPT EDU, strategic AI curriculum development, cultural shifts in higher education, and how AI is transforming teaching, learning, and career readiness. Angela shares American University’s phased approach—from pilot projects to institutional integration and strategic transformation—with a focus on community building, ethical AI use, and workforce alignment.