This week’s post opens with two projects from our own aiX lab — on treating LLMs as objects of statistical inquiry, and on designing reliable agentic AI workflows — alongside the usual roundup from across higher education.
This week’s post centers on three threads: the durability of learning — whether learners’ gains through AI use survive once the tool is removed; assessment as the load-bearing response to that problem; and the redefinition of entry-level work as AI skills become a hiring baseline.
This week’s post examines two converging disruptions: accountability when AI mediates consequential decisions, and AI’s growing strain on the knowledge and talent ecosystems — peer review, open-source software — that it was built on.
This week’s post examines the widening gap between near-universal AI adoption and institutional readiness — from Microsoft and Gallup survey data to the platform competition at ISTE 2026.
This post tracks converging empirical evidence on AI and learning outcomes, SUNY’s systemwide AI policy across all 64 campuses, and the fast-growing market for detection-evasion tools.
Welcome to the inaugural issue of aiX Weekly — a curated digest of research, institutional moves, and debate at the intersection of AI and higher education.
An interactive timeline tracing pivotal moments in AI and higher education — from ChatGPT’s launch through exam disruptions, campus tensions, workforce shifts, and the emergence of institutional AI strategies.
