"But focusing so much on cheating misses the larger transformation already underway, one that extends far beyond student misconduct and even the classroom. Universities are adopting AI across many areas of institutional life. Some uses are largely invisible, like systems that help allocate resources, flag "at-risk" students, optimize course scheduling, or automate routine administrative decisions. Other uses are more noticeable."
"People may use AI to cheat or skip out on work assignments. But the many uses of AI in higher education, and the changes they portend, beg a much deeper question: As machines become more capable of doing the labor of research and learning, what happens to higher education? They risk hollowing out the ecosystem of learning and mentorship upon which these institutions are built, and on which they depend."
Public debate about AI in higher education has centered on cheating, but AI adoption reaches far beyond academic misconduct. Universities are adopting AI across many institutional functions, from invisible systems that allocate resources, flag "at-risk" students, optimize course scheduling, and automate routine administrative decisions, to visible uses where students use AI to summarize and study, instructors build assignments and syllabuses, and researchers use AI to write code, scan literature, and compress hours of tedious work into minutes. As AI becomes more autonomous and better at knowledge work, ethical stakes rise and the technologies risk hollowing out learning and mentorship, raising questions about the university's purpose.
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