"The issue is not that the column takes AI seriously; higher education should take AI seriously. The issue is that it mistakes machine-generated prescription for human judgment and acceleration for destiny."
"Numeric specificity lends such claims borrowed authority. At the point where the argument most needs source criticism and methodological transparency, readers are asked to accept machine-generated figures as if they were settled evidence."
"A benchmark may inform debate; it cannot determine what institutions owe students, what labor should remain human or what losses are acceptable in the name of efficiency."
The column critiques the reliance on AI-generated analysis and recommendations for higher education curricula. It argues that using AI to define educational needs constitutes epistemic outsourcing, undermining human judgment. The piece highlights the lack of source transparency in AI-generated data and warns against accepting machine-generated figures as evidence. It emphasizes that benchmarks like GDPval have limitations and should not dictate educational priorities or the human aspects of labor, especially in light of automation's unequal impacts.
Read at Inside Higher Ed | Higher Education News, Events and Jobs
Unable to calculate read time
Collection
[
|
...
]