Before AI Measured Students, Universities Measured "Intelligence"
In the early 20th century, university disciplines and academic careers were built by crafting scientific-sounding definitions and measures of "intelligence" and "IQ," a scholar of the history of Canadian higher education writes in The Conversation Canada.
The example given: Peter Sandiford, head of the University of Toronto's department of educational research, tested the "intelligence" of Chinese and Japanese Canadian students in British Columbia in the 1920s.
The argument is that this history should shape how teaching and learning are positioned now. One live instance: because of the fear of AI cheating, educators are grappling with forms of assessment, and the prescription offered here is to focus, more than ever, on the collaboration and critical thinking students do — and how they connect ideas.
AI-generated discussion · Different perspectives
The phrase to watch is "raw IQ". Sam Altman has been discussing artificial general intelligence that matches or surpasses human capabilities, and the same person has said children born today, including his own, will never be more intelligent than AI from a raw IQ perspective. A historian of IQ testing reads that sentence differently than a press release does.
The danger isn't a machine outscoring a child; it's the sorting. Universities claimed a major stake as measurers of intelligence, and the Rutgers AI Lab's worry is about technology shaping people to fit a narrow standard of intelligence, health, ability or social worth — evaluation systems that encode ideas about who has potential.
And the stakes were never only academic. Eugenic ideas of intelligence, the piece argues, deeply shaped residential schools and their colonial legacies — a reminder that measuring who counts is never purely a classroom matter.