The Ugly History of IQ Testing Matters for AI’s Future

OpenAI CEO Sam Altman has recently been discussing “artificial general intelligence” that matches or surpasses human capabilities. This is from the same person who has said children born today (including his own) will “never be more intelligent than AI, from a ‘raw IQ’” (intelligence quotient) perspective.

United States President Donald Trump has also recently mused about who is and who is not “high IQ.”

As a scholar rooted in the history of Canadian higher education and its intersections with rhetoric around disability and race, every time I hear the word “intelligence,” including as “IQ,” I get jumpy.

“Intelligence” clearly has a high-stakes and worrisome future, but also a dark history.

To figure out what AI might be replacing, we need to better understand intelligence as a historically situated idea — and a dangerous one — rather than as some sort of biological fact.

For universities, this reflection matters as institutions confront questions about how their responses to AI align with their missions.

‘Intelligence’ and eugenics

In the early 20th century, universities, university disciplines and academic careers were built by crafting scientific-sounding definitions and measures of “intelligence” and “IQ.”

As historian Gerald Thompson notes, the creator and head of the University of Toronto’s department of educational research, Peter Sandiford, tested the “intelligence” of Chinese and Japanese Canadian students in British Columbia in the 1920s.

This was done under the direction of the first full professor of education at the University of British Columbia, George Moir Weir.

The research, writes Thompson, “was meant to confirm” long-standing racist notions of Anglo-white superiority and Asian inferiority.

As historians like Angus McLaren have demonstrated, such projects were the work of eugenics. These defined intelligence as a genetic and inheritable trait that could be measured but not necessarily easily developed within individuals, and assumed a pseudo-scientific racialized genetic hierarchy.

Eugenic ideas of intelligence shaped residential schools

Researchers involved in such projects ranked Canadians, and these rankings determined educational and social futures. Eugenic ideas of intelligence deeply shaped residential schools and their colonial legacies.

Sociologist Alexandra Giancarlo has documented how in the 1930s, Kenneth E. Kidd, who went on to found the “Indian-Eskimo Studies” program at Trent University, administered a series of IQ tests at the Mohawk Institute, a residential school in southern Ontario.

This led to two published books that advanced racist ideas around intelligence and informed Department of Indian Affairs policy not just for children at the Mohawk Institute, but at residential schools across the country.

Some of the researchers — such as Weir, Kidd and Sandiford, who contributed to popularizing these ideas — went on to build university programs and disciplines.

The more general result was that universities and academics claimed a major stake as measurers of intelligence. This coincided with an increased reliance on testing, exams and grading at Canadian universities and academic rankings.

Now, because of the fear of AI cheating, educators are grappling with forms of assessment. In some cases, this means more hand-written or oral exams, which raise concerns about ableism.

In the past, measuring intelligence was a way to exclude entire groups of people from opportunity. How will intelligence be used and misused going forward?

Teaching, learning and AI

These histories influence how we talk about artificial intelligence, and should also shape how we position teaching and learning today.

The intersection of AI and eugenics is beginning to be studied more deeply, for instance by the Rutgers AI Lab. The lab notes this technology may be “shaping people to fit a narrow standard of intelligence, health, ability or social worth” often “through data, algorithms, or evaluation systems that encode biased ideas about who has potential and who does not.”

Likewise, the impacts of AI usage on learning and “de-skilling” have been extensively explored, with some people calling de-skilling “enfeeblement,” perhaps unaware of the eugenic history of this wording: “feeble-mindedness” was a pseudoscientific, eugenic term.

As disability studies scholar Rua Williams argues, “through ignorance of the historical context,” the current project of artificial intelligence may be “replicating historical and political projects that devalue human beings on the basis of abstract or fabricated concepts” of intelligence.

Others express concern that a lack of regulation around AI is coinciding with authoritarian politics and ideas.

What is the role for education and educators?

On the one hand, we are told that technology is already “smarter” than we are, smarter than we can teach our young people to be. On the other hand, we are asked trust people like Altman to train or regulate this AI.

What role is there, then, for education and educators?

Reflecting on the history of IQ testing should prompt universities to call into question the value that we have placed on IQ to begin with.

IQ was at first an educational tool; it was gradually transformed into a weapon used to identify and segregate whole populations based on terrible science.

Educators will need to confront how many of the ways that we have built efficiency and credibility have also sought to validate our expertise in testing and ranking, sometimes understood as quantifying intelligence.

Ironically, our institutions’ obsessions with standardizing education and their over-emphasis on grading and assessing students has made our work too easy to automate.

It has also arguably contributed to grade inflation and other trends that devalue our important work.

What to do? Focus on connection, critical thinking

So, what do educators do? We should focus, more than ever, on the collaboration and critical thinking our students do, as well as how they connect through relationships and learn to connect ideas. We should move away from high-stakes testing, measuring and grading.

“Intelligence” itself has been an ableist, even eugenic, construct — certainly in how and why it has been measured.

Teaching and learning in contemporary universities can be much more dynamic, interpersonal and human. Our innovative classroom practices can lead other educators to resist transactional teaching as well.

We need to continue asking: “What is intelligence?” And we need to provide different answers to this question than we ever have throughout the history of higher education.