It is worth reflecting, as much as HN seems to hate the social sciences, on this point. But the difficulty of measuring intelligence is a challenge that several fields have struggled with for decades. It is inherently hard because defining intelligence and building intelligence are very closely coupled. This both makes it hard to make unbiased measures as well making measures that don't affect the phenomenon basically NP hard, or known as the Flynn effect[0].

It also goes to how a lot of people misunderstand the replication crisis. 'Hard science' really should replicate - we should be able filter out sources fo error and variance because the phenomena (generally) isn't affected by our attempts to measure it. Making social science replicate often requires so much control that it is deabstracted from reality, meaning the effort at replication reduces the value and usefulness of the knowledge. Generalizable claims are hard because the sources of variance are so much larger adn more complex. Speaking as someone who went through a transition from engineering to social sciences, it is the concept that made it hard. I started my time in social sciences with a cool idea of a whole carrer based on just doing replication studies, because science. That was...useful and stupid at the same time.

[0] https://en.wikipedia.org/wiki/Flynn_effect