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Intelligence quotient test

As explained in How Large Language Models Work

An intelligence quotient test is a standardized psychometric assessment intended to estimate cognitive abilities relative to a reference population.

An intelligence quotient (IQ) test measures performance on a finite set of capabilities, often specific logic puzzles completed under time constraints. It can correlate with outcomes such as school performance, but it does not provide an objective definition of intelligence or reduce intelligence to a single underlying cause. section 1.4

Different IQ tests exist because intelligence is difficult to define. Their usefulness comes from repeated refinement and from identifying answers that correlate with human performance—not from directly measuring the cause of that performance. section 7.1.1 section 1.4

Using IQ tests to judge an LLM

An LLM may perform impressively on an IQ test, just as it may perform well on the MCAT or bar exam. That result does not establish human-like intelligence: training data may contain similar questions, and IQ tests were designed to predict aspects of human performance rather than evaluate AI algorithms. section 7.1.1 section 1.4

How How Large Language Models Work covers it

How deep it goes
Defines tested abilities, correlations, and limitations, but stops short of explaining psychometric construction or scoring procedures.
Examples
Uses timed logic puzzles, school performance, and LLM results on IQ, MCAT, and bar exams as examples.
What you can do after
Evaluate IQ-test results as evidence about selected abilities while avoiding claims about intelligence’s fundamental nature or AI’s human equivalence.
How it connects
Connects IQ tests with intelligence, artificial intelligence, logic puzzles, school performance, and correlation versus causation.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of How Large Language Models Work. The section links point to the parts of the book it draws on.