Measuring an Artificial Intelligence System's Performance on a Verbal IQ Test For Young Children

TL;DR

This study evaluates an AI system's verbal IQ using a standard children's test, revealing strengths in vocabulary and similarities but weaknesses in comprehension, highlighting areas for AI improvement.

Contribution

First application of a children's verbal IQ test to an AI system, demonstrating how standard psychometric assessments can evaluate AI language understanding.

Findings

AI scored average for 4-year-olds, below for 5-7 years.

Strengths in Vocabulary and Similarities subtests.

Weaknesses in Comprehension and Word Reasoning.

Abstract

We administered the Verbal IQ (VIQ) part of the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III) to the ConceptNet 4 AI system. The test questions (e.g., "Why do we shake hands?") were translated into ConceptNet 4 inputs using a combination of the simple natural language processing tools that come with ConceptNet together with short Python programs that we wrote. The question answering used a version of ConceptNet based on spectral methods. The ConceptNet system scored a WPPSI-III VIQ that is average for a four-year-old child, but below average for 5 to 7 year-olds. Large variations among subtests indicate potential areas of improvement. In particular, results were strongest for the Vocabulary and Similarities subtests, intermediate for the Information subtest, and lowest for the Comprehension and Word Reasoning subtests. Comprehension is the subtest most strongly associated with common sense. The large variations among subtests and ordinary common sense strongly suggest that the WPPSI-III VIQ results do not show that "ConceptNet has the verbal abilities a four-year-old." Rather, children's IQ tests offer one objective metric for the evaluation and comparison of AI systems. Also, this work continues previous research on Psychometric AI.