Evidence of Cognitive Deficits andDevelopmental Advances in Generative AI: A Clock Drawing Test Analysis

TL;DR

This study evaluates recent generative AI models on the Clock Drawing Test, revealing their strengths in rendering clock features but weaknesses in numerical reasoning and time accuracy, akin to cognitive impairments.

Contribution

It provides a novel assessment of AI cognitive abilities using a neuropsychological test, highlighting specific deficits in reasoning and numerical understanding.

Findings

GPT-4 Turbo and Gemini Pro 1.5 correctly displayed the time

Most models showed errors in numerical sequencing and reasoning

Drawing deficits linked to visual-spatial and working memory weaknesses

Abstract

Generative AI's rapid advancement sparks interest in its cognitive abilities, especially given its capacity for tasks like language understanding and code generation. This study explores how several recent GenAI models perform on the Clock Drawing Test (CDT), a neuropsychological assessment of visuospatial planning and organization. While models create clock-like drawings, they struggle with accurate time representation, showing deficits similar to mild-severe cognitive impairment (Wechsler, 2009). Errors include numerical sequencing issues, incorrect clock times, and irrelevant additions, despite accurate rendering of clock features. Only GPT 4 Turbo and Gemini Pro 1.5 produced the correct time, scoring like healthy individuals (4/4). A follow-up clock-reading test revealed only Sonnet 3.5 succeeded, suggesting drawing deficits stem from difficulty with numerical concepts. These findings may reflect weaknesses in visual-spatial understanding, working memory, or calculation, highlighting strengths in learned knowledge but weaknesses in reasoning. Comparing human and machine performance is crucial for understanding AI's cognitive capabilities and guiding development toward human-like cognitive functions.