AI and Intelligence Testing: Lessons from a Humble Free IQ Test

Can we apply standard intelligence tests to AI systems, and what do their scores really tell us? In this article, we explore the challenges and insights gained from testing artificial intelligence (AI) with a free IQ test. We delve into the methodologies researchers use, highlight interesting findings, and discuss the limitations and benefits of these tests.

Introduction to AI Intelligence Testing

The field of artificial intelligence (AI) is rapidly evolving, and with it, the question of whether AI can standard intellectual tests designed for humans. Many researchers and enthusiasts have pondered whether AI systems can be compared to human intelligence and, if so, how they perform under these rigorous evaluations.

Standard IQ Tests and AI

Can AI be subjected to standard intelligence tests, such as those commonly used to evaluate human cognitive abilities? Yes, and yes, but does this assessment truly reveal anything meaningful?

Francois Chollet, a well-known figure in the Google AI community, has extensively studied this topic. His work aims to create a framework that can measure the intelligence of AI systems by building a corpus of questions to assess both fluid and crystallized intelligence.

Initial Impressions and Real-World Applications

One of the fascinating applications of Chollet's work is the testing of AI systems on mathematical word problems. These problems are notoriously difficult for both humans and AI, making them a perfect test for assessing problem-solving skills.

Early results showed that AI systems performed well initially, but when presented with problems that included red herrings (unrelated information that potentially confuses the solver), the performance dropped dramatically. This suggests that while AI can perform pattern recognition, true reasoning is still a long way off.

Free IQ Test on AI

To further explore this topic, I personally tried a free IQ test with an AI system. While the test itself is rudimentary and designed for human use, it sparked some interesting reflections on the current state of AI technology.

I used a free IQ test and had the AI system, specifically ChatGPT, attempt it. The results were quite revealing:

Test Results: ChatGPT

ChatGPT, as a large language model (LLM), did not perform exceptionally well on the IQ test. Despite the system's advanced natural language processing capabilities, it still encountered several issues that are characteristic of current AI limitations.

Here are some of the key findings:

1. Self-Contradictions

ChatGPT occasionally contradicted itself in its answers. For example, the statement "Nine chickens, two dogs, and three cats have a total of 40 legs" was marked as "True," despite the fact that chickens have two legs and not four. This indicates a fundamental problem with logical consistency and pattern matching.

2. Pattern Matching vs. True Reasoning

While ChatGPT could provide answers based on pattern recognition and basic knowledge, it struggled with questions that required deeper reasoning. When presented with a problem that included irrelevant information (red herrings), the performance plummeted. This suggests that current AI systems are still heavily reliant on pattern matching and may not possess true reasoning capabilities.

Conclusion: AI, Intelligence, and beyond

Despite the impressive advancements in AI, the current systems are still far from being truly intelligent. They excel at tasks involving pattern recognition and basic knowledge but struggle with more complex reasoning and problem-solving. This is evident from both the academic research and real-world tests conducted by enthusiasts.

While AI systems can be subjected to standard intelligence tests and can achieve reasonable scores, these tests may not fully capture the depth and nuance of human intelligence. Instead, they can provide insights into the current limitations and potential of AI systems.

As AI continues to evolve, it will be fascinating to see how these tests and evaluations change, and what new insights they bring to the field of artificial intelligence.