Today’s artificial intelligence may seem powerful, but its abilities related to deductive reasoning are actually very weak. Current AI possesses only inductive statistical capabilities. Even though large language models (LLMs) appear to have deductive reasoning abilities, they merely simulate this through context-based pseudo-deductive reasoning. When faced with unknown phenomena, they still struggle to respond and can even produce hallucinations.
Deductive reasoning is a skill inherent to all animals, and even to cells. While this form of reasoning may not strictly adhere to formal logical definitions, it generally follows the classic framework of deductive reasoning. This flexibility in reasoning is essential for evolution.
Neural networks, however, cannot truly learn this capability. They can only engage in inductive thinking, and even then, their efficiency pales in comparison to humans. The effectiveness of human induction can often be achieved with a single instance, whereas AI may need to iterate dozens of times during training. Overall, the data humans collect before induction is processed through deductive reasoning.