09 April 2025 Does Artificial Intelligence Really Think?

So, how is this mechanical imitation done?
Artificial intelligence demonstrates problem-solving, decision-making, and learning capabilities by employing various methods of thinking and reasoning. Below are the main types of reasoning and judgement commonly used in artificial intelligence systems:

Deductive Reasoning: Deductive reasoning draws specific conclusions from general principles using a logic-based approach. It is commonly applied in rule-based and symbolic AI systems. For instance: “All humans are mortal. Socrates is a human. Therefore, Socrates is mortal.”

Inductive Reasoning: Inductive reasoning derives general rules or models from specific observations, moving from the particular to the general. It is commonly used in classification, prediction, modelling, and deep learning. Data-driven machine learning can be shown as an example.

Abductive Reasoning: This model, focused on identifying the most probable explanation, makes the most logical inference about a given subject using incomplete information. It is used in areas such as diagnosis and fault analysis. Unlike the other two models, Abductive reasoning operates in a backward fashion.

Beyond these core reasoning processes, a variety of other techniques and models, including analogical reasoning, probabilistic reasoning, symbolic and non-symbolic reasoning, intuitive reasoning, meta-reasoning, common sense reasoning, and ethical reasoning may be used individually or in combination.

One reason AI systems can appear to “think” and deliver impressive results is that humans often struggle to apply their intelligence methodically and consistently over extended periods. As human beings, can we combine all our accumulated life experience with our professional knowledge, emotions, and intuition to produce optimal results quickly and consistently? What are your thoughts on this?