Human and Machine: A View through Kant's Use of Regulative Reason - Ümit Taştan (Hitit İlahiyat Dergisi)

(untitled)
This study examines the qualitative difference between human intelligence and artificial intelligence (AI) through the lens of Immanuel Kant’s philosophy. This difference is based on the human mind’s idea of unity and its intuitive ability to limit this unity. Kant argues that, through the regulative use of reason, it is able to obtain conceptual wholes such as God, soul, and universe. We argue that this idea of unity, derived through regulative reason, plays a significant role in distinguishing the human mind from AI. Based on Kant’s idea of unity, our study determines that the human mind constructs a unity such as a formal system. Artificial intelligence, which is made possible by this construction, is inadequate in solving many problems that have shown surprising developments in recent years. We attribute this inadequacy to the inability of computers to model the aforementioned idea of wholeness. We justify this claim through the problem of “narrowing the brute search space” in computational complexity, which is a significant issue in computer science. This problem arises from the lack of a formal procedure for narrowing down a problem space with very large boundaries. When computers lack an efficient procedure or an analytical solution to the problems they aim to solve, they are forced to try all available solutions. In contrast, the human mind has cognitive abilities that allow it to intuitively narrow down these large problem spaces.Kant’s use of regulative reason provides a framework for understanding this human faculty. According to Kant, the regulative function of reason supplies the concepts of pure reason that guide scientific inquiry. For example, through a concept of pure reason, such as the cosmos, the human mind is able to limit the physical domain in such a way as to conduct physical science. Through Kant’s use of regulative reason, we consider that the human mind, by bringing together a set of formal signs, makes a limitation such as a formal system. Since we can conceptualize a unity such as a formal system, we can discuss algorithms that operate according to this system. The regulative use of reason, which enables the establishment of such wholes, creates a qualitative difference between AI and the human mind when combined with the human’s intuitive thinking ability. However, establishing the link between Kant’s idea of unity and intuitive thinking based solely on Kantian philosophy is quite difficult. Thus, we refer to the views of Henri Bergson and Nazif Muhtaroğlu to establish this connection. Bergson, while explaining the concept of motion, argues that the mind reaches such an idea of unity through an instinctive synthesis. In this respect, movement is a mental synthesis, insofar as it is a transition from one point to another. Similarly, Muhtaroğlu, after emphasizing that the intuitive cognition that accompanies reason is a direct, unmediated and rapid cognition, identifies the type of intuition that leads to the idea of unity as immediate intuition. Stating that this type of intuition is a cognitive intuition, Muhtaroğlu cites Archimedes’ discovery of the laws of fluids as an example of this way of thinking. In our study, we use the example of Archimedes to show how intuition accompanies the narrowing of the field of brute force search. Thus, when the regulative use of reason and intuitive thinking come together, a difference emerges in the cognitive abilities of the human mind and artificial intelligence. Thanks to the regulative use of reason, the human mind is able to have an awareness of the unity of the object field it is confronted with. The fact that this awareness is accompanied by intuitive thinking allows this field of unity to be narrowed. Since artificial intelligence cannot model both the use of regulative reasoning and intuitive thinking, it is subjected to the brute search method. We argue that such a deficiency underlies the lack of analytical solutions to problems of computational complexity. This deficiency reveals the difference between the human mind and artificial intelligence in problem solving and narrowing down large search spaces.