As one of the most valuable human inventions, artificial intelligence is a phenomenal issue in terms of the applied science that is progressively evolving in the current technology-based society. For a better comprehension of the artificial mind, it is essential to examine the notion of the ‘mind’ itself. Considering the philosophical and psychological approach, the concept of mind is classified as “mental states, functions or processes (such as thinking, remembering or believing)” (Erden, 2015, p.111). Besides, the intertwining of the mind and brain are bases upon two critical approaches of dualism and materialism. The dualist concept implies the fundamental division between the mind and brain, where mental and physical are the contrary notions. Materialism is the alternative perspective that believes only in material things. According to Erden (2015), there are three materialist theories, such as identity theory, eliminative materialism, and functionalism, that might facilitate the idea and possibility of the artificial mind.
The particular importance is given to the implications of functionalism as the possible outcomes of artificial minds. As biologically, the human brain can maintain specific mental processes at the current moment. There is a chance for them to be supported by any other material processes until they have proven to be the same in the functional sense. The development of the artificial mind was a time-consuming goal of scientists, engineers, philosophers, and psychologists. Artificial intelligence is the theory that implies the developmental process of computer systems responsible for performing tasks that generally involve human intelligence. Artificial intelligence (AI) consists of two central concepts, strong AI and weak AI (Erden, 2015).
Strong AI is the idea that artificial intelligence is eventually able to create intelligence equal to or surpassing the human mind. Some arguments suggest a possibility to fully reproduce human intelligence and the human mind with the help of technology. The most common prototypes of strong AI are presented in science fiction stories or films, including robots and machines that are endowed with special skills to think and act with an objective, logic, and intelligence. Besides, those technological inventions perform their tasks regardless of regular or consistent programming by a human.
The weak AI implies the idea that artificial intelligence is only able to simulate a mind. The followers of this idea, however, do not admit the resemblance of this technological intelligence to the human mind, as the followers of strong AI believe. They also might be less inclined to accept the possibility of artificial intelligence. The in-depth examination of this simple distinction between strong and weak artificial intelligence is essential to understand the impact intelligence and thinking have on the emergence of artificial intelligence. There are two critical concepts concerning human intelligence, such as reason and creativity, which means that the mind operates due to the human ability to reason and a certain amount of creativity.
It is crucial to analyze the perspectives and research approaches to human and machine thinking to understand their close interaction. One of the approaches was made by Alan Turing, who raised the most important and influential question in the history of computing: “can machines think?” (Erden, 2015, p. 120). The ideas in his seminal paper, written in 1950, are known as the Turing test that presents an ‘imitation game’ involving three participants. One of them serves as an interrogator who asks questions in a separate room and is obliged to identify a man and a woman among two other participants based on the gender-neutral labels provided.
The typewritten communication is applied, excluding any visual or tactile contact, or hearing their voices. Male and female participants were allowed to give false answers. The key elements of this game include a possibility for imitation and deception to consider the artificial intelligence concerning mechanical participants, as one of the human participants was replaced by the machine later in the test. This approach helps to examine if the machine can imitate intelligence and the overall possibility of the artificial mind and has a direct linkage with the concept of strong and weak AI, obviously supporting strong AI. Turing test is the general modern understanding of machine intelligence and is vital in the philosophy of artificial intelligence.
Another yet controversial approach to the issue of the human and artificial mind is the 1999 Searle’s Chinese room thought experiment. It aimed at presenting machines as the clever processors of symbols (syntax) and human minds that can process syntax as well as meaning (Erden, 2015). This serves as a response to the computational theory of mind (CTM), where the mind’s performance is seen as analogous to a computer. Searle’s Chinese room argument implies imagining oneself locked in a room together with a rulebook and cards with squiggles (Chinese symbols that Searle is not acknowledged with). More squiggles with questions are passed to him under the door by Chinese people and are meant to be answered according to the rulebook. Eventually, Searle succeeds in following the book’s instructions, although he still could not understand the content of the symbols and the game’s idea. He performs the tasks by following the instructions, however, without interpretation.
Searle’s experiment is an argument against strong AI that displays the way a digital computer uses syntactic rules to manipulate symbols, pretending it is a language. It refutes the Turing test, as it did not demonstrate the machine using a language in any meaningful way, even when it managed to deceive the interrogator. Based on these two contrary research approaches, one may conclude that programs manipulate symbols according to the rules and structure provided. However, the mind involves meaning (semantics) since it can understand and interpret those symbols, match them by pattern, and use them meaningfully. As such, human and machine minds differ because humans can understand the symbols and words they manage, as well as make decisions not based on the rulebook. Nevertheless, there are multiple attempts to study other problems for developing an artificial mind based on less traditional ideas of intelligence, which leaves the question of the possibility of the artificial mind open for future discussions.
Reference List
Erden, Y. (2015). Artificial minds. In: J. Turner, C. Hewson, K. Mahendran and P. Stevens, ed., Living Psychology: From the Everyday to the Extraordinary. The Open University, pp. 109–146.