Intelligence has numerous definitions. To some, it is the measuring of intelligent quotient, and to others it is the time bound completion of tasks. Some link it with creativity, while many consider it algorithmicizing. Arguably, there is absence of consensus about the very definition however, it still has universal connotations. A common definition has been drafted by intelligence experts: a very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think and perceive abstractly, comprehend complex ideas, learn quickly and learn from experience. It is not merely book learning, a narrow academic skill, or test-taking smarts rather, it reflects a broader and deeper capability to comprehend our surroundings—’catching on,’ ‘making sense’ of things, or ‘figuring out’ what to do. Under this definition it is essential to inquire some fundamentals of Artificial Intelligence (AI) and Human Intelligence (HI) in order to differentiate between them.
What makes HI different from AI? In brief, HI is a non-uniform cognition which involves a process comprising of phases and stages. It is based on sensory-knowledge and mental faculties. Seeing, hearing, smelling, tasting, touching and intuition are fundamental of sensory-knowledge, while mental-faculties are memory, perception, cognition, imagination, will and intuition. Each of them has well-knitted but complex neural-engineering. Now, let us take a glimpse at the elements of AI. Its knowledge is based on data/information, the source of acquiring this information is human input. The process involves data, algorithm, learning, computation and action.
A very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think and perceive abstractly, comprehend complex ideas, learn quickly and learn from experience.
The chief distinction between HI and AI is the means of acquiring knowledge. Homo sapiens get knowledge through five senses excluding the innate knowledge. Interaction of senses with environment is the topmost condition of acquiring knowledge but the environment has no control over a human’s ability of acquiring knowledge. The moment a human being is born its interaction with the environment begins. The growth of human widens its domain and range of interaction with the environment. This process goes on. The more the interaction the greater the amount of knowledge acquired. At a certain point, human acquires as well as generates knowledge (self-cognition on the basis of previous interaction) even in the absence of new interaction with the surroundings. But the case of a computer acquiring knowledge/data is absolutely dependent on a human’s input. Interaction with the environment plays no role in acquiring knowledge in the case of a computer, it only learns what its fed. The crux is that the information acquired by a human being cannot be limited unlike the information acquired by a computer, which is limited to the extent of what is provided to it.
Memory is the kingpin of intelligence. All intelligence builds upon memory; even irrationality needs memory. Human and computer memory share meaningful discrepancies. Computer memory is static, tabular, erasable and can be overwritten. Paradoxically, human memory is dynamic, contextual, perceptual and is evolutionary. That is to say, both human and computer memory have converse dimensions. This kind of non-uniformity blinkers a computer’s perception in terms of process, domain and range.
The solid reason behind it is that every object in the environment acts as a stimulus to a human being’s sensory system managed by the brain. Impairment in one or two senses cannot fail the whole sensory system. Even loss of mind does not fully vanish sensation in humans. In computers, the principle behind voice, face and threat perception is algorithmic in nature that is why it either refuses the stimulus or results in wrongness if the stimulus does not match with the program.
In HI, sensation, memory and perception are the undertones of imagination. The former serves the latter where both overlap each other, to some extent. Holistically, imagination is the highest stage of intelligence. Both, intelligence and creativity live in the womb of imagination. That is why Einstein said, ‘the true sign of intelligence is not knowledge but imagination’. Verily, artificial imagination or machine imagination exists in computational form and is algorithmic in nature. An imagination based on computation and algorithm is usually mimetic of numeric and calculation but void in certitudes of original imagination.
Cognition is a term referring to the mental processes involved in gaining knowledge and comprehension. These processes include thinking, knowing, remembering, judging and problem-solving. These are higher-level functions of the brain and encompass language, imagination, perception, and planning etc. This has become the most critical stage in the development of AI because nature, ability and capability of machine cognition will determine the future course of AI. Experts have only one model of cognition, human cognition, and they are in pursuit of developing machine cognition that would be modelled on human cognition. So, firstly, we have to understand the nature, structure, functions, factors, domain, range and limits of human cognition in order to differentiate it with machine cognition. That is to say, what are the foundations of human cognition? How human cognition works? How human cognition is different from machine cognition? Can machine cognition acquire nature, form and features of human cognition? If yes, how? If no, why? Structurally and functionally, all the sensory systems (seeing, hearing, smelling, tasting, touching) and mental faculties (memory, perception, imagination, cognition, will, intuition) work in cooperation. Purposely, all are subservient to cognition and imagination.
However, human cognition possesses some unique influencing factors that are absent in a machine’s program, information, knowledge, data, expertise and ultimately in cognition. These unique influencing-factors can be divided into four categories. Inner factors like emotions, social factors like norms and ethics, environmental factors like calamity and cosmological factors like forces of nature. The first factor (emotions) gets influence from other factors and creates non-uniformity in the sensory system and mental faculties. This non-uniformity in the sensory system and in mental faculties is directly proportional to cognition as well. It is pertinent to mention here that manifestation of uniformity of cognition in tasking among humans is usually done because humans and their cognition is conditioned. In simple words, generally, we manifest conditioned-cognition that brings uniformity in our cognition and in tasking (behavior). For once, let our conditioned-cognition be unconditioned, unpredictability and randomness will rule cognition and behavior.
However, human cognition possesses some unique influencing factors that are absent in a machine’s program, information, knowledge, data, expertise and ultimately in cognition. These unique influencing-factors can be divided into four categories. Inner factors like emotions, social factors like norms and ethics, environmental factors like calamity and cosmological factors like forces of nature.
In intelligence’s territory, randomness is nothing but imprudent behavior. It is like an infinite monkey theorem which says, if a monkey keeps on hitting keys on a keyboard randomly, it will type the given text even Shakespeare’s Hamlet. In fact, the monkey would almost surely type every possible finite text an infinite number of times. However, the probability that the monkey would type a complete work such as Shakespeare’s Hamlet is so tiny that the chance of it occurring during a period of time hundreds of thousands of orders of magnitude longer than the age of the universe is extremely low (but technically not zero). This behavior seems consistent but deprived of intelligence. But the case of machine/computer is not different from the monkey theorem because machine cannot even compute without human aid. Realistically, thinking lies outside the territory of machines and computers. In the words of Descartes, I think, therefore I am. Analogically, homo sapiens think therefore they are, machines cannot think therefore they are not. Thus, the debate infers that machine-cognition cannot be modelled exactly on human-cognition. Same is the case with intelligence because true intelligence demands cognition and imagination which is absent in machines. Therefore, organically and qualitatively, AI and HI are in juxtaposition. The inquest suggests, arguably, the quest of AI to conquest HI is impossible.
