What is intelligence? It is a subjective concept, but Psychologist Howard Gardner’s Seven Types of Intelligence, as they apply to children, is a good place to start:
- Linguistic –
Children with this kind of intelligence enjoy writing, reading, telling stories or doing crossword puzzles.
- Logical-Mathematical –
Children with lots of logical intelligence are interested in patterns, categories and relationships. They are drawn to arithmetic problems, strategy games and experiments.
- Bodily-kinesthetic –
These kids process knowledge through bodily sensations. They are often athletic, dancers or good at crafts such as sewing or woodworking.
- Spatial –
These children think in images and pictures. They may be fascinated with mazes or jigsaw puzzles, or spend free time drawing, building with Legos or daydreaming.
- Musical –
Musical children are always singing or drumming to themselves. They are usually quite aware of sounds others may miss. These kids are often discriminating listeners.
- Interpersonal –
Children who are leaders among their peers, who are good at communicating and who seem to understand others’ feelings and motives possess interpersonal intelligence.
- Intrapersonal –
These children may be shy. They are very aware of their own feelings and are self-motivated.
These seven are just the tip of the Iceberg. Each one may be subdivided into an indefinite number of sub-categorizations. Additionally, they may be cross-referenced to create specific types of genius, think of the combination of kinesthetic and spatial intelligence that goes into being a pinball wizard.
Mensa is an international organization that requires applicants to score in the top 2% of test takers on a widely accepted Intelligence Test such as the SAT, IQ, or ACT for membership. The focus of these tests being solely on two types of intelligence, linguistic and logical-mathematical, seems almost pedantic in the vast mosaic of intelligence types.
So this raises the question: How do we measure Intelligence? If Mensa, the top 2% of the world’s Intelligencia, cannot (or will not) develop a more substantive measure for intelligence, then we must explore the cultural and intellectual pluralism that makes such measurement impossible:
In a civilization as enormous the human race, without the specialization of knowledge and labor it would all break down. Agriculture, chemistry, physics, social engineering, market science, production science, information technology, mechanical, on and on, lose any one of these specializations and an entire sector of goods and services disappears with it, potentially generating a domino effect on the whole as other, dependent systems fail. In spite of this understanding, we still persist on elevating some types of knowledge above others.
The perceived value of some specializations over others creates one barrier to comprehending Intelligence. In America, we compare Intelligences based on their economic value. When my car breaks down, I value the Intelligence of an Auto mechanic as superior to mine own. On the Internet, we value Rhetorical Intellect above others, whoever creates the most entertaining appeal wins the hits. Thus the value of Intelligence is dependent upon its context.
Rap music and Poetry Slam’s employ metaphors, similes, rhyme, double entendres, and a host of other techniques to create melodious verbal “flow”. They combine musical and linguistic intelligences with ingenious results, but because of Rap and Bohemian argots, these artists cannot be accurately gauged through contemporary Intelligence Tests. The test and individual are incapable of communication.
This is because IQ Tests are immersed in the constructs of Linguistic Intelligence. Albert Einstein would test low on an IQ test written in English, because German was his native tongue. IQ Tests are written in the language of the most popular culture. Is it any wonder then, that Mensa cites verbal proficiency as the single most important factor in improving one’s Intelligence?
Intelligence is malleable, both subject to improvement and recidivism. As an English Major in College, I had strong Linguistic Intelligence, but never took Calculus-level Mathematics. My IQ was 118. Then I began working in programing and was forced to work out complex logical problems on a daily basis. Next thing I know, my last three Mensa scores were 128, 129, and 129, genius-level being 130.
I gave up on Mensa because of Ideological differences, but with enough effort and time to make that effort, I could have made that 130 score. Free time is crucial to improving Intelligence. Effort is even more important, but that is within the realm of an individual’s control. Temporal freedom is a struggle against all of our daily demands: working to pay off bills, fighting sickness, adhering to the State’s bureaucratic demands. Intelligence depends very much on resources.
Possibly one of the biggest influences on popular Artificial Intelligence development is the Turing Test. Alan Turing’s proposed method for evaluating an Artificial Intelligence involved having a human being on a computer converse with both a human and an AI. If the person couldn’t tell the difference, then we have AI success.
As one might expect, limiting the scope of discussion improved results for the AI, another example of Intelligence in relation to context. For instance, AI’s designed to imitate humans may run around multi-user online games virtually indistinguishable from human players. Because their discourse is limited to the subject of the game and the conversations are brief enough to prevent arousing suspicion, the deception is managed with very simple programming.
The Turing Test’s focus on simply fooling human Intelligences has led to the popular field of Chatbots, computer programs capable of holding a moderately engaging conversation with a human. Using a process of reducing inputted sentences down to groups of related key words to determine the subject, the Chatbot selects from a database of pre-entered responses and returns the most relevant. Again, reducing the scope of the conversation to a specific subject improves the result. For this reason, Chatbots are becoming useful as Software and Website Helpers, similar to the MS Word Paperclip, but more personable.
While Chatbot development can be entertaining, it does little to advance the field of Artificial Intelligence except through increasing its popularity. The Intelligence-Imitators do not make any attempt to understand the information given them. They do not store information in a growing database of details similar to a human mind’s Cognitive Schema. Nor do they construct hypothesis out of stored data. Without at least these functions, there cannot be Intelligence.
Currently the greatest advances in Artificial Intelligence theory comes from Germany, where a science of breaking down sentences into a mathematical form holds wonderful potential. “The cat is black” becomes “cat = black,” but this is just the tip of deconstructing the language iceberg.
Software attempts to describe real life functions through mathematics and logic. The logic in your computer’s calculator program expresses elementary mathematics. In a sense, these are concrete ways of quantifying the complex system that is reality.
AI’s are Intelligence expressed through structured logic and mathematics. As we evolve them, we will learn more about how our own Cognitive Schemas are structured and function. Already we see the comparisons between us and them: Specializations of Intelligence, the significance of Intelligence dependent on context, the importance of Linguistic aspects, the benefits of different Programming Languages used to write the AI, and so on.
On a Social level, an understanding of Intelligence argues for the need to respect all forms of Intelligence, from the Jock to the Bookworm. When we get to the Marketplace of Ideas, we will need to keep this principle in mind. All Ideas may not be created equal, but they must be treated with equal respect.