By John Paul Mueller, Luca Massaron

Saying that AI is an artificial intelligence doesn’t really tell you anything meaningful, which is why there are so many discussions and disagreements over this term. Yes, you can argue that what occurs is artificial, not having come from a natural source. However, the intelligence part is, at best, ambiguous. Even if you don’t necessarily agree with the definition of AI as it appears in the sections that follow, this book uses AI according to that definition, and knowing it will help you follow the rest of the text more easily.

People define intelligence in many different ways. However, you can say that intelligence involves certain mental activities composed of the following activities:

  • Learning: Having the ability to obtain and process new information.
  • Reasoning: Being able to manipulate information in various ways.
  • Understanding: Considering the result of information manipulation.
  • Grasping truths: Determining the validity of the manipulated information.
  • Seeing relationships: Divining how validated data interacts with other data.
  • Considering meanings: Applying truths to particular situations in a manner consistent with their relationship.
  • Separating fact from belief: Determining whether the data is adequately supported by provable sources that can be demonstrated to be consistently valid.

The list could easily get quite long, but even this list is relatively prone to interpretation by anyone who accepts it as viable. As you can see from the list, however, intelligence often follows a process that a computer system can mimic as part of a simulation:

  1. Set a goal based on needs or wants.
  2. Assess the value of any currently known information in support of the goal.
  3. Gather additional information that could support the goal.
  4. Manipulate the data such that it achieves a form consistent with existing information.
  5. Define the relationships and truth values between existing and new information.
  6. Determine whether the goal is achieved.
  7. Modify the goal in light of the new data and its effect on the probability of success.
  8. Repeat Steps 2 through 7 as needed until the goal is achieved (found true) or the possibilities for achieving it are exhausted (found false).

Even though you can create algorithms and provide access to data in support of this process within a computer, a computer’s capability to achieve intelligence is severely limited. For example, a computer is incapable of understanding anything because it relies on machine processes to manipulate data using pure math in a strictly mechanical fashion. Likewise, computers can’t easily separate truth from mistruth. In fact, no computer can fully implement any of the mental activities described in the list that describes intelligence.

As part of deciding what intelligence actually involves, categorizing intelligence is also helpful. Humans don’t use just one type of intelligence, but rather rely on multiple intelligences to perform tasks. Howard Gardner of Harvard has defined a number of these types of intelligence, and knowing them helps you to relate them to the kinds of tasks that a computer can simulate as intelligence.

Understanding the kinds of intelligence
Type Simulation Potential Human Tools Description
Visual-spatial Moderate Models, graphics, charts, photographs, drawings, 3-D modeling, video, television, and multimedia Physical environment intelligence used by people like sailors and architects (among many others). To move at all, humans need to understand their physical environment — that is, its dimensions and characteristics. Every robot or portable computer intelligence requires this capability, but the capability is often difficult to simulate (as with self-driving cars) or less than accurate (as with vacuums that rely as much on bumping as they do moving intelligently).
Bodily-kinesthetic Moderate to High Specialized equipment and real objects Body movements, such as those used by a surgeon or a dancer, require precision and body awareness. Robots commonly use this kind of intelligence to perform repetitive tasks, often with higher precision than humans, but sometimes with less grace. It’s essential to differentiate between human augmentation, such as a surgical device that provides a surgeon with enhanced physical ability, and true independent movement. The former is simply a demonstration of mathematical ability in that it depends on the surgeon for input.
Creative None Artistic output, new patterns of thought, inventions, new kinds of musical composition Creativity is the act of developing a new pattern of thought that results in unique output in the form of art, music, and writing. A truly new kind of product is the result of creativity. An AI can simulate existing patterns of thought and even combine them to create what appears to be a unique presentation but is really just a mathematically based version of an existing pattern. In order to create, an AI would need to possess self-awareness, which would require intrapersonal intelligence.
Interpersonal Low to Moderate Telephone, audio conferencing, video conferencing, writing, computer conferencing, email Interacting with others occurs at several levels. The goal of this form of intelligence is to obtain, exchange, give, and manipulate information based on the experiences of others. Computers can answer basic questions because of keyword input, not because they understand the question. The intelligence occurs while obtaining information, locating suitable keywords, and then giving information based on those keywords. Cross-referencing terms in a lookup table and then acting on the instructions provided by the table demonstrates logical intelligence, not interpersonal intelligence.
Intrapersonal None Books, creative materials, diaries, privacy, and time Looking inward to understand one’s own interests and then setting goals based on those interests is currently a human-only kind of intelligence. As machines, computers have no desires, interests, wants, or creative abilities. An AI processes numeric input using a set of algorithms and provides an output, it isn’t aware of anything that it does, nor does it understand anything that it does.
Linguistic Low Games, multimedia, books, voice recorders, and spoken words Working with words is an essential tool for communication because spoken and written information exchange is far faster than any other form. This form of intelligence includes understanding spoken and written input, managing the input to develop an answer, and providing an understandable answer as output. In many cases, computers can barely parse input into keywords, can’t actually understand the request at all, and output responses that may not be understandable at all. In humans, spoken and written linguistic intelligence come from different areas of the brain, which means that even with humans, someone who has high written linguistic intelligence may not have similarly high spoken linguistic intelligence. Computers don’t currently separate written and spoken linguistic ability.
Logical-mathematical High Logic games, investigations, mysteries, and brain teasers Calculating a result, performing comparisons, exploring patterns, and considering relationships are all areas in which computers currently excel. When you see a computer beat a human on a game show, this is the only form of intelligence that you’re actually seeing, out of seven. Yes, you might see small bits of other kinds of intelligence, but this is the focus. Basing an assessment of human versus computer intelligence on just one area isn’t a good idea.