Before you can use a term in any meaningful way, you must have a definition for it. After all, if nobody agrees on a meaning, the term has none; it’s just a collection of characters. Defining the idiom—a term whose meaning isn’t clear from the meanings of its constituent elements—is especially important with technical terms that have received more than a little press coverage at various times and in various ways.
Saying that AI is an artificial intelligence doesn’t tell you anything meaningful, which is why people have 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 lesson uses AI according to that definition, and knowing it will help you follow the text more easily.
The term “artificial intelligence” was first coined in 1956 at a conference at Dartmouth College, marking the official birth of AI as an academic discipline.
Discerning intelligence
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
Which of these aspects of intelligence do you think is the most difficult for computers to simulate, and why?
The activities list could easily grow quite long, but even this list is relatively prone to interpretation by anyone who accepts it as viable. As the list implies, however, intelligence often follows a process that a computer system can mimic as part of a simulation:
- Set a goal (the information to process and the desired output) based on needs or wants.
- Assess the value of any known information in support of the goal.
- Gather additional information that could support the goal. The emphasis here is on information that could support the goal rather than on information you know will support the goal.
- Manipulate the data such that it achieves a form consistent with existing information.
- Define the relationships and truth values between existing and new information.
- Determine whether the goal is achieved.
- Modify the goal in light of the new data and its effect on the probability of success.
- 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 in the earlier list that describes intelligence.
Do you agree that computers are limited to mechanical manipulation of data, or can advancements in AI bridge this gap? Explain your perspective.
As part of deciding what intelligence actually involves, categorizing intelligence is also helpful. Humans don’t use just one type of intelligence; rather, they rely on multiple intelligences to perform tasks. Howard Gardner, a Harvard psychologist, has defined a number of these types of intelligence. Knowing them helps you relate them to the kinds of tasks a computer can simulate as intelligence. (Read more: The Theory of Multiple Intelligences.)
Want to go deeper? How do AIs simulate different human intelligences?
AI systems often focus on simulating specific aspects of intelligence. For example, bodily kinesthetic intelligence is mimicked by robots using sensors and actuators, while logical-mathematical intelligence underpins many data analysis and reasoning systems. However, creative intelligence—such as inventing radically new ideas—remains out of reach for current AI, which mostly recombines existing patterns rather than generating truly novel insights. Understanding where simulation ends and genuine intelligence begins is a central debate in AI research.
TABLE 1-1 The Kinds of Human Intelligence and How AIs Simulate Them
| Type | Simulation Potential | Human Tools | Description |
|---|---|---|---|
| Bodily kinesthetic | Moderate to high | Specialized equipment and real-life 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, or 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 in reality just a mathematically based version of an existing pattern. To create, an AI would need to possess self-awareness, which would require intrapersonal intelligence. |
| Interpersonal | Low to moderate | Telecommunication, social networks, collaborative tools | Interpersonal intelligence is the ability to understand and interact effectively with others. AI chatbots and virtual assistants attempt to simulate this through language processing and pattern recognition, but lack genuine human empathy or intuition. |
- You’ve explored how “artificial intelligence” is more than a label—it’s a term with deep controversy and complexity.
- You’ve reviewed core mental activities that make up intelligence and seen how computers attempt to simulate these processes.
Practitioners in AI development often focus on a narrow type of intelligence—such as pattern recognition or logical reasoning—rather than attempting to recreate the full spectrum of human intelligence. This pragmatic approach delivers tangible results, even if it falls short of replicating “true” intelligence.
The capability of a machine to perform tasks that typically require human intelligence, such as learning, reasoning, problem-solving, perception, and language understanding.
The theory that humans possess a variety of distinct types of intelligence, such as logical, interpersonal, and creative, rather than a single general intelligence.
Robotic surgery systems use bodily kinesthetic intelligence to perform precise operations, while virtual assistants use interpersonal and linguistic intelligence to interact with users.
Consider a task you do every day—such as making a decision or solving a problem. Which type of intelligence do you use most in that process, and could an AI perform that task as well as you?
Think about three different technologies you use daily (e.g., smartphone, search engine, voice assistant). For each, identify which type(s) of intelligence it simulates, if any.
- List three technologies you use often.
- For each, note which kind of intelligence (from the list above) it simulates.
- Briefly explain how that simulation works—or falls short—compared to a human using that intelligence.
Reflect on your own definition of intelligence. How does it compare to the list of activities and types of intelligence discussed here? Do you think AI can ever truly possess intelligence as you define it?
Artificial intelligence means a computer can “think” just like a human.
AI simulates aspects of intelligence through algorithms and data processing, but does not understand, reason, or create in the same way humans do.
What is artificial intelligence (AI)?
Tap to revealThe capability of a machine to perform tasks that typically require human intelligence.
List one mental activity associated with intelligence.
Tap to revealLearning, reasoning, understanding, grasping truths, seeing relationships, considering meanings, or separating fact from belief.
Who proposed the theory of multiple intelligences?
Tap to revealHoward Gardner, a Harvard psychologist.
Which mental activity is NOT typically associated with intelligence as described in this lesson?
Artificial intelligence refers to machines that simulate specific human mental activities, but do not replicate the full depth of human intelligence.
Understanding and defining intelligence is complex, with multiple types and processes that are difficult—if not impossible—for current AI systems to fully mimic.
Even if you don’t necessarily agree with the definition of AI as it appears in the sections that follow, this lesson uses AI according to that definition, and knowing it will help you follow the text more easily.
How confident are you that you can explain the difference between human intelligence and artificial intelligence?
Machine learning, a subset of AI, focuses specifically on enabling computers to learn from data—just one aspect of the broader concept of intelligence discussed in this lesson.