Artificial Intelligence (ai)

The Intelligent Computer

This book is about the field that has come to be called Artificial Intelligence. In this chapter, you learn how to define Artificial Intelligence, and you learn how the book is arranged. You get a feeling for why Artificial Intelligence is important, both as a branch of engineering and as a kind of science. You learn about some successful applications of Artificial Intelligence. And finally, you learn about criteria you can use to determine whether work in Artificial Intelligence is successful.

The Field and the Book

There are many ways to define the field of Artificial Intelligence. Here is one: Artificial Intelligence is ... the study of the computations that make it possible to perceive, reason, and act. From the perspective of this definition, Artificial Intelligence differs from most of psychology because of the greater emphasis on computation, and Artificial Intelligence differs from most of computer science because of the emphasis on perception, reasoning, and action.

From the perspective of goals, Artificial Intelligence can be viewed as part engineering, part science:

* The engineering goal of Artificial Intelligence is to solve real-world problems using Artificial Intelligence as an armamentarium of ideas about representing knowledge, using knowledge, and assembling systems.

* The scientific goal of Artificial Intelligence is to determine which ideas about representing knowledge, using knowledge, and assembling systems explain various sorts of intelligence.

This Book Has Three Parts

To make use of Artificial Intelligence, you need a basic understanding of how knowledge can be represented and what methods can make use of that knowledge. Accordingly, in Part I of this book, you learn about basic representations and methods. You also learn, by way of vision and language examples, that the basic representations and methods have a long reach.

Next, because many people consider learning to be the sine qua non of intelligence, you learn, in Part II, about a rich variety of learning methods. Some of these methods involve a great deal of reasoning; others just dig regularity out of data, without any analysis of why the regularity is there.

Finally, in Part III, you focus directly on visual perception and language understanding, learning not only about perception and language per se, but also about ideas that have been a major source of inspiration for people working in other subfields of Artificial Intelligence.

The Long-Term Applications Stagger the Imagination

As the world grows more complex, we must use our material and human resources more efficiently, and to do that, we need high-quality help from computers. Here are a few possibilities:

* In farming, computer-controlled robots should control pests, prune trees, and selectively harvest mixed crops.

* In manufacturing, computer-controlled robots should do the dangerous and boring assembly, inspection, and maintenance jobs.

* In medical care, computers should help practitioners with diagnosis, monitor patients' conditions, manage treatment, and make beds.

* In household work, computers should give advice on cooking and shopping, clean the floors, mow the lawn, do the laundry, and perform maintenance chores.

* In schools, computers should understand why their students make mistakes, not just react to errors. Computers should act as superbooks, displaying planetary orbits and playing musical scores, thus helping students to understand physics and music.

The Near-Term Applications Involve New Opportunities

Many people are under the false impression that the commercial goal of Artificial Intelligence must be to save money by replacing human workers. But in the commercial world, most people are more enthusiastic about new opportunities than about decreased cost. Moreover, the task of totally replacing a human worker ranges from difficult to impossible because we do not know how to endow computers with all the perception, reasoning, and action abilities that people exhibit.

Nevertheless, because intelligent people and intelligent computers have complementary abilities, people and computers can realize opportunities together that neither can realize alone. Here are some examples:

* In business, computers can help us to locate pertinent information, to schedule work, to allocate resources, and to discover salient regularities in databases.

* In engineering, computers can help us to develop more effective control strategies, to create better designs, to explain past decisions, and to identify future risks.

Artificial Intelligence Sheds New Light on Traditional Questions

Artificial Intelligence complements the traditional perspectives of psychology, linguistics, and philosophy. Here are several reasons why:

* Computer metaphors aid thinking. Work with computers has led to a rich new language for talking about how to do things and how to describe things. Metaphorical and analogical use of the concepts involved enables more powerful thinking about thinking.

* Computer models force precision. Implementing a theory uncovers conceptual mistakes and oversights that ordinarily escape even the most meticulous researchers. Major roadblocks often appear that were not recognized as problems at all before the cycle of thinking and experimenting began.

* Computer implementations quantify task requirements. Once a program performs a task, upper-bound statements can be made about how much information processing the task requires.

* Computer programs exhibit unlimited patience, require no feeding, and do not bite. Moreover, it is usually simple to deprive a computer program of some piece of knowledge to test how important that piece really is. It is almost always impossible to work with animal brains with the same precision.

Note that wanting to make computers be intelligent is not the same as wanting to make computers simulate intelligence. Artificial Intelligence excites people who want to uncover principles that must be exploited by all intelligent information processors, not just by those made of neural tissue instead of electronic circuits. Consequently, there is neither an obsession with mimicking human intelligence nor a prejudice against using methods that seem involved in human intelligence. Instead, there is a new point of view that brings along a new methodology and leads to new theories.

Artificial