What Is Artificial Intelligence?
In this chapter:
Defining intelligence and artificial intelligence
Tracing the early history of artificial intelligence
Recognizing key limitations
Differentiating strong and weak artificial intelligence
In 1955, Dartmouth professor John McCarthy coined the term artificial intelligence (AI for short) as part of an academic grant to assemble the first AI conference—the Dartmouth Summer Research Project on Artificial Intelligence in 1956. The goal of this conference was to get computers to behave in ways that humans would identify as intelligent.
At the time, computers were taking up whole floors in office buildings, yet they had less processing power than most modern smart watches. Making these computers intelligent was quite an ambitious goal, and conference participants soon bumped up against the limitations inherent in the hardware at the time. They made little progress toward creating the machine equivalent of a human brain.
The most lasting contribution from this grant was the term artificial intelligence. It ignited everyone’s imagination and inspired journalists, writers, academics, and computer scientists to envision a futuristic world in which machines would think like humans. Had Professor McCarthy come up with a different name, this conference, in all likelihood, would have faded into memory. Thanks to McCarthy’s choice of words, however, artificial intelligence has continued to fuel the imagination and drive progress toward creating intelligent machines.
Unfortunately, the concept of AI and the prospect of machines displacing humans in the workplace are frightening to most people. Just imagine if the first personal computers had been called artificial employees. Workers would have panicked as soon as the first PCs arrived at their office. Personal computers sound personable. Artificial employees would have threatened to take their jobs!
Likewise, the term artificial intelligence sends shivers down the spines of many people who rely on their intelligence for their jobs. This can include professionals such as lawyers, doctors, and analysts. They might all imagine a day when they’re supplanted by computerized counterparts.
To alleviate some of the fear surrounding AI, it is important to separate the term from the technology. While the term evokes images of sentient and perhaps omniscient machines supplanting humans, the technology is more subdued. You won’t see a mechanized version of the human brain any time soon. As a technology, AI is merely any system that exhibits behavior that could be interpreted as human intelligence, such as winning a game of chess against a world-renowned chess master.
What Is Intelligence?
The dictionary definition of artificial intelligence is the capability of a machine to imitate intelligent human behavior. Determining the meaning of intelligence, however, is the greater challenge. Although we all agree that intelligence has something to do with knowledge and the ability to reason, human intelligence seems to go beyond that to include consciousness or self-awareness, wisdom, emotion, sympathy, intuition, and creativity. To some, intelligence also involves spirituality—a connection to a greater force or being.
To further challenge our ability to define intelligence is the fact that human intelligence comes in many forms. Whereas some people are highly intelligent in the field of mathematics, others excel in art, music, politics, business, medicine, law, linguistics, and so on. Some people may excel in academics, whereas others are skilled in trades or have a higher level of emotional competence. And although people have tried to develop a single standard for measuring intelligence, such as the intelligent quotient (IQ), such standards are skewed. For example, a typical IQ test evaluates only short-term memory, analytical thinking, mathematical ability, and spatial recognition.
Without a reliable standard for measuring human intelligence, it’s very difficult to point to a computer and say that it’s behaving intelligently. Computers are certainly very good at performing certain tasks and may do so much better and faster than humans, but does that make them intelligent? For example, computers have been able to beat humans in chess for decades. IBM Watson beat some of the best champions in the game show Jeopardy. Google’s DeepMind has beaten the best players in the 2500-year-old Chinese game called Go—a game so complex that there are thought to be more possible configurations of the board than there are atoms in the universe. Yet none of these computers understands the purpose of a game or has a reason to play.
As impressive as these accomplishments are, they are still just a product of a computer’s special talent for pattern matching—extracting information from its database that enables it to answer a question or perform a task. This seems to be intelligent behavior only because a computer is excellent at that particular task. However, we rarely attribute human characteristics to other machines, such as boats that can “swim” faster or hydraulic jacks that are “stronger” and can easily lift a car above a mechanic’s head.
In many ways a game is a perfect environment for a computer. It has set rules with a certain number of possibilities that can be stored in a database. When IBM’s Watson played Jeopardy, all it needed to do was use natural language processing (NLP) to understand the question, buzz in faster than the other contestants, and apply pattern matching to find the correct answer in its database.
Early AI developers knew that computers had the potential to excel in a world of set rules and possibilities. Only a few years after the first AI conference, developers had their first version of a chess program. The program could match an opponent’s move with thousands of possible counter moves and play out thousands of games to determine the potential ramifications of making a move before deciding which piece to move and where to move it, and it could do so in a matter of seconds.
AI is always more impressive when computers are on their home turf—when the rules are clear and the possibilities limited. Organizations benefiting most from AI are those that work within a well-defined space with set rules, so it’s no surprise that organizations like Google fully embrace AI. Google’s entire business involves pattern matching—matching users’ questions with a massive database of answers. AI experts often refer to this as good old-fashioned artificial intelligence (GOFAI).
If you’re thinking about incorporating AI in your business, consider what computers are really good at—pattern matching. Do you have a lot of pattern matching in your organization? Does a lot of your work have set rules and possibilities? This work will be the first to benefit from AI.