“Thinking” Machines
In the early and middle years of the 20th century, as mankind made strides in the brand new field of computer science, researchers began to wonder if they could create a machine with human-like intelligence—a mechanical brain to rival or even surpass biological brain-power.
Early work was promising, and computers were soon playing chess and checkers against human opponents. But the successes were short-lived, as scientists found that beyond simple pattern-matching as in a game of tic-tac-toe or chess, the mysteries of human intelligence and thinking were far too complicated to replicate directly in a computer program. The attempt to duplicate human intelligence—to make a computer emulate the unique human spirit that sets mankind apart from the animal world (Job 32:8)—has proved to be far more complex than was first imagined.
But there has been a renaissance in the realm of artificial intelligence in the 21st century, even as researchers have given up trying to model human intelligence and its approach to problem solving as a means of achieving artificial intelligence. Instead, they are harnessing the power of data processing and statistical probabilities. The result has been the creation of machines that not only take in vast amounts of data, but that also learn from the data, inferring connections among bits of information by finding patterns and relationships of cause and effect.
The consequence has been that, while machines do not yet replicate actual human thought processes, they can—in ways all their own—produce very “intelligent” results. This has led to such a wide range of technical and commercial advances that, if you live in the developed world, AI is probably not some abstract concept far distant from you. When you read your e-mail or use your car’s navigation system or change the filter in your refrigerator—or in so many other ways—AI is probably already a part of your daily life!