I just read AI: The Tumultuous History of the Search for Artificial Intelligence by Daniel Crevier. It was very interesting to see the different ways and methods that researchers approached AI as well as the problems that were faced in the early years of AI research. Here’s a quick look at one of the main problems encountered - the fact that understanding once concept or idea requires understanding of many or even all other concepts as well.

The main problem that was encountered is that it is nearly impossible to define a single concept without understanding many other concepts. For example, to understand the meaning of the word car you have to understand about wheels and driving and people and locations and distances, etc. This is what mathematician-philosopher Gottfried-Wilhelm Liebnitz said in the 17th century when trying to develop a method to formalize thought: “There is no term so absolute or detached that it contains no relations and of which a perfect analysis does not lead to other things or even all other things.” Which means that to understand any concept you need to understand many other concepts if not all other concepts.”

This problem manifested itself in many ways. First, early AI researchers were very limited by the amount of memory in computers at the time. One example is a project a student worked on to try to analyze sentences. Since understanding any one word requires understanding of many other words, there was nowhere near enough room in memory to attempt anything. In fact, he only had enough room in memory for definitions of about 4 words.

To avoid this problem, researchers worked on projects in limited problem spaces. In this way there was a limited number of concepts available and it was possible to write a program that could understand them all. At MIT they worked on a project called Micro Worlds where a robot would move colored cubes and pyramids around a room. For this all it had to understand was colors, shapes, and the robots functions. This program worked really well but it was very difficult to expand it to work in a more general environment.

Finally, even when memories increased enough to make things like the sentence understanding program more feasible, researchers were still trying to hand code these definitions and things into the program. However if understanding one concept could require understanding of all other concepts, programming them all in could take forever. Finally in the mid 1980s the researchers realized that it would be impossible to program all concepts by hand and the computer needs to be able to learn on its own to”completely automate the knowledge acquisition process.”