Three open problems in AI

Abstract

Reading and understanding books is a quintessentially human activity. It is the process by which much knowledge transfer occurs from generation to generation. For example, we test students’ understanding of a given subject by asking them to answer questions at the end of the chapter in a textbook. In general, we are satisfied if a student correctly answers 80 to 90% of the questions. When a computer can do the same task, we will have arrived at a significant milestone. A human being who starts reading at age 4, lives to be 100 years old, and reads a book a day every day could complete 35,000 books in a lifetime. By many estimates, the total number books ever written in all languages is under 100 million. Harvard library has around 12 million volumes. The Library of Congress has fewer than 30 million volumes. All the unique titles in the OCLC member libraries is under 42 million. However, US libraries do not have most of the books published in other languages internationally, thus leading to an approximate estimate of 100 million books ever published. Once a computer can read one book and prove that it understands it by answering questions about it correctly, then, in principle, it can read all the books that have ever been written. This has led to the speculation that once computers can read, understand, and share knowledge with each other, without the limitations that biology imposes, they will begin to exhibit super human intelligence. For a machine to read a book, understand it and answer questions about it, it needs mechanisms