Chapter 4

The “ELIZA effect” described in preface 4 can be seen in the description of BACON in chapter 4. Researchers have exaggerated the program’s ability to make scientific discoveries. The process of sorting through different types of information and determining what is relevant (arguably the most difficult part of making a discovery) is already done for BACON.

In this chapter Hoffsteader describes some of the problems of representation. How is data determined to be relevant in a representation? He tells us that low level information will be quite irrelevant at the highest representational level. My question is: is the core of the conceptual sphere enough to represent the entire concept? The second problem of representation is organization. How do we organize information into a coherent structure? This problem seems intimately entwined with the question, what is it that perceives coherence? If we know something about the structure of what is doing the perceiving, we’ll know what sort of structure the data needs to be in. Both questions are hard to answer.

True AI will require a machine and program being able to sort out the relevant data for itself, to know that the colors of the flowers on earth aren’t as relevant to calculating its gravitational pull as its mass. Or, a program would have to know that the delicious type of food bacon is not relevant to its name as the man credited with the scientific method.