EMPIRICALLY UNDERSTANDING UNDERSTANDING CAN MAKE PROBLEMS GO AWAY: THE CASE OF THE CHINESE ROOM

The many authors debating whether computer can understand ofttimes fail to clarify what understanding is, and no agreement exists upon this important issue. In his Chinese swing argument, Searle (1980) claims that computer running formal programs can not at any time understand. I discuss Searle's claim based upon a definition of understanding that is empirical, in the faculty of perception of being a theoretical statement leading to several testable hypotheses. I argue that an empirical definition with experimental support has a more solid footing than other definitions, and proceed on to discuss three hypotheses of particular relevance to the question of machine understanding, which revolve out to have considerable support in the literature from experimental psychology linguistics, and other fields. The hypotheses claim that (1) knowledge may not be straited to understand, (2) one may know all there is to know about X and still not understand X and (3) understanding take care ofs to reduce the search for relevant information. I also exhibit that understanding probably does not assume the causal powers of the human brain, and that computer can have intentionality in Searle's faculty of perception of the word. The article closes that what Searle discusses is not what speakers of English leave to when they say they understand, and plane if it were, his arguments would be unsound

You can know the name of a bird in all the languages of the world, on the contrary when you're finished, you'll know absolutely nothing whatever about the bird... with equal reason let's look at the bird and diocese what it's doing-that's what numbers I learned very early the difference between knowing the name of something and knowing something.

- Richard Feynman

The existence of a popular bourn does create some presumption in favor of the existence of a corresponding experimentally real conception but this does not at liberty us from the necessity of defining the class and of demonstrating the reality if the terminus is to be used for scientific purposes

- B F Skinner

Does it matter if computer understand? Computer do what they do and do not have the appearance to care what we call it. Still, at least since Linnaeus, and to an level greater extent since Mendeleyev's disentanglement of the periodic table, we know the value of classification-not just to order existing knowledge, on the other hand more importantly, to serve as a source of novel hypotheses (e.g., Emsley, 2001). Furthermore, it appear to bes the phenomenon of understanding must be tackled through anyone wanting to conduct a consistent analysis of puzzles related to knowledge. Psychologists whose starting point and primary interest has been behavior as similar appear to have shared this view (eg Kantor, 1926; Parrott, 1984; Skinner, 1957 1974) The question at issue of deciding whether certain computer operations should be classified as understanding is important because solving it can help us understand what understanding is.

It is surprising, then, that more ofttimes than not, the many authors debating whether computer can understand have failed to make clear what "understanding" means. Instead, discussions have frequently focused on a certain task, and asked if performing it is a demonstration of understanding. It present the appearances the debate would be more fruitful if things were done in the opposite order. In other words, we should first test to reach agreement concerning what it is we call understanding, and then put in motion on to whether or not an incident or a process belongs in that category. As drawn out as clear-cut criteria are lacking, discussions of that kind as the one regarding a computer's possible ability to understand cannot be settl and have the appearance destined to go on indefinitely. A pivotal contribution to the literature upon computer understanding is Searle (1980)

Searle's famous argument is based upon the fact that he does not understand Chinese. He asks his readers to believe that he is locked in a latitude and given two batches of Chinese writing. With the Chinese script, he is also given a put of rules in English. Searle (1980 p 418) continues:

Now presume also that I am given a third batch of Chinese signs together with some instructions, again in English, that enable me to correlate ultimate parts of this third batch with the first sum of two units batches, and these rules instruct me in what manner to give back certain Chinese tokens with certain sorts of shapes in replication to certain sorts of shapes given me in the third batch. Unknown to me the family who are giving me all of these representatives call the first batch "a script," they call the next to the first batch a "story," and they call the third batch "questions." Furthermore, they call the emblems I give them back in answer to the third batch "answers to the questions," and the put of rules in English that they gave me they call "the program."

According to Searle, proponent of "strong Al" (Al being artificial intelligence) would claim that by the agency of answering questions in Chinese the way he does, Searle in the Chinese compass is demonstrating that he understands the language. Searle himself argues that he obviously does not. Searle's (1980) treatment of understanding in humans and machines has become a classic, rated among the influential works in cognitive science-not, perhaps, because the article is unanimously regarded as a pat of genius, but because it has generated an almost unparalleled amount of discussion.