Tuesday, 18 June 2013

Everyday prediction of the growth of knowledge (or is it?)

I received the following response to my last post:

When deciding to research a topic, a person may decide that he expects to learn more about a particular subject by using his computer than by reading a book.

But as you point out, it is a contradiction to perfectly know which path to new knowledge is best, because one would have to know all the possible states of knowledge we could possibly have (ahead of time!) to decide perfectly which path we should take. But if we had the knowledge ahead of time, then we wouldn't need to develop it. Instantaneous (timeless) knowledge growth would seem to violate a law of physics.

But when we decide to research a topic using a computer rather than a book, we conjecture a path to new knowledge that we expect to be more efficient. This knowledge is not assumed to infallible, which leads to the above contradictions. One could call a person's ability to guess which path to new knowledge is faster his relative "depth of knowledge". Like other forms of knowledge, knowledge about how to create knowledge is conjectural.

People do form expectations (make predictions) about which type and amount of knowledge will be forthcoming utilizing different techniques, with better accuracy of their predictions depending on their depth of knowledge.

Unless depth of knowledge is a myth, people can form expectations about what will help them learn a particular type of knowledge in a way that is better or faster.  So people can form reasonable expectations about what they will learn.  Can't they?

The argument seems to be that we can predict the effectiveness of different ways of creating knowledge, and we can do this more or less accurately depending on how good are our ideas about it - suggesting that there is an objective form of predictive knowledge about the growth of knowledge itself. One thing to notice about this form of knowledge is that it only allows us to predict at a kind of meta-level. It doesn't say what I will learn in the future - only that (say) the computer will be more helpful than a book.

But more importantly, this argument seems to have assumed that the case against predicting the growth of knowledge is only against infallible prediction. By this account, fallible prediction is possible: I could say the computer would be helpful in my research, and while I might be wrong, this would still be a better conjecture than, say, that watching the Simpsons (or any other  unrelated activity) would be helpful.

http://thumbnails.illustrationsource.com/huge.25.125786.JPGThere is a crucial difference being overlooked here, and it is not about fallibility. A prediction of how a chemical will react on being exposed to air might be wrong. But this would be because some aspect of the theory that produced the prediction was wrong, or because a measurement (or a background assumption) was wrong. Similarly, the truth of the explanatory theory that the computer is a better source for my research project depends on aspects of the computer and the nature of the research. Yet the predictive claim that I will create more new knowledge if I use the computer is a different thing entirely. I could be right about the former, non-predictive theory about the usefulness of computers, and still be wrong about the latter: I might still learn less by using the computer, for any number of other reasons. For example, it might lead me to get a Facebook account or a video game and spend the whole day procrastinating. Or I might find a wealth of information about another topic and change my whole direction of research. Or I might commit to my original topic and complete the project, with the result that it only impedes the growth of knowledge, because the finished publication perpetuates a violent political ideology.

The problem with predicting the growth of my own knowledge is that it depends not only on objective, unchanging factors, but also on whether I will change my mind. And this is not something I can predict without having the relevant knowledge already. It is true that the more I know about why the computer will be useful and what I will find there, the less my prediction that I will learn more depends on whether I will change my mind. But again, to the extent that I have detailed expectations about what I will find on the computer, this is not a prediction of the growth of knowledge so much as a theory about what information is available on computers.

No comments:

Post a Comment