Three Myths of the Information Age
Every age has its characteristic myths, and the myths of the information age are about the power of organized information. A myth, unfortunately, is just a myth, and no matter how hard you believe in it a myth is not a good guide to action. In this article we'll look at three of the myths which are causing us Information Agers to waste a lot of our time.
The first myth is that all data is information. However, much data isn't even accurate, and even if it were accurate it wouldn't really be information. For a fact to constitute information it must help you make a decision. If you're deciding whether or not to buy a car, a knowledge of the operating principles of the Stanley Steamer, although it is automotive knowledge, is not going to play a big role in your decision. Nevertheless, people today insist on assembling databases in which they file every piece of information they can think of just in case it may be relevant.
The second myth follows from the first. It is the idea that all information is valuable. A corollary of this belief is that the more information you have the better. However, if you want to build a house you don't order enough bricks for twenty houses. If you did you'd have to figure out what to do with all those extra bricks. Similarly, if you pack your database full of information whose relevance is questionable you'll have to figure out what to do with all that information. The best you can hope for is that people ignore it. If they start basing decisions on irrelevant information, then you'll have real trouble.
The third myth is that information is immediately comprehensible. If you wanted to build a house, you wouldn't just order all the bricks, wood, shingles, windows, and so on, and assume that they would assemble themselves into a house. Nevertheless, many people think that if you collect a huge batch of information it will somehow analyze itself.
McLuhan feared that people would abdicate their intellectual functions to electronic technology, in the same way that they have abdicated too many of their locomotive functions to the automobile. Unfortunately, his fear seems to have been justified. As we have seen in the article on data mining, some software companies are even promoting (and many people are accepting) the idea that computers can analyze data all by themselves. That idea doesn't stand up to scrutiny, though.
To make sense of large masses of data you have to know mathematics, but computers know only arithmetic. They know how to calculate descriptive statistics, for example, and they know how to calculate regression weights, but they have no idea why they are doing these things.
Besides mathematics, you also have to know the goal you are trying to attain. You have to be able to postulate theoretical explanations of why your data behaves as it does. A computer, of course, can have no idea of goals or theories, let alone be able to generate them. In general, computers are clueless. No matter how sophisticated the software, a computer does nothing more than mindlessly carry out rules which have been programmed into it.
The arrival of the Information Age did not imply that the sun had set on the Age of Human Judgment. The less irrelevant information you have to consider, the more likely you are to notice the important information. The more attention you pay to the relationships in your data (instead of being insulated from the analysis, as one data mining software company promises to make you), the more likely you are to notice an important relationship. The computers on our desks do not give us a reason to put our minds in the drawers.