Machine learning and magic [ Or, Big Data and magic]

Machine learning and magic by John D. Cook.

From the post:

When I first heard about a lie detector as a child, I was puzzled. How could a machine detect lies? If it could, why couldn’t you use it to predict the future? For example, you could say “IBM stock will go up tomorrow” and let the machine tell you whether you’re lying.

Of course lie detectors can’t tell whether someone is lying. They can only tell whether someone is exhibiting physiological behavior believed to be associated with lying. How well the latter predicts the former is a matter of debate.

I saw a presentation of a machine learning package the other day. Some of the questions implied that the audience had a magical understanding of machine learning, as if an algorithm could extract answers from data that do not contain the answer. The software simply searches for patterns in data by seeing how well various possible patterns fit, but there may be no pattern to be found. Machine learning algorithms cannot generate information that isn’t there any more than a polygraph machine can predict the future.

I supplied the alternative title because of the advocacy of “big data” as a necessity for all enterprises, with no knowledge at all of the data being collected or of the issues for a particular enterprise that it might address. Machine learning suffers from the same affliction.

Specific case studies don’t answer the question of whether machine learning and/or big data is a fit for your enterprise or its particular problems. Some problems are quite common but incompetency in management is the most prevalent of all (Dilbert) and neither big data nor machine learning than help with that problem.

Take John’s caution to heart for both machine learning and big data. You will be glad you did!

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