What the Machine Cannot Learn

If you have been hanging around Software much – you have been hearing about Machine Learning – probably over and over. This is something that makes some people pee in their pants, they are so excited about it. I hate to pee on their parade – but somebody needs to.

Machine Learning looks at Data, and the more data the better – and finds patterns in it. If you live in certain zip code, own an an expensive home, and are a woman – you are likely to buy expensive clothing. And the people who sell this clothing should concentrate their marketing on you.

This is obvious, but it is looking for correlations, that are not obvious – but work, anyway. Anything to make money.

A whole industry now concentrates on providing personal data for everyone under the sun. You and I are in their secret databases – and probably in a number of them.

This is a standard business practice – buy low and sell high. Get free (or low-cost) information, process it, and sell it for more – hopefully. much more. The market will determine the price – and there is a very active market.

The computer cannot look into people’s minds – and see the values there. But any small child can do this easily.

This is not for lack of trying. Every software company – and I mean every company – tries to understand people. And all have failed miserably. They predicted Hillary would win – and Trump won in a landslide.

The book Whiplash has some stunning examples of this:

“The future,” as the author William Gibson once noted, “is already here. It’s just unevenly distributed.”

The Computer is a machine – cleverly disguised to appear like a person. But it cannot be anything like a person – or a Chimp – or even a common weed in a ditch.

It is not living, and cannot be. It is made of different material (Silicon) and works in different ways. Not with neurons, but semiconductors. These are much faster – compared to people – but much stupider.

Let me repeat that – the Computer is much stupider than people are. No matter how much hype you hear to the contrary.

And you will hear plenty of it.


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