A friend recently introduced me to a writer who has achieved worldwide fame and respect for a couple of his books, most notably Tipping Point and Blink. I became quite interested in what he has had to say after viewing a short clip of his views on the GFC, so I got myself a copy of his Blink to read while commuting to and fro work.
Malcolm Gladwell is a Canadian writer who lives in New York. His works are mostly short, “research” and “data” filled commentaries on many subjects, most commonly on social sciences. In Blink – The Power of Thinking Without Thinking, he explores the theory that we very rapidly make subconscious decisions and intepretations and use them to make decisions. His arguments are largely based on studies and tests done by others into fields such as marital interaction, social studies, human intuition and prejudices. If you are interested in this sort of thing, I’d suggest not to purchase his work. It’s a silly and glorified case of obsurdity that most people should be smart enough to realise that the author is a man of typical American religious naivety.
Gladwell’s theories are formed under studies and evidence he has gathered. One example is particularly notable.
A group of so called “scientists” did a study on gamblers. They placed four decks of cards, two blue and two red, on a table and asked someone to turn them over. Each card either won or lost the gambler some amount of money. The cards were rigged in a way such that the blue cards were, on a whole, optimal for winnings and generally produced favourable results with steady winnings and modest penalties, and the red cards were a minefield – having high rewards but higher losses. This team of “scientists” then measured how quickly the test subject noticed what was occuring by measuring the sweat glands on their subject’s skin. They found that the gamblers generally began to notice what was happening within about 50 cards. They also noticed that the gamblers started generating stress responses to the red cards by the 10th card.
His conclusion was that the gamblers “figured the game out before they realised they had figured the game out…long before they were consciously aware of what (was occuring)”.
This is the classic example of over-simplification and over-assumption – something I’d like to term “Gladwelling”. A completely plausible and much simpler explanation for these results would be that the gamblers correctly felt that the red cards had more risk. That is, more variance. Higher risk results in more shock, nervousness and emotion, which explains the readings. The subjects’ reactions may well have been a simple adverseness to risk, rather than a lower overall return.
What does this have to do with hi-fi?
Because this sort of thing happens all the time. People over-simplify the world despite the fact that there are clear reasons why we don’t just compare two figures to determine the properties of two real world things. Why does a Japanese sports car cost 1/5th of the price of an Italian thoroughbred, even though on paper they have nearly the same performance specs? Which idiot would buy a Leica camera if its specs were only as good as a Canon or Nikon? People need to read between the lines.
The fact that people say “X branded amplifier is more conservatively rated compared to Y branded” is in itself, proof that comparing specs is a silly exercise. If specs can be made to be more or less conservative, then their integrity is lost and scientifically speaking they are completely pointless. To me, a specification should be a standardised, strictly controlled way of measuring an extremely simple factor. RMS power, for example, should be true RMS and never “short term”. The whole idea that RMS could be “short term” is silly, since Root Mean Squared requires the signal to be evaluated over the longest possible period. Anything less is a compromise, and completely eliminates any science behind the figure.
Another thing that bugs me is the way people draw conclusions from “evidence”. I often find articles on the net from studies which show a whole range of ludacris “relationships”. For example, the other day I read a study which showed that obesity causes depression. Sure, there are tests which indicate that obesity is linked to depression. But how does one draw the conclusion that it is obesity which causes depression and not the other way round? How does one draw the conclusion that it is not a third factor which may be causing both, for example a gene or a mental health issue?
Anyone who has a basic understanding of statistics and sampling analysis would understand the concept of “data mining”. Additionally, the fact that even if a link is proven mathematically true, there can be no straightforward “cause-effect” conclusion without extensive further investigation.
In hi-fi, this is all too common. We draw conclusions based on the tiniest, most meaningless figures. The world is too complex to be represented by a set of numbers on a page. Don’t be a fool – question everything. Don’t be Gladwelling your view of the world.