While hearing about the most and least wanted painting study
I was reminded of another study conducted in a very similar way. The study was centered around finding the
world’s funniest joke. The reason I
bring this up is that I think the study on comedy illustrates some of the flaws
in the study on paintings and some of the inherent difficulties in studying
that which is a matter of taste. You
will find the link to the study’s website here:
Basically the idea of the study was to have the general
public submit jokes to the website.
These would then be posted and voted on by visitors to the website. Some demographic data would be collected
while rating the joke. The world’s
funniest joke could be found from the highest ratings. Sounds simple enough, but there were some
problems with this set up, one of which was the issue of crude humor. To get around this each of the jokes was
screened by the website staff. This way
only clean jokes made it onto the web site.
I personally do not like crude humor, but many do. In filtering the jokes to be voted on the
website staff have completely done away with objectivity. You can see the result in the winning joke. It really isn’t very funny, in the same way
that the most wanted paintings were not particularly beautiful. In an issue of taste, can we censor that
which considered bad taste without sacrificing objectivity?
The very structure of these studies set the research teams
up for failure. Paintings cannot be
boiled down to checkbox elements. The
checkboxes do not account for the infinite variety of people’s personal
tastes. The checkboxes are the reason
why all the paintings look the same. I
am not a visual artist but I do know a lot more goes into painting that simply
combining different iconic elements. There
is gestalt to consider, and painting style.
There is that intangible transcendent quality that separates a
masterwork from other works of lesser quality and skill.
What are your opinions?
How could these studies be changed to provide better results? I am reminded of Isaac Asimov’s Hari Seldon. There is power in a large sample size, but
one must ask the right questions to produce meaningful data.
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