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I find the Idea of a Simpon’s Paradox fascinating because it represents one way that humans can incorrectly interpret data. It may simply be counterintuitive and not a paradox, but most people are incapable of telling the difference. Something that is true when the whole population is considered seems as though it should remain true within subgroups, which tends to be the case with most things encountered in everyday life. This casual inference is hard to combat because Simpon’s Paradox is rare enough that most people do not consider, but common enough to be more than a statistical anomaly.

 The authors argue that one should look for Simpon’s Paradox in fields they believe to be most relevant, but I did not see anything in the paper to suggest that I should trust that their claim of which studies are the most vulnerable. I believe most snapshot psychology studies to be inherently flawed because people are not static things and change both day-to-day and year to year. Psychological studies that about cognitive subjects like memory are acceptable at the snapshot level, but still vulnerable to Simpon’s Paradox.

I believe using programs like R to detect Simpon’s Paradox are useful tools but are not a viable solution. The issue does not stem from the data or programs that organize them, but the human that processes the data. A human brain can metaphorically be compared to a computer, but one has to remember that the human brain was created by accident. Learning how to compensate for the errors in human software would be more beneficial than trying to create a program to do it for us. For a program to absolve data of human errors and biases could be possible with a neuro-network, but both collection and interpretation of data would have to be done by AI, which as a general human enthusiast I believe to be more problematic than simply compensating for our species defects.