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posted by chromas on Monday January 14 2019, @02:22AM   Printer-friendly
from the Surely-you-jest,-Dr.-Feynman dept.

Probably not that good of an article, but it actually exists, only at Wired, so it is certain that it probably is worth reading. But only if you go in with no preconceptions.

Nobel laureate Richard Feynman once asked his Caltech students to calculate the probability that, if he walked outside the classroom, the first car in the parking lot would have a specific license plate, say 6ZNA74. Assuming every number and letter are equally likely and determined independently, the students estimated the probability to be less than 1 in 17 million. When the students finished their calculations, Feynman revealed that the correct probability was 1: He had seen this license plate on his way into class. Something extremely unlikely is not unlikely at all if it has already happened.

Bayesian probability is all well and good, until it runs up against actuality. But the point here is all about having a Beautiful Mind or π, and seeing patterns everywhere, and how if you see them in Big Data, the patterns are bigger. But no less crazy.

The Feynman trap—ransacking data for patterns without any preconceived idea of what one is looking for—is the Achilles heel of studies based on data mining. Finding something unusual or surprising after it has already occurred is neither unusual nor surprising. Patterns are sure to be found, and are likely to be misleading, absurd, or worse.

This approach to "science" can certainly lead to interesting results, as in this particular study:

A standard neuroscience experiment involves showing a volunteer in an MRI machine various images and asking questions about the images. The measurements are noisy, picking up magnetic signals from the environment and from variations in the density of fatty tissue in different parts of the brain. Sometimes they miss brain activity; sometimes they suggest activity where there is none.

A Dartmouth graduate student used an MRI machine to study the brain activity of a salmon as it was shown photographs and asked questions. The most interesting thing about the study was not that a salmon was studied, but that the salmon was dead. Yep, a dead salmon purchased at a local market was put into the MRI machine, and some patterns were discovered. There were inevitably patterns—and they were invariably meaningless.

Brings to mind (brains!) a certain Irish myth of the Salmon of Knowledge, and the parallel formation of the posthumous Salmon of Doubt by Douglas Adams.

The problem has become endemic nowadays because powerful computers are so good at plundering Big Data. Data miners have found correlations between Twitter words or Google search queries and criminal activity, heart attacks, stock prices, election outcomes, Bitcoin prices, and soccer matches. You might think I am making these examples up. I am not.

There are even stronger correlations with purely random numbers. It is Big Data Hubris to think that data-mined correlations must be meaningful. Finding an unusual pattern in Big Data is no more convincing (or useful) than finding an unusual license plate outside Feynman's classroom.

New Myth: Big Data and the MRIed Dead Salmon of Pattern Imagination.


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  • (Score: 2) by aristarchus on Monday January 14 2019, @09:32AM (1 child)

    by aristarchus (2645) on Monday January 14 2019, @09:32AM (#786384) Journal

    Why does a dog lick himself? Because he can.

    Two dudes watching a dog lick himself. One dude saysx, "I wish I could do that!" Second dude says, "I don't think the dog would let you."

    Probability is only ignorance quantified.

    Starting Score:    1  point
    Karma-Bonus Modifier   +1  

    Total Score:   2  
  • (Score: 2) by Muad'Dave on Monday January 14 2019, @05:49PM

    by Muad'Dave (1413) on Monday January 14 2019, @05:49PM (#786516)

    > Second dude says, "I don't think the dog would let you."

    I heard it as "That dog would BITE you!"