Mathematical Recipes Revealed: Oh, Oh, Trouble

August 26, 2018

I don’t read the Times Literary Supplement. When I worked in London, I was able to flip through the printed version. In Harrod’s Creek, nope. I did spot a link to an essay with the snappy title “God Is in the Machine.” I took a look.

The write up belongs to the genre of non fiction essays which I call “Yep, that’s all there is.”

The focus is how algorithms work and why some are simple and others are complicated.

Think of the essay as explaining how math works to people who know right off the starting block who Eratosthenes was.

The main point of the first chunk of the write up is that algorithms are recipes, procedures which are implemented one at a time. The input yields an output.

The guts of the argument surface in this passage, attributed to a real algorithm wizard:

The researcher knew, of course, what data he’d fed into the process. He knew why he’d designed it, the problem it was trying to solve and the outputs that it produced. However, after he’d been trying to explain it for over an hour, he sat back in his chair, exhausted. “Yes, as you can see, the gap between input and output is difficult to understand,” he said. He’d flooded the algorithm with a huge amount of information, “a trend”, he said, because in the tech giant he could, and everyone did. But the amount of data meant it was hard to tell what the salient inputs within it were. “From a human perspective you’re not sure which of the inputs is significant; it’s hard to know what is actually driving the outputs. It’s hard to trace back, as a human, to know why a decision was made.”

The complexity emerges when:

  1. Algorithms are stuck together
  2. Data (which may or may not be consistent, accurate, or timely) are stuffed into the numerical recipe as “inputs”
  3. Outputs which may or may not be what the user understands, wants, or can use.

The complexity is manageable if the creator or numerical poets are, what the essay calls, “rigorous.” Is rigor possible in Silicon Valley with professionals who focus on mobile phones, laptops, and lunch options?

Where’s this going?

Not surprisingly, I will have to read a forthcoming book called The Death of the Gods. Like other clarion calls to the use of numerical recipes to do what humans once thought they could do with sufficient education, experience, and judgment, numerical recipes can do—algorithms are the future.

Questions I want toss out when I meet with my research team next week: What if the algorithms are already in charge? Are search results objective? Can you explain why some data are not available from commercial sources? What control do you have over content when ads and “information” are freely mixed?

Perhaps the numerical recipe mechanisms are locked and loaded and firing millions of times a day? What if few hear, know, or understand that the big guns are blazing without sound or a flash? What if people do not care?

Stephen E Arnold, August 26, 2018

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