Mathiness: Better Than Hunan Chicken?
July 6, 2020
I am thrilled when one of my math oriented posts elicits clicks and feedback. Some still care about mathematics. Yippy do.
I read “Why China’s Race for AI Dominance Depends on Math.” The article comes from one of those high-toned online publications of mystical origins and more mythy financial resources.
The main point of the article is that China may care more about numbers than Hunan chicken. I noted this statement:
Dozens of think tank projects and government reports won’t mean anything if Americans can’t maintain mastery over the fundamental mathematics that underpin AI.
The write up disputes the truism “it’s all about the data.” The article stated:
Yet without the right type of math, and those who can creatively develop it, all the data in the world will only take you so far
Now that’s an observation which undercuts what some might call “collect it all” thinking. The idea is that the nugget is in “there” somewhere. And at some point in time systems and software will “discover” or “reveal” what a particular person needs to complete a task. That task may be the answer to the question, “What stock can I buy cheap today to make a lot of money tomorrow?” to “Who helped Robert Maxwell’s extremely interesting daughter hide in New Hampshire?”
Years ago I was on the advisory panel for a company called NuTech Solutions. The founder and a couple of his relatives focused on applying a philosophical concept to predictive methods. The company developed a search system, a method for solving traveling sales person-type problems, and a number of other common computational chestnuts. The methods ranged from smart software to old-fashioned statistical procedures applied in novel ways.
Tough sell as it turned out. On one call in which I participated, I remember this exchange:
Prospective Customer: Would you tell us how your system works?
President of NuTech: Now I think we will not make a sale.
Prospective Customer: Why is that?
President of NuTech: I have to write down equations, and we need to talk about them.
Yep, math for some is not about equations. Math is buzzwords. I mentioned to a college medical analytics professor who asked me a question about what I was working on. I replied, “I have been thinking about Hopf fibration.”
Crickets. He changed the subject.
The write up (somewhat gleefully) it seemed to me, stated:
American secondary school and university students are not mastering the fundamental math that prepares them to move into the type of advanced fields, such as statistical theory and differential geometry, that makes AI possible. American fifteen-year-olds scored thirty-fifth in math on the OECD’s 2018 Program for International Student Assessment tests—well below the OECD average. Even at the college level, not having mastered the basics needed for rigorous training in abstract problem solving, American students are often mostly taught to memorize algorithms and insert them when needed.
If true (and I have only anecdotal evidence obtained by watching young people try to make change at Walgreen’s), the idea that “insert them” is going to create some crazier stuff than Google selling ads for fast food next to a video about losing weight.
My team and I did a job for the University of Michigan before I retired. The project was to provide an outsider’s view of what could be done to make the university rank higher in math, computer science, and related disciplines. We gathered data; we interviewed; and we did on site observations. We did many things. One fact jumped out. There were not too many Americans in the advanced classes. Plus, the very best students in the advanced programs stayed in lovely Michigan. Thus, instead of setting up a business near the university, there folks headed to better weather and a more favorable venture capital climate. Yikes. These are tough problems for a university to fix easily and maybe not be able to remediate in a significant way. Good news? Yep, I got paid.
The essay grinds forward with the analysis. The essay ended with this statement:
Winning the AI competition begins by acknowledging how poorly we do in attracting and training Americans in math at all levels. Without getting serious about the remedy, the AI race may be lost as clearly as two plus two equals four.
Now think about this article’s message in the context of no code or low code programming, one click output of predictive reports based on real time data flows, or deciding what numerical recipe to plug into a business dashboard for real deciders.
Outstanding work. Those railroad cars in Texas. Just a glitch in the system. The “glitch” may be a poor calculation. Guessing might yield better results in some circumstances. Why? Yikes, the answer requires equations and that’s a deal breaker in some situations. Just use a buzzword.
Stephen E Arnold, July 6, 2020
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