Just Thinking, That’s All

Sunday, September 25th, Day 10

Advisory: This day’s blog is about things I was thinking about, not about what I was experiencing. As I was once told, “Reading about what you are thinking helps me fall asleep.” Don’t say I didn’t warn you!

Slept until 8:30am when I was awoken by the men’s chorus. Stayed in bed, dozing, thinking about my experiences so far.

  • I haven’t seen any street performers
  • I haven’t seen any beggars
  • What is the average age of people in the city versus the country?
  • What is the average income of city versus country?

The first week I was here, my experiences were all about new things: new language, new customs, new foods, new money. But there are other differences I am just beginning to recognize, differences that are things that I’m NOT seeing, things that I would find normal in the U.S. but which are absent here. Let’s call these “missing” differences.

It’s much harder for me to see “missing” differences. And I am struck by how statistical methods and artificial intelligence learning models don’t distinguish between these two sorts of differences and how they contribute to learning. For most algorithms, a difference is a difference. A difference is symmetric, commutative. The statement “x a member of A and x not a member of B” carries the same weight as “x not a member of A and x a member of B”. But in my experience of my own thought process, it seems that I pay much more attention (i.e. it contributes MORE to my learning) if I observe “x not a member of A and x a member of B,” where A is my upbringing and B is my new environment.

So, here I am in Chengdu, a new place, and I see very quickly the new things, which I attend to by categorizing and learning about them. But then, a week into the exercise, and I start to notice things that AREN’T in Chengdu.

There must be psychological research on the brain’s ability to see new things added versus old things removed. I’ll have to search the literature. Don’t introduction to psychology texts talk about an experiment that puts a tray of objects in front of a person for a minute, then ask them to recall all the objects on the tray? Didn’t that experiment also take away and add objects and ask the person what was added or taken away?

As I think about this, and other unexpected ways the brain behaves, I am reminded that building artificial intelligence can follow two paths: thinking like a human (which will have to include our biases), or thinking like a machine (without biases like the one I experienced when I first came to Chengdu). Statistics and statistical methods pride themselves on being unbiased. It is one of the strengths of the discipline, to see the world through universal eyes that do not depend on the individual. But that’s part of what makes us human and not machines, the messiness of poor data collection and poor data analysis.

Also, I was thinking about the ripples from the fundamental change of the single-child policy. This policy broke such a fundamental custom (family structure and procreation) that I wonder if it has allowed China to move away from tradition to adopt the rapid change we have seen since the 1980’s. How will the second-generation cohort of the single-child policy relate to the old traditions versus the new traditions? I have heard that the reaction so far to the two-child policy is “Why should I have two children? One worked just fine for me and my parents.” There is talk even about the Chinese government encouraging two children, to keep the population from becoming too heavily weighted on the aging, non-working population.

How do second-generation children, now working adults, getting married, view things versus their parents? Versus their grandparents? I would love to know what the discussion was concerning the decision to put the single-child policy in place. Was it a desperate measure to save China from starvation and collapse? Or was it a calculated attack on the ancient institutions that keep China tied to its ancient culture? Or…

I am enjoying learning to write Chinese characters. It’s a lot of work, and a whole different language from spoken Chinese. It will be interesting to see if Chinese characters survive versus pinyin over the next couple generations. Will economic efficiency decisions drive out characters in favor of pinyin? Or perhaps computers become smart enough and fast enough that it doesn’t matter, because everything will be verbal and transcribed by computer. Do people write less carefully with the computer technology, relying on the computer to recognize what they are writing, people learning shorthand to get certain characters to appear faster? I see just that when I let people write Chinese characters on my tablet. They do squiggles, that trigger the right character to show up on the pick-list. I tried it myself, drawing circles, and the computer tried its best to find the character that matched my nonsense.

What percentage of time is spent in school teaching basic communication skills (reading, writing, speaking) here in China, versus the U.S., versus other cultures around the world?

10am Melissa called (Twice, but I didn’t hear the first time? I was in the kitchen with the teapot sizzling. Did I really not hear the phone ring 6 times? I heard it ring the second time she called, three times, as I poured out my tea and then got the phone.

Talked until 11:15am. Told her about the case of the tipping waste basket and my suspected visitor. Do I really have a rat coming into the apartment to check out what’s in my waste basket?

1pm Finished typing notes in my journal. Going to take a shower, brush my teeth, sweep the floor.



About jamescmarch

A child of the '50's in rural Pennsylvania, an adolescent of the '60's in southern California, and a political activist of the 1970's in northern California, I have been a husband, a college graduate, an expert witness, a banker, a father, a software entrepreneur, and a philanthropist. Today, I follow my heart by writing.
This entry was posted in Chengdu, China, Sep-Nov 2016. Bookmark the permalink.

4 Responses to Just Thinking, That’s All

  1. 4444for says:


    I love your pictures! They influence me in advancing the appreciation of my own assembly of vegetables before combining them into a beautiful sustenance.



  2. Ken Piotrowski says:

    I’m learning how to do this better. Have been sending my comments by email ! love you and miss you my brother !


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