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Josh Knox

Just Joshin' #209 (Fair)

Published 10 days ago • 8 min read

Family Photo:
Fair Play

Last week, we attended a San Luis Obispo Blues baseball game with some friends from Leadership SLO. I thought this might be a good chance to teach Calvin and Lawrence about baseball - strikes and balls; fair and foul - but in the end it was a difficult venue to hold a conversation. Our group sat near the PA system, so the start of any discussion was punctured by 10-second music clips of player walk-up songs or sponsorship announcements.

It was fine though. The kids mostly ran around with the other kids, and everyone had a pretty good time. Lawrence even competed in the "Footloose Frenzy" competition, where all the kids' shoes were collected in a bucket and then the kids had to run barefoot onto the outfield, find their shoes from a pile, put them back on, and run back to foul territory. Lawrence was disadvantaged in this event in that 1) he was the smallest kid and 2) he doesn't know how to tie his shoes. He lost to a 12-year-old girl in flip-flops.

That didn't seem entirely fair.

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Kids shout "That's not fair!" so frequently that the idea would seem to be innate. But what does it mean?

The English word itself is one-to-one untranslatable into any other language: other languages have one-to-one translations with words like just or equitable, but fair is a category of its own. So what's the difference?

​From Bart Wilson's Fair's fair:​

[Linguist Anna] Wierzbicka makes a compelling case for the differences in meaning among fair, just, and equitable, which can be illustrated by the rules of another game.
​
When the NBA suspends players for leaving the bench to join a fight on the court, the question that sports commentators debate is "Are the suspensions fair?", not "Are the suspensions just?", nor "Are the suspensions equitable?" There's no moral first principle that tells us whether players on the bench should be allowed to join fights. Nor is the central issue whether all the players got punished equally. As Steve Pinker might note, the case for claiming that the words are different is simply that it doesn't feel right to substitute the words interchangeably in context after context, even if some contexts are ambiguous. The question then becomes, what are the common features of the contexts in which we feel uneasy using a word other than fair?
​
Wierzbicka's research indicated that there are two key contextual elements that make fair precisely the right word for the situation. First, the circumstances entail a tradeoff in welfare between individuals: some action benefits one person at the expense of another. The second element is that other people in the community think that there are limits to how much people are allowed to cost others in order to benefit themselves.
...
​
No matter how much we may feel that fairness is a pure principle, it's really a regular social rule, a custom. (Another surprispingly revealing word: you have probably seen the words "customary rates" applied to gratuities and sales commissions). Fairness really boils down to an issue of agreement: can we agree on what rules this particular context calls for?

Fair play.

Dad Joke:
Fair Response?

video preview​

Source: ESPN​

Highlights:
Are These Dice Fair?

​The geometry of weird-shaped dice | Skulls in the Stars [Thanks to Friend of the Newsletter Joel for the recommendation.]

[H]ow does one design dice with a weird number of faces? What mathematical strategies does one use to make them? What other types of dice are possible? And, perhaps most important: are these dice “fair”?

​84-Year-Old Kurt Vonnegut's Wonderful Letter to a Group of High School Students ​

Here’s an assignment for tonight, and I hope Ms. Lockwood will flunk you if you don’t do it: Write a six line poem, about anything, but rhymed. No fair tennis without a net. Make it as good as you possibly can. But don’t tell anybody what you’re doing. Don’t show it or recite it to anybody, not even your girlfriend or parents or whatever, or Ms. Lockwood. OK?
​
Tear it up into teeny-weeny pieces, and discard them into widely separated trash recepticals. You will find that you have already been gloriously rewarded for your poem. You have experienced becoming, learned a lot more about what’s inside you, and you have made your soul grow.

​Polishing the Apple: What ‘Dangerous Minds’ and Other Movies Get Right and Wrong About Teachers by Shea Serrano​

The first time this happened to me, it just really obliterated my whole everything. It was one of my special-ed students, this boy named Vincente — I taught him for seventh and eighth grade. He was incredible; possibly the most driven, most inspired kid I’d had up to that point. He never missed class, never missed an assignment, never did anything except try to be better than he was when he walked in. But he had a severe learning disability, one that wouldn’t let him process any problem that was designed for anyone more advanced than a first grader. At the end of his eighth-grade year, after I’d passed out the final report cards and the papers that said whether the students had passed or failed, he stayed around for a moment after I’d dismissed the class. He waited for everyone to leave. Then he walked up to me. He’d failed again. He looked me right in my face, blinked his gigantic eyes a few times, then said, “Mr. Serrano, I don’t think it’s fair that I failed. I try harder than everyone else. Kids who don’t work as hard as me passed. What do I do?” I didn’t have an answer. It felt like I’d been shoved out of a plane. I didn’t know what to do. All I could think about was not crying, which I wasn’t doing a very good job of. I will remember Vincente forever.

​Picture Limitless Creativity at Your Fingertips by Kevin Kelly​

At its birth, every new technology ignites a Tech Panic Cycle. There are seven phases:
1. Don’t bother me with this nonsense. It will never work.
2. OK, it is happening, but it’s dangerous, ’cause it doesn’t work well.
3. Wait, it works too well. We need to hobble it. Do something!
4. This stuff is so powerful that it’s not fair to those without access to it. ​
5. Now it’s everywhere, and there is no way to escape it. Not fair. ​
6. I am going to give it up. For a month.
7. Let’s focus on the real problem—which is the next current thing.

​How to Use AI Without Becoming Stupid by Cedric Chin​

English teachers spend a large amount of time grading essays and providing students with written feedback. Daisy Christodoulou is Director of Education at No More Marking, a provider of online comparative judgment software for schools. In a podcast interview in March earlier this year, she summarised what she’s found from more than two years of LLM experimentation with real world school grading systems.
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At first, Christodoulou’s team thought that LLMs could help with teacher marking directly. That is, give the LLM a student essay, and then have the LLM grade the essay and write the feedback. But of course LLMs were horrible at this.
...
​
So the next thing they did was to feed each piece of writing to the LLM to be comparatively judged twice, each way around. When they did that, they learnt that the LLM was mostly making these sort of “prefer the left-most essay” errors on essay pairs that were quite close to each in quality. This was a relief. It meant that they could set up the grading system such that essay pairs that are close in quality would go to a human, which would still cut down a teacher’s workload by a fair amount.
​
What should these teachers do with their free time? Christodoulou’s team wanted teachers to spend more time on feedback, which is actually what helps students improve.
​
Notice that this is consistent with the clause in the Vaughn Tan Rule: Christodoulou’s team was outsourcing subjective value judgments in grading to an AI, with the caveat that the most difficult pairs were still sent to a human grader. But they were making this tradeoff because they believed it was worth it: essay assessment is only part of the goal of marking; if they could do a ‘good enough’ job on this, they could free up the human teachers to give better feedback, which they judged to be more important.
​
So how did Christodoulou’s team approach the feedback task? Of course, the first thing they did was that they fed essays to an LLM and asked it for writing feedback. They quickly found that the LLM would produce these superficially impressive but ultimately very generic pieces of writing feedback. This was not helpful for student improvement. So it was unacceptable.
​
Next, they decided “ok, let’s have a human in the loop!” They fed the essays to an LLM and then let the teachers read the essay, read the AI-generated feedback, and edit the feedback before giving it to the student. Here, the teachers revolted. Every single teacher said “it takes more time to read the essay and the AI feedback and think about how to modify the AI feedback; by the time I’m done it would’ve been faster if I just read the essay and then wrote the feedback from scratch myself!”
​
This is known as the ‘Paradox of Automation’ — if you have a system that can get to 90-95% quality, getting a human operator to stay alert enough to spot the 5%-to-10% of errors is actually terribly hard; you would get better total system performance if you let the human do the entire task by themselves.
​
So what did they do next? Christodoulou’s team flipped the approach. First, they built a system where the teachers would be able to leave audio feedback whilst reading the essay. Then they set it up so that multiple teachers could leave audio comments on each piece. The important thing here was that teachers could be as harsh in their feedback as they liked, so that giving feedback was easier for them; they didn’t have to spend time softening their tone.
​
The system would then use AI to:
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- Transcribe the feedback into written form, and then
- Rewrite it to soften the tone based on a system-level prompt, and then
- Summarise the transcribed feedback for the student to call out common themes across multiple teachers who read the piece.
- And finally, most importantly, summarise across all the students, so that the teacher would know what issues to focus on in class!
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This approach works on at least two levels: first, teachers would be able to read — in their high-level report — “20 out of 35 students in your class had problems with tenses” and would then be able to change their lesson plans in response to that.
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Second, students feel ‘seen’ when receiving human feedback.

iamJoshKnox:
Handwriting Practice!

I used some Claude/ChatGPT credits to create and publish a series of handwriting books under the pseudonym Dottie D. Eye. My author copies arrive next week, I'm excited to see how the books turn out.

Available on Amazon Where Books are Sold:​
​Handwriting Practice for Kids Who Love... Dinosaurs! ​

Want to Be Interviewed?

I want to improve my interviewing skills:
​Please REPLY if you'd like to do a 30-minute interview with me for a Podcast that doesn't yet exist.

Or book some time on my calendar if there's anything else you'd like to chat about:
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Until next week,
​iamJoshKnox​​

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Josh Knox

Hi! I am Josh Knox. Read more of me here: 👇

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