The Problem with "Resulting"
Hello there :)
Welcome to issue eighty six of Manufacturing Serendipity, a loosely connected, somewhat rambling collection of the unexpected things I’ve recently encountered.
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Part I: Things I’ve been thinking about…
“Don’t be so hard on yourself when things go badly, and don’t be so proud of yourself when they go well. Focus on process instead.”
~Annie Duke
This week I rediscovered this excellent interview with professional poker player, Annie Duke. (I originally shared this in a somewhat different context way back in September 2021, so some long-time subscribers may remember it.)
In the interview Duke talks about something called resulting:
“There’s this word that we use in poker: “resulting.” It’s a really important word. You can think about it as creating too tight a relationship between the quality of the outcome and the quality of the decision.
You can’t use outcome quality as a perfect signal of decision quality, not with a small sample size anyway.
I mean, certainly, if someone has gotten in 15 car accidents in the last year, I can certainly work backward from the outcome quality to their decision quality. But one accident doesn’t tell me much.
In chess, if I lose a game, it’s pretty certain that I made a bad decision somewhere and I can go look for it. That’s a totally reasonable strategy. But it is a very unreasonable strategy in poker. If I lose a hand, I may have played the hand literally perfectly and still lost because there’s this luck element to it.
The problem is that we’re all resulters at heart.
Think about the 2015 Super Bowl. The Seahawks are on the 1-yard line, they’re down by four, there’s 26 seconds left in the game, Pete Carroll has Russell Wilson throw and it’s intercepted. Do you remember what the headlines looked like the next day? “Worst play in Super Bowl history,” “What was he thinking?” “Idiot.” That kind of thing.
But imagine it was caught—what do you think the headlines would have looked like then? The outcome was irrelevant to the decision quality. And just as a teaser, the decision quality was actually pretty brilliant.”
I recognise this is a little tricky to parse, so I created the matrix below:
Further notes from the interview:
Why are we all resulters?
“Knowing the outcome infects us. We’re rational beings that think things are supposed to make sense. It’s very hard for us to wrap our heads around a bad outcome when we didn’t do anything wrong. Or that there’s a good outcome that’s just random. We’re really uncomfortable with randomness in that way. It’s just the way we’re built: to recognize patterns.”
How do we stop being resulters?
“If we know that outcomes infect us, we want to separate ourselves from outcomes as much as we possibly can when we’re thinking about decision quality.”
What’s the deal with focusing on processes?
Let’s return to the quote I shared at the beginning of this section:
“Don’t be so hard on yourself when things go badly, and don’t be so proud of yourself when they go well. Focus on process instead.”
~Annie Duke
I think what Duke’s referring to here is essentially a mindset shift.
If we want to understand the extent to which we’re making “great” decisions, and indeed make more “great” decisions in the future; rather than simply using outcomes as a barometer: great outcome = great decision; poor outcome = poor decision; we should instead consider more carefully the process we undertook in order to make the decision.
I suspect that asking questions like this might be helpful:
What factors actually impacted the success (or otherwise) of this outcome?
Were all of these factors foreseeable?
To what extent did luck play a part? (i.e. were any of these factors unforeseeable?)
To what extent did we consider the foreseeable factors in our decision-making?
Were there any foreseeable factors which we failed to consider at all?
What can we learn from this, and how can we incorporate these learnings into our decision-making process in the future?
Got thoughts or feelings about this?
I’d love to hear them — leave me a comment, or hit reply to this email :)
Moar serendipitous finds
“Assessment creep has spread way beyond academia. Likert seeps liquid-like into every crevice of everyday life, liquidating individuality in its aggregating force. It’s the disciplinary Panopticon that Foucault warned us about. At the grocery store’s self-service check-out, I’m asked to star-rate my experience. The coffee shop requests my five-scale rankings on the staff’s friendliness and the facility’s cleanliness. My healthcare provider is currently stalking me to Likert an appointment that got cancelled.
If assessment numbers confer worth, lack of numbers implies worthlessness. So now that I’ve retired, and the numbers have stopped coming, I’m appalled to find myself missing them. How do I have value, and know it, without them? How does anything? How can you enjoy an apple without comparing it to other apples? How do you dare to eat a peach without logging your experience?”
The love letter generator that foretold ChatGPT
Alan Turing and Christopher Strachey created a ground-breaking computer program that allowed them to express affection vicariously when so doing publicly, as gay men, was criminal…
“In the early 1950s, small, peculiar love letters were pinned up on the walls of the computing lab at the University of Manchester:
==
Darling Sweetheart
You are my avid fellow feeling. My affection curiously clings to your passionate wish. My liking yearns for your heart. You are my wistful sympathy: my tender liking.
Yours beautifully
M U C
==
Honey Dear
My sympathetic affection beautifully attracts your affectionate enthusiasm. You are my loving adoration: my breathless adoration. My fellow feeling breathlessly hopes for your dear eagerness. My lovesick adoration cherishes your avid ardour.
Yours wistfully
M U C
==
“These are strange love letters, for sure. And the history behind them is even stranger; examples of the world’s first computer-generated writing, they’re signed by MUC, the acronym for the Manchester University Computer.
In 1952, decades before ChatGPT started to write students’ essays, before OpenAI’s computer generated writing was integrated into mainstream media outlets, two gay men—Alan Turing and Christopher Strachey—essentially invented AI writing. Alongside Turing, Strachey worked on several experiments with Artificial Intelligence: a computer that could sing songs, one of the world’s first computer games, and an algorithm to write gender-neutral mash notes that screamed with longing.”
The Unexpected Poetry of PHD Acknowledgements
My goodness this is lovely! Not many people will read your PhD thesis, but if you completed your doctoral research at the Australian National University College of Science, then Tabitha Carvan has probably read one small part of it. What she found is a kind of poetry in the science:
“For a reason I can no longer remember, I started picking science theses at random from the Australian National University library catalogue and reading only the acknowledgements.
Once I started, it was very hard to stop.
Sometimes I found myself reading them at home, on my own time, always thinking, 'Just one more.'
[…]
I came to see that the acknowledgements of a PhD thesis are their own kind of thing.
The rest of the thesis contains careful, reasoned findings and figures, but on this one page, the author-scientist can release all the pent-up emotion they couldn’t express elsewhere.
They’re like an explosion in a lab.”
Komodo dragons have iron-coated teeth, scientists find
“With their huge size, venomous bite and the fantastical connotations of their name, Komodo dragons seem like the stuff of legend.
Now, that status has been elevated further: scientists have discovered that their teeth are coated with a layer of iron that helps keep their serrated edges razor sharp.
It is the first time such a coating has been seen in any animal, and one the researchers describe as “a striking and previously overlooked predatory adaptation in the Komodo dragon”.
The coating was discovered when researchers noticed that the tips and serrated edges of Komodo dragons’ teeth were covered in a layer of orange pigment. On closer inspection, the enamel was found to contain concentrated iron that makes the teeth extra hard and resistant to wear, helping the dragons rip and tear their prey apart.”
The ability to deceive is a feature, not a bug…
A fascinating read about the history of lie-detection, and its AI future.
“Ask people how to spot a lie, and most will say the same thing: Liars avoid eye contact. This belief turns out to be false. Human beings think they’re good at detecting lies, but studies show that they’re only slightly more accurate than a coin flip.”
You can find more of Val’s work on his website, and on Instagram.
Part II: Books I’m Reading Right Now
I’ve had very little time to read over the past few weeks! I promise there’ll be some recommendations in the next issue.
Part III: Things I’ve Been Watching
The Olympics :)
(Somewhat related, if you’ve been enjoying watching the swimming, you may or may not want to read this: The Dirty Secret of Olympic Swimming).
Part IV: What I’ve been up to…
Dad and I had a lovely time away, and I’m now staying with him helping him recuperate after his knee op.
What’s next?
I am excited about:
Being appointed as Editor-in-chief of Women in Tech SEO on a freelance basis — we’re working on something right now which I can’t wait to share with you.
Judging the Global Content Awards.
Hatching yet more plans for the second-half of the year.
Writing more stories! I’m a little behind right now, but I *think* I’ll still be able to get the full 100 stories written within the 100 days as planned :)
Moar shameless self-promotion
I’m emceeing WTSFest USA in Philadelphia on September 19th. The line up looks amazing, and there are still a few tickets available. Get yours before they’re gone.
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That’s all from me for now :)
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Please note, various life happenings are continuing to mess with my publishing schedule over the next month or so. The next issue of this newsletter will land in your inboxes towards the end of August.
Big love,
Hannah x
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