It's movie logic. Anything with a 90% chance of happening actually happens 100% of the time, but anything with a one-in-a-million chance also happens 90% of the time.
There's a wonderful fourth-wall-breaking parody in the Discworld novels in which a group tries to pull off a daring scheme by making the odds worse, because they know it should work if the odds are exactly one in a million (neither more nor less).
I think this is intended. The director who committed the murder said the tests showed he wasn't violent, and the doctor's son isn't all he was promised to be. The tests are being taken as gospel without a good basis is part of the point, that people are being written off based on flawed metrics without actually giving them a shot.
There’s an element of this that’s tongue in cheek but I took the movie’s message as a whole to be “free will and grit conquer all” and it sort of side stepped the question of those things being genetic. (My suspicion is that development opens up a whole can of worms that again makes genetic prediction loose by default) I don’t think by design it was written with the intent of saying the tests don’t even work. I could be wrong.
I think you're right about a lot of things here, but I take issue with your framing of the shallow story as willpower versus strength. It's not willpower versus strength, it's adventure versus safety. The whole society is built on safety, and your favorite line is not about willpower; it's about his brother's failure to be adventurous. I knew I'd win because you would always keep a reserve, a margin of safety.
It's what we're seeing today. Gattaca is an allegory for the AI economy.
Which is why this film is still interesting, the prescience of it, as we embrace the AIs that will do our thinking for us, and as curiosity is soon to be punished or bred out of us.
This is a perhaps just a nuance of the film’s more overt message.
The same “sloppy” logic applies to most jobs today that require college degrees. “We’ve found that degree holders probably perform better, so now it’s mandatory to have a degree, despite the job not needing advanced mathematics etc. except Joe, he’s the best at this job, even though he doesn’t have a degree and would never get hired now”
By extension favoring/excluding an ethnicity, gender etc. because of “likelihood” of better performance.
Groups of people inevitably want to lump people into neat columns that make good/bad decisions easy regardless of facts. (I even just did it there)
Thanks for making me think about this movie again and its message, I always thought it was about how new electric cars should really be reproductions of classic cars with new powertrains. 😜
I loved your analysis. Now, I think this film is a warning about mindlessly using AI. People now just check the algorithm or search result, and then they take it as given. There is no curiosity or pursuit of something deeper. Not even to fine tune the programs It’s all a black box anyway, so who knows and as you said there is no desire to figure out “how [things] truly are.”
Great until the bit about Greece. For instance, pretty famously there was a debate about the definition of a man. Plato called man a featherless biped, so Diogenes plucked a chicken, brought it and said, “Behold! A man.”
There absolutely was falsifiability, that’s how the dialogs work. It’s also what predicated scholasticism and the scientific method.
In contrast, all of the scientific method begins and ends in syllogism, not data. What you’ve identified is a fallacious major premise: that 90% is the same as “all.” Potentially several implied in the film: hasty generalisation, cherry picking, overfitting, false causality, survivorship, ecological, etc.
A deeper dive might be where and when they commit basic fallacies in the film on the data front and how, precisely, this is as much about an inability to reason as it is about empiricism.
This is the sort of pedantry that I love and everyone around me hates
I also hate it.
I do too but it sits in my brain and eats away until the brain damage causes me to talk about it to someone.
It's movie logic. Anything with a 90% chance of happening actually happens 100% of the time, but anything with a one-in-a-million chance also happens 90% of the time.
There's a wonderful fourth-wall-breaking parody in the Discworld novels in which a group tries to pull off a daring scheme by making the odds worse, because they know it should work if the odds are exactly one in a million (neither more nor less).
https://wiki.lspace.org/Million-to-one_chance
Huge fan of Discworld.
I agree I am a lesser person for digging too much into the how.
I thought this WAS the theme of the movie. :)
I have been checkmated.
I think this is intended. The director who committed the murder said the tests showed he wasn't violent, and the doctor's son isn't all he was promised to be. The tests are being taken as gospel without a good basis is part of the point, that people are being written off based on flawed metrics without actually giving them a shot.
There’s an element of this that’s tongue in cheek but I took the movie’s message as a whole to be “free will and grit conquer all” and it sort of side stepped the question of those things being genetic. (My suspicion is that development opens up a whole can of worms that again makes genetic prediction loose by default) I don’t think by design it was written with the intent of saying the tests don’t even work. I could be wrong.
"Breaking Bad is a prequel to Malcom in the Middle"
Whoa 😲
Beautiful. No notes. Subscribed.
In the world one often has to make things happen.
I think you're right about a lot of things here, but I take issue with your framing of the shallow story as willpower versus strength. It's not willpower versus strength, it's adventure versus safety. The whole society is built on safety, and your favorite line is not about willpower; it's about his brother's failure to be adventurous. I knew I'd win because you would always keep a reserve, a margin of safety.
It's what we're seeing today. Gattaca is an allegory for the AI economy.
Regurgitating AI is all about the mediocre, the commonly accepted, and the safe answer.
Which is why this film is still interesting, the prescience of it, as we embrace the AIs that will do our thinking for us, and as curiosity is soon to be punished or bred out of us.
This is a perhaps just a nuance of the film’s more overt message.
The same “sloppy” logic applies to most jobs today that require college degrees. “We’ve found that degree holders probably perform better, so now it’s mandatory to have a degree, despite the job not needing advanced mathematics etc. except Joe, he’s the best at this job, even though he doesn’t have a degree and would never get hired now”
By extension favoring/excluding an ethnicity, gender etc. because of “likelihood” of better performance.
Groups of people inevitably want to lump people into neat columns that make good/bad decisions easy regardless of facts. (I even just did it there)
Thanks for making me think about this movie again and its message, I always thought it was about how new electric cars should really be reproductions of classic cars with new powertrains. 😜
I loved your analysis. Now, I think this film is a warning about mindlessly using AI. People now just check the algorithm or search result, and then they take it as given. There is no curiosity or pursuit of something deeper. Not even to fine tune the programs It’s all a black box anyway, so who knows and as you said there is no desire to figure out “how [things] truly are.”
Great until the bit about Greece. For instance, pretty famously there was a debate about the definition of a man. Plato called man a featherless biped, so Diogenes plucked a chicken, brought it and said, “Behold! A man.”
There absolutely was falsifiability, that’s how the dialogs work. It’s also what predicated scholasticism and the scientific method.
In contrast, all of the scientific method begins and ends in syllogism, not data. What you’ve identified is a fallacious major premise: that 90% is the same as “all.” Potentially several implied in the film: hasty generalisation, cherry picking, overfitting, false causality, survivorship, ecological, etc.
A deeper dive might be where and when they commit basic fallacies in the film on the data front and how, precisely, this is as much about an inability to reason as it is about empiricism.
Why should you think badly of yourself for thinking these things? By which standard are they bad?
Why should you think badly of yourself for thinking these things? There are others out there (here?) like you. By which standard are they (we?) bad?
Fun trivia, the nurse in the early scene was actually Maya Rudolph in one of her first roles.
It makes sense that the one person who actually treats Vincent like a person is the staff Doctor. He's had to actually study the numbers.