Learn about a new computer model that may have gotten us closer to figuring out how we choose our mates; why Meno’s paradox says you can’t ever learn anything new; and whether the Earth weighs the same as it did billions of years ago.
Learn about a new computer model that may have gotten us closer to figuring out how we choose our mates; why Meno’s paradox says you can’t ever learn anything new; and whether the Earth weighs the same as it did billions of years ago.
How do we choose our mates? A new computer model may have gotten us closer to the answer by Cameron Duke
Meno's Paradox Says You Can't Ever Learn Anything New by Reuben Westmaas
LISTENER Q: Does the Earth weigh the same as it did billions of years ago? by Ashley Hamer (Listener question from Rob in Cedar Falls)
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Find episode transcript here: https://curiosity-daily-4e53644e.simplecast.com/episodes/has-the-earth-lost-weight
CODY: Hi! You’re about to get smarter in just a few minutes with Curiosity Daily from curiosity-dot-com. I’m Cody Gough.
ASHLEY: And I’m Ashley Hamer. Today, you’ll learn about a new computer model that may have gotten us closer to figuring out how we choose our mates; and a paradox that says you can’t ever learn anything new. We’ll also answer a listener question about whether the Earth weighs the same as it did billions of years ago.
CODY: Let’s satisfy some curiosity.
Are computers capable of love? Probably not. Can they help us understand human love? Maybe. To find out how we choose our special someones, a psychologist has created computer avatars of real people to simulate the dirty work of finding a totally human mate.
To create his simulation, psychology researcher Dan Conroy-Beam began by recruiting several hundred real-world couples. They filled out surveys about their romantic preferences and the personality traits of themselves and their partners. Then, Conroy-Beam created computer avatars from that data. The avatars represented their coupled human counterparts as closely as possible, with one exception. These avatars were single and ready to mingle.
Next, Conroy-Beam ran a series of simulations, each based on a different model of mate selection. That way he could determine which theory of how we choose our mates actually leads these single avatars back to their real-world partners. The algorithms set rules for how the avatars should interact and behave with one another. When the avatars were all paired up, the algorithm is scored according to its real-world accuracy.
One of the models has the avatars pair with people that meet some set of minimum requirements, then only pair with someone else if they exceed that first partner’s stats. Another model is a little more old-fashioned: female avatars have many suitors and choose the one they like the best, but then ditch them when a better suitor comes along. A third model is basically the bar scene: the avatars choose partners entirely on physical attractiveness and nothing else.
Obviously, these models lack some nuance, so Conroy-Beam’s ultimate goal was to build and test his own algorithms in hopes of producing one that accurately reflects the complexities of human mate choice. And he came up with a model that beats all the existing ones.
He calls it the “resource allocation model.” It’s based on the idea that humans have a limited amount of resources, like time and attention, and that we choose the person we think is most deserving of these resources. That’s based both on their overall value as a mate and on how much they’re investing in us.
So are we going to be plugging in a set of preferences and having a computer reveal our soulmates any time soon? Don’t count on it. The most accurate model only seems to get it right about 45 percent of the time, so there’s still a lot of work to do.
If all else fails, we’ll still have Tinder.
Have you heard of Meno's Paradox? It’s an idea from ancient Greek philosophy that says you can’t ever learn anything new. Obviously, you’re listening to a podcast that helps you learn new things, so that idea might be a little troubling. But don’t worry — even though those Greek philosophers were smart, they weren’t always right.
To illustrate the paradox, let’s imagine you want to find out what the animal known as a tenrec [TEN-rek] looks like. (Also imagine you don’t have Google.) You go exploring through Madagascar looking for this animal. But even if you encounter one, you still won't know what a tenrec is after you see it — you'll just know that you saw something like a tiny hedgehog wearing a yellow hoodie. And if you already knew that’s what they looked like, then you didn't learn anything new by seeing one in the wild.
This is Meno's Paradox — either you already know something, so you can't learn it, or you don't know it, so you can't verify it. It first popped up in conversation with Socrates.
It seems to make sense. So does that mean we’re out of a job?
I’m happy to say that the answer is no. I mean, after all, humanity has learned a few things since Socrates' time. Like sandwiches. We didn't know what sandwiches were back then, right? So there must be some kind of loophole to the paradox.
Luckily for us, there is. There’s a big fallacy right in the middle of it. Let’s restate the paradox really quick: either you already know something, so you can't learn it, or you don't know it, so you can't verify it. In the first case “knowing something” means “the answer to your question.” If you already know the answer, you can’t learn it. But if you don’t know the answer, you can totally verify it. So that makes the paradox wrong. In the second case, “knowing something” means “the question you need to ask.” If you don’t know the question you need to ask, you can’t verify it. True! But if you already know the question you need to ask, can you learn something? Absolutely you can!
This commits the fallacy of “equivocation,” where one phrase is used to mean two different things. It makes things seem true, even when they aren’t.
So cheer up, Curiosity fans. It turns out you can learn all sorts of things after all.
We got a listener question from Rob in Cedar Falls, Iowa, who asks, “Does the Earth weigh approximately the same as it did a billion years ago? Or is it gaining or losing mass?” He follows up with, “Also, do Curiosity Daily fans have a name? If not, I think we should be called Curios. And then if you had an advisory listener board, you could call them the Curio Cabinet. I'm not even going to charge for that winning idea.” [ad-lib] CODY: I’d say curiosi-TEERS, but then it’s like, well, I hope nobody’s listening and crying tears… unless they’re so happy we made puns
Aaaanyway, back to your question. Has the Earth maintained its svelte physique over the years, or has its weight changed? I’m gonna be pedantic here for a second and say that actually, the Earth doesn’t really weigh anything: weight is a measure of force exerted on an object, and there’s no external force holding Earth down. What you’re wondering about is mass, a measure of the stuff that an object contains.
So, has the Earth gained or lost mass in the last billion years? Yes and yes! The vast majority of Earth’s mass has stayed put — what happens on Earth stays on Earth — but there are tiny amounts of stuff that are being added and subtracted on a daily basis. Our planet is always whizzing through space, and space is kinda dirty. It’s full of dust, ice, tiny meteors, and comet leftovers — and thanks to Earth’s gravity, we pull that debris into our atmosphere on a daily basis. If you add up everything that lands on our planet from space — from the tiniest ionized particles to the heftiest iron meteorites — it comes out to an added 43 tons of mass every day. Now, considering that Earth is about one quintillion times more massive than that, it doesn’t make much of a dent. But it’s there!
But Earth also loses mass every day. Our atmosphere is full of really light gases, like hydrogen and helium. These gases easily escape into space, so we lose about 300 tons of mass in the form of atmosphere every day.
So if you balance the Earth’s mass checkbook, we’re in the red. Earth loses around 55,000 tons (or 50,000 metric tons) every year. That is inconceivably tiny compared to our planet’s mass overall. One scientist said it was the equivalent of an elephant losing a red blood cell. So don’t let it hang heavy on your conscience. Thanks for your question, Rob! If you have a question, send an email or voice recording to curiosity at discovery dot com, or leave us a voicemail at 312-596-5208.
CODY: Before we recap what we learned today, here’s a sneak peek at what you’ll hear next week on Curiosity Daily.
ASHLEY: Next week, you’ll learn why when it comes to connecting during COVID, old tech beats new tech;
A frog that has noise-canceling lungs;
Why marijuana gives people the munchies;
And VERY SPECIAL Earth Day coverage featuring our interview with — wait for it! — Bill Nye. Yeah, we interviewed Bill Nye. And it was amazing.
CODY: Oh yeah, that’s right, I’d almost forgotten, we interviewed Bill Nye.
ASHLEY: Yeah, we did interview Bill Nye.
[ad lib some stuff]
ASHLEY: ANYWAY. Now, let’s recap what we learned today.
DAVID POGUE VERSION (BACKUP):
ASHLEY: Next week, you’ll learn about a trick for getting people to be less defensive;
Why marijuana gives people the munchies;
A slug that cuts off its own head when it wants a new body;
Why you listen to songs on repeat;
And more! We’ll also be presenting special Earth Day coverage, including tips and tricks for preparing for climate change, with best-selling author and CBS news correspondent David Pogue. For now, let’s recap what we learned today.
[ad lib optional]
CODY: Today’s stories were written by Cameron Duke, Reuben Westmaas, and Ashley Hamer, and edited by Ashley Hamer, who’s the managing editor for Curiosity Daily.
ASHLEY: Scriptwriting was by Cody Gough and Sonja Hodgen. Today’s episode was produced and edited by Cody Gough.
CODY: Have a great weekend, and join us again Monday to learn optimism for the future in just a few minutes. [something old, something new…]
ASHLEY: And until then, stay curious!