I was not aware of the Doomsday argument but it feels nice to have come up with it independently

What happens when really old advice meets really new technology?

A recurrent neural network (like the open-source char-rnn framework used here) can teach itself to imitate recipes, paint colors, band names, and even guinea pig names. By examining a dataset, it learns to formulate its own rules about it, and can use these rules to generate new text that - according to the neural network - resembles the dataset. But since the neural network is doing all this without cultural context, or any knowledge of what the words really mean, the results are often a bit bizarre.

In this example, the dataset is a list of more than 2000 ancient proverbs, collected by reader Anthony Mandelli. Some of these are well-known, such as “You can lead a horse to water, but you can’t make it drink.” and “Where there’s a will, there’s a way.” Others are frankly a bit strange: “Where there’s muck there’s brass.” and “A curst cow has short horns.” and “Be not a baker if your head is made of butter.”

What will a neural network make of this ancient wisdom?

If you answered “Really really weird proverbs”, you are correct.

A fox smells it better than a fool’s for a day.
No songer in a teacuper.
A fool in a teacup is a silent for a needle in the sale.
No man is the better pan on the hunder.
A mouse is a good bound to receive.
Do not come to the cow.

Some of them almost make sense:

A good wine makes the best sermon.
A good fear is never known till needed.
Death when it comes will have no sheep.
An ounce of the heart comes without an exception.
A good face is a letter to get out of the fire.
No wise man ever wishes to be sick.
A good excuse is as good as a rest.
There is no smoke without the best sin.
A good man is worth doing well.
A good anvil does not make the most noise.

While others would be more difficult to pass off as real proverbs:

We can serve no smort.
A good face is a letter like a dog.
A good earse makes a good ending.
Gnow will not go out.
Ung.
A fox smeep is the horse of the best sermon.
No sweet is half the barn door after the cat.
There is not fire and step on your dog and stains the best sermon.
An ox is a new dogn not sing in a haystar.

One of the oddest things to emerge from the proverb-trained neural network is a strange obsession with oxen. I checked, and there were only three oxen-related proverbs in the dataset, yet they appear frequently in the neural network’s version, and usually as rather powerful creatures.

An ox can lever an enemies are dangerous and restens at home.
An ox is not to be given with a single stone.
An ox is never known till needed.
An ox is as good as a best.
An ox is not to be that wound is hot.
An ox is a silent for the gain of the bush.
An ox is not fill when he will eat forever.

Whatever the internal mythos the neural network has learned from these ancient proverbs, oxen are mysteriously important.

In this post I am going to show, with high probability, that humans will soon go extinct. How soon? I am thinking over the next few thousand years.

To set up my argument I’m going to use an analogy. Imagine a world of many, many countries: a huge number, say a million different countries. Instead of names, these countries have numbers: Country 1, Country 2, Country 3 and so on. You’ve been told that, as a general rule, the countries with larger numbers have much larger populations than countries with smaller numbers.

Scenario 1: You are an employer and you post an advert for a job. To your surprise, there is only one applicant and this applicant happens to be from Country 5. Why is this surprising to you? Two reasons: firstly in this world there are a million different countries, and yet the only applicant happened to come from a country so early in the sequence. (If you wanted to give this a p-value it would be p = 5/1000,000.) Secondly, the population of later countries in the sequence is much, much larger than the ones early in the sequence. There may be a factor of thousands or hundreds of thousands more people in Country 1000 compared to Country 5. This makes it far more probable for the applicant to be from Country 1000.

Although it is only a single data point, this should lead you to doubt the idea that there really are so many more people in high-number countries. Even if you drop the assumption of population increasing with country number and instead assume roughly constant population, it’s hard to explain why the applicant came so early on in the sequence. This should make you think that most of the world’s population is probably concentrated in Countries 1 to 10 without many people after that.

Scenario 2: Suppose the exact same world as in Scenario 1, with one minor change. Instead of an employer you are a baby, born in Country 5. You have just been born, and it is explained to you (you are a very smart baby) about how there are a million other countries each with progressively higher populations. By the same argument in scenario 1, you begin to doubt this.

I think this line of reasoning is correct. Ask yourself: why aren’t you the Queen? Simple: to become the Queen you need to have been born as the daughter of the former monarch of Great Britain and that is very unlikely. Why is it unlikely? Well because there is only one monarch, but millions of other people.

Scenario 3: The final scenario is similar to Scenario 2 except for one change: countries become centuries (or some other period of time), with the country number measuring time from the dawn of man. The “population” of each century is simply the number of people born in it. We transform variation throughout space to variation throughout time.

You are living around the year 2000. The population of the world is 6-7 billion. This is about 20 times bigger than the population living in the year 1000. How do we expect the population to evolve into the distant future, say hundreds of millions of years? One possibility is that humans go interstellar and spread out across the galaxy. That would likely involve a population explosion. Another possibility is that little technological progress is forthcoming and humans are stranded on Earth. That would probably involve population stabilising at 10 billion or so. In both cases humanity stays around for a very long time and the 21st century looks extremely close to the start of potentially hundreds of millions of years of human history.

The possibility of a population explosion corresponds to higher-number countries having larger and larger populations. The other possibility is analogous to countries having roughly constant populations.

The fact that you are here, conscious, in the 21st century means that both of these possibilities are very unlikely. This can mean only one thing: humanity cannot be far away from a cataclysmic event which either drastically reduces or entirely wipes out the human population.

I’m interested in the case of the person who interrupted a performance of Julius Caesar as a protest, because it shows clearly that my disagreements with many of my friends about disruptive but peaceful campus protests are genuine principled disagreements. I generally support disruptive protest more than they do.

Like, I understand why content-neutral place/time restrictions on speech are necessary. But “the free speech maximizing action is to get thugs with guns to punish a peaceful speaker” is a weird state of affairs and it needs to be treated with caution and care lest the US government does the thing it always does and starts oppressing people it doesn’t like.

She should have been removed from the theater but I think it is wrong to prosecute her.

I keep feeling silly for not rushing to do laundry exactly when it would be the optimal time to hang it outdoors, but it is actually just as eco-friendly and not-dryer-using and what have you if you hang it indoors, and then you get to do laundry at 1am on a rainy day when you realize that if you don’t do it you’ll be out of clean underwear.

Anthropologist writes book accusing tribe of being heartless savages.

Other anthropologists accuse him of slandering the tribe.

Tribe: “If Turnbull were to return to our land, we shall bury him alive!”