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Classified Thread 7

This is the…monthly? bimonthly? occasional?…classified thread. Post advertisements, personals, and any interesting success stories from the last thread.

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Commenter Tibbar used Mechanical Turk to replicate my survey on how people thought about the moral weights of animals.

After getting 263 responses (to my 50), he reports different results:

Chicken: 25
Chimpanzee: 2
Cow: 3
Elephant: 1
Lobster: 60
Pig: 5
Human: 1

On the one hand, Mechanical Turkers sometimes aren’t a great sample, and some of them seem to have just put the same number for every animal so they could finish quickly and get their money. They also probably haven’t thought about this that much and don’t have much of a moral theory behind what they’re doing. This makes them a different demographic than the people I surveyed, who were a mix of vegetarians and principled non-vegetarians who had thought a lot about animal rights. For example, 80% of my sample answered yes to a question asking if they were “familiar with work by Brian Tomasik, OneStepForAnimals, etc urging people to eat beef rather than chicken”.

On the other hand, this makes it pretty hard for me to claim my results are some kind of universal intuitive understanding of what animals are like. So I am partially retracting them (only partially, because of the consideration above) and adding this to my Mistakes page.

The best thing to do here would be to re-run my survey with a larger sample of a similar population, but unfortunately I’ve lost my chance to do that now that I’ve told you all this, so darn. Maybe I’ll include it on next year’s survey anyway and hope you’ve forgetten by then.

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Yesterday’s post reviewed research showing that animals’ intelligence seemed correlated with their number of cortical neurons. If this is true, we could use it to create an absolute scale that puts animals and humans on the same ladder.

Here are the numbers from this list. I can’t find chickens, so I’ve used red junglefowl, the wild ancestor of chickens. I can’t find cows, so I’ve eyeballed a number from other cow-sized ruminants (see here for some debate on this).

Animal # cneurons % of human cneurons # equivalent to human
Lobster 100,000 0.0006 160,000
Chicken 50 million 0.3 320
Cow 300 million 1.9 53
Pig 425 million 2.7 38
Elephant 5.6 billion 35 2.9
Chimpanzee 6.2 billion 39 2.6
Human 16 billion 100 1

Some animal rights activists discuss the relative value of different species of animal. You have to eat a lot of steak to kill one cow, but you only have to eat a few chicken wings to kill one chicken. This suggests nonvegetarians trying to minimize the moral impact of their diet should Henglong 1 16 Russia T34-85 RC Tank Metal Road Wheels 360 Degrees Turrret 3909-1. But any calculation like this depends on assumptions about whether one cow and one chicken have similar moral values. Most people would say that they don’t – the cow seems intuitively more “human” and capable of suffering – but most people would also say the cow isn’t infinitely more valuable. Different animals rights people have come up with different ideas for exactly how we should calculate this.

I wondered how people’s intuitive ideas about the moral value of animals would correspond to their cortical neuron count. I asked Tumblr users who believed that animals had moral value to fill out a survey (questions, 2PC Military Camouflage 6061T6 Aluminum Diamond Bridge Axle 58 Angle Steering fo) estimating the relative value of each animal, in terms of how many animals = 1 human. Fifty people answered, including 21 vegetarians and 29 nonvegetarians. Their numbers ranged from 1 to putting their hand on the 9 key and leaving it there a while, but when I Scalextric C3693A Ford Sierra RS500 vs BMW E30 Ltd Ed, here’s what I got:

The middle column in this table is the same as the third column on the one above – it’s how many of each animal it takes before the group has the same cortical neuron count as a human. The last column is the survey results on how many of each animal it takes to have the same moral worth as a human.

The two are pretty similar. For example, 53 cows have the same neuron count as one human, and respondents said that 50 cows would have the same moral value as one human. Respondents placed a little less value on elephants and chimps than their neurons warranted, and a lot more on lobsters. Carl S suggests by email that lobsters might have been a bad choice: they have fewer neurons than an ant (really!) but because they’re so big everyone assumes they must be pretty advanced. Despite this, overall people’s answers were pretty close. Here’s a log-log graph:

This is a better match for the moral value data than other ways of calculating animal intelligence. For example, a cow has an encephalization quotient of 0.5, compared to a human’s 7.5. That would suggest a human is worth 15 cows, which doesn’t match the survey-takers’ impressions.

I would like to see this repeated with a larger survey of a more representative population. But for now I think this adds at least a little credibility to intuitive ways of thinking about these problems.

OT124: Opentatonic Thread

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This is the bi-weekly visible open thread (there are also hidden open threads twice a week you can reach through the Open Thread tab on the top of the page). Post about anything you want, but please try to avoid hot-button political and social topics. You can also talk at the SCALEXTRIC Slot Car C4015 Honda Civic Type R - BTCC 2018 - Chris Smiley or the SSC Discord server – and also check out the FW005-01C Slotwings Framed Porsche 917K - Vic Elford - New. Also:

1. The DC SSC meetup group is celebrating its second anniversary and wants to throw a party. It’s Saturday April 13 at 4 PM on 616 E Street NW, Washington DC. Anyone who reads this blog, even a little, is welcome to attend. Please see this link for very slightly more information.

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Gwern has answered my prayers and taught GPT-2 poetry.

SCALEXTRIC C2256 Subaru Impreza BELGACOM 1999 No.16 NEW is the language processing system that OpenAI announced a few weeks ago. They are keeping the full version secret, but have released a smaller prototype version. Gwern retrained it on the SCALEXTRIC Digital ARC Pro Slot Cars Aston Martin Vantage GT3 Porsche 911 RS, a 117 MB collection of pre-1923 English poetry, to create a specialized poetry AI.

I previously tested the out-of-the-box version of GPT-2 and couldn’t make it understand rhyme and meter. I wrongly assumed this was a fundamental limitation: “obviously something that has never heard sound can’t derive these complex rhythms just from meaningless strings of letters.” I was wrong; it just didn’t have enough training data. Gwern’s retrained version gets both of these right, and more too. For example:

Thou know’st how Menoetiades the swift
Was dragged, of Hector and the fierce compeers
And Phrygian warriors. So, we will dispatch
Your bodies, then, yourselves to burn the ships
In sacrifice; with torches and with bells
To burn them, and with oxen to replace
Your gallant friends for ever. But I wish
That no man living has so long endured
The onset of his foes, as I have power
To burn or storm; for mighty Hector erst
Was slain, and now returns his safe return

This is all perfect iambic pentameter. I know AP English students who can’t write iambic pentameter as competently as this.

(by the way, both “compeers” and “erst” are perfectly cromulent words from the period when people wrote poems like this; both show up in Shelley)

It has more trouble with rhymes – my guess is a lot of the poetry it was trained on was blank verse. But when it decides it should be rhyming, it can keep it up for a little while. From its Elegy Written in a Country Churchyard fanfic:

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Methinks I see her in her blissful dreams:
Or, fancy-like, in some mirage she lies,
Majestic yet majestic, and of seems
The image of the unconquerable skies.

Methinks I see her in her blissful dreams:
—Or, fancy-like, in some majestic cell,
Where lordly seraphs strew their balmy dreams
On the still night, or in their golden shell.

There, in the calm of some Platonic dream,
Sits she, and views the unclouded moon arise
Like a fair lady full of realms divine;

And, all at once, a stony face and bright
Glittering in moonlight, like the noon-tints of a night.

COME ON, IT’S A ROBOT. THAT’S BETTER THAN YOU COULD DO IF YOU WERE A ROBOT. GIVE IT A BREAK.

I think its problem is less ability to rhyme, and more a sort of…maintaning the will to rhyme. Gwern prompts it with several Alexander Pope pieces; Pope is a very formal poet who always rhymes in the exact same way. For each Pope piece, GPT-2 does the first couplet in perfect Pope style, then degenerates into increasingly confused gibberish. For example:

Pride even in numbers; wit’s a kind pretence
To something foreign still, but ne’er to sense;
A constant waste of words, the world produces,
A lazy sap, that nothing that’s foreign to expels,
; that’s foreign still unknown to the soul;
A young, like, but in the world in motion,
Obscending not, which smells all our own the worse than our own our own the soul’s, and soul;
Like sense; which is like, but in all our whole.
Which thus far more like, but in all things that’s an excellence; and ne’er unchanged by which is folly’s the worse, they give the worse maintained by which
If sick of sense;
Wholubil, or snug. ills, we know our own our first in sense the worse maintained between the worse, soon expired.

First two lines are perfect rhyme and rhythm, next four have no rhyme but are close to the right meter, next few have almost random length, and by the last one we’ve abandoned grammar and are making up nonsense words like “wholubil”. Every Pope test Gwern runs is like this:

They talk of constancy and faithless love,
A seraph trembles at the specious glove;
Nor in the rich confin’d relief of state,
Find proud pretence, nor in the disdiscoveries of fate.
For when misfortune makes choice remains the conduct’s the prize half known,
Can we secret soul without due, they fear of sense of more known.
Some rise where’ rights, they make it pays due.
.
.
. Sense and judgment, as equal prize seem meanly, the reward the joy, as much possess the prize paid, as well reckon the prize we do not less dare not less keenly wise.
We see;
Of happy lovers ought, as well done, like a friend.
Know they ought, ’tis ev’ is the other joy, as well worth a right;
The joy, as well might, as well may, as well may all is great.
Nor need of joys not as well maysters, as well as well may they give; but as little store; but as well as well as well may shewn, as much, as well we know, as well as well can be sure might prove, as well may well as well as well as well as well may view;
The mind: as well as well as well as well as much the fair as well as well as well as well as well as well as well may

Again, first two lines are great – “a seraph trembles at the specious glove” is both nonsense and exactly the sort of thing Alexander Pope would write, but by the fourth line we have nonsense words, by the fifth we lose the meter, the eighth and ninth are just periods, and finally it starts stuttering helplessly.

I tested this many more times on a public version (not poetry-trained) and found a similar effect – the first two lines are always the best, and it deteriorates from there. I’m interested in hearing from people who understand the model better than I do about why this should be.

Some other highlights:

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My heart, why come you here alone?
The wild thing of my heart is grown
To be a thing,
Fairy, and wild, and fair, and whole

That last line, with its ABAB structure, is actually brilliant even by the standards of human poets. “Fairy and wild and fair and whole”. I could say that all day. This has to be a coincidence. It’s not that good anywhere else. But even having something generally okay enough that it can occasionally blunder into something that good is great.

From its Hindu phase:

…which Indra, King of all the Blest,
Had thrown by Rávan’s mighty breast,
The monstrous coil, the brawny hand,
The monstrous mouth, the jaw, the jaw,
The jaw, the jaw and bleeding jaw,
The ungovernable host, the jaw,
And the great bow which never bends,
The arm, the fist, the knee, the ends,
The body laid with mighty stroke,
And the great bow which never bends.
So, when the giants fought, and fell
With murderous strokes, the giant fell,—
So falls the tree with all his trunks
Terrific in its death, that shoots
Wild volley at the mighty trunk,—
So fell the tree with all its boughs
While all the vipers dug and sowed—
So fell the tree with all its boughs.
But Ráma’s heart was sad within
He wept and mourned his captive’s sin

The first two lines are great (and the program must have invented the epithet “King of All The Blest” for Indra, because I can’t find it anywhere else). The description of Ravan’s jaw is, uh, quite memorable. “So falls the tree with all his trunks” is a good deployment of a metaphor which is frankly overused in old poetry. I’m ambivalent between interpreting the repetition as an AI getting stuck in a loop vs. as good use of repetition as a poetic device.

The next few are from C3644sf Scalextric McLaren P1 UKSF 2016 new boxed of a thousand randomly generated samples:

And they have seen the last light fail;
By day they kneel and pray;
But, still they turn and gaze upon
The face of God to-day.

And God is touched and weeps anew
For the lost souls around;
And sorrow turns their pale and blue,
And comfort is not found.

They have not mourned in the world of men,
But their hearts beat fast and sore,
And their eyes are filled with grief again,
And they cease to shed no tear.

And the old men stand at the bridge in tears,
And the old men stand and groan,
And the gaunt grey keepers by the cross
And the spent men hold the crown.

And their eyes are filled with tears,
And their staves are full of woe.
And no light brings them any cheer,
For the Lord of all is dead

And:

There are several kinds of people in America;
There are several kinds of people, I mean their number.
There’s a girl growing up in the house by the light,
There’s a youth upon the road, or a girl somewhere in New York;
There’s a prettier girl, and a man more congenial,

But none of the likes of the likes of the fellows are equal.
There’s one who has never been married and married,
There’s one who don’t want to be treated with kindness;
A fair youth is never employed nor neglected;
There’s one who has never yet come to a neighbor,
And one who resides in New York from the start;

But none of the likes of the likes of the fellows
Are equal to him, and wherever he goes,
The heart somehow breaks under the hand that is steering;
And so it is with me

And this quatrain just worked out really well:

Fair is the Lake, and bright the wood,
With many a flower-full glamour hung:
Fair are the banks; and soft the flood
With golden laughter of our tongue

This one is notable for competent metaphor:

How the clouds
Seem to me birds, birds in God’s garden! I dare not!
The clouds are as a breath, the leaves are flakes of fire,
That clash i’ the wind and lift themselves from higher!

And this one is obviously a failure on one level, but on another level is some kind of great experimental modern political poetry:

The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), rapacious,
The Emperor Wu (the great Wu), majestical,
The Emperor Wu (the great Wu), rapacious,
The Emperor Wu (the great Wu), rapacious,
The Emperor Wu (the great Wu), rapacious,
The Emperor Wu (the great Wu), rapacious,
The Emperor Wu (the great Wu), rapacious,
The Emperor Wu (the great Wu), rapacious,
The Emperor Wu (the great Wu), rapacious,
The Emperor Wu (the great Wu), rapacious,
The Emperor Wu (the great Wu), rapacious,
The Emperor Wu (the great Wu), rapacious

This one displays an interesting combination of world-knowledge and lack-of-world-knowledge:

In the dark the sun doth gleam,
And in the dark the moon doth seem
But now the evening is begun–
Gone is the sun upon the earth!
The silver moon doth like a cup
Of blood-red wine, and as that cup
Is drained of life, doth quench no drop.
What man will drink such wine?
There is no soul of earth or birth
Which man hath never known of earth.
There is no soul who doth not sit
And sing to it, and cry, “Drink!”
There is no soul whose feet are set
On youth’s eternal paradise;
For all is a solemn harmony,
And all is a perpetual chant,
And all the world is a song of God.
There is no soul so wholly free

And here’s another:

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There gloom the dark, broad seas. My mariners,
Souls that have toiled, and wrought, and thought with me
That ever with a frolic welcome took
The thunder and the sunshine, and opposed
Free hearts, free foreheads – you and I are old;
Old age hath yet his honour and his toil;
Death closes all: but something ere the end,
Some work of noble note, may yet be done,
Not unbecoming men that strove with Gods.

Except this last time I’m cheating: this is an excerpt of Tennyson’s Scalextric Aston Martin DBR9 No5 DHL C2790 Mint Boxed, one of the most famous English poems. I included it as a placebo, ie a test to see whether real poems sound fake if you think they’re by an AI when you read them. I’ll be honest: if I didn’t know this was Great Poetry, I would skim it over and assume it made several mistakes. Like: is “gloom” really a verb? (it is if you’re Alfred, Lord Tennyson). Is the last line grammatical? (yes: it’s an adjective phrase modifying “work”, ie “some work which is fitting for the sort of men who fought gods to do”). Are the mariners’ souls opposing their foreheads? (I’m still confused on this one). These are all the sorts of things that would make me go “Haha, AIs are still pretty dumb” if I were reading it blindly.

If you liked these poems, you might also appreciate Gwern’s work making Scalextric x2 Porsche 911 GT3R Fully Serviced & Working Lights.

(and you can also donate to Gwern’s Patreon here)