trentmkelly/LessWrong-43k huggingface dataset:
Saving Lives Reduces Over-Population—A Counter-Intuitive Non-Zero-Sum Game
by James Stephen Brown — 2024-06-28T19:29:55.238Z
Link: https://nonzerosum.games/savinglives.html

AN ARGUMENT AGAINST SAVING LIVES

When making the argument for charitable giving, a response I have often received is that saving lives in areas that are already over-populated will perpetuate over-population-solving nothing. It’s a concern I shared when first considered charity.

The logic seems sound on the face of it. For instance, if a predator is eliminated from, let’s say, a rabbit habitat, the rabbits can become over-populated until they reach some other natural limit, like resource depletion. This is the standard Malthusian theory of population equilibration

*

.

AN ARGUMENT FOR SAVING LIVES

I will be making the case that the reverse situation is actually at play, and that, somewhat counter-intuitively, by saving lives we actually reduce over-population. I will be employing two studies; one looking at

data from the US

and the other looking at

data from Europe

. The first conclusive finding is a clear positive correlation between the fertility rate and the infant mortality rate over time.

“In every case, changes in infant mortality are positively associated with changes in fertility and most are significant.” (European study)

This correlation is not just evident over time but is clear geographically.

More infants dying means more babies being born. But correlation is not causation! It is entirely possible that any or all of the following relationships are at play.

A Higher Fertility Rate causes a Higher Infant Mortality Rate
A Higher Infant Mortality Rate causes a Higher Fertility Rate
Both Fertility and Infant Mortality are affected by other variables

The case I am making depends on option 2 being a factor.

If this is the case, then saving lives reduces over-population-creating a win-win situation where the population becomes more sustainable alongside the obvious benefits to individuals, whose lives are saved in the process. But why would this be? Let’s unpack the issue.

WHY LOOK AT FERTILITY AND INFANT MORTALITY?

In short, for the sake of clarity.

It’s important to clarify that the fertility rate is not actually a measure of how fertile individuals are, but rather the average number of children an average woman gives birth to. It’s essentially the ‘birth rate’ but relative to the female population only, which gives a clearer signal regarding reproductive behavior. Infant mortality turns out to be a clearer indicator of societal health, and has a...
Mentorship in AGI Safety: Applications for mentorship are open!
by Valentin2026 — 2024-06-28T14:49:48.501Z

One month ago we called for mentors for MAGIS mentorship program. Today, we are happy to announce that we found enough mentors and invite potential mentees to apply! Please check our list of mentors here, choose two (first choice and second choice), and then fill out this application form.

The application deadline is July 12.
Contra Acemoglu on AI
by Maxwell Tabarrok — 2024-06-28T13:13:15.796Z
Link: https://www.maximum-progress.com/p/contra-acemoglu-on-ai

The Simple Macroeconomics of AI

is a 2024 working paper by Daron Acemoglu which models the economic growth effects of AI and predicts them to be small: About a .06% increase in TFP growth annually. This stands in contrast to many

predictions

which forecast immense impacts on economic growth from AI, including many from

other academic economists

. Why does Acemoglu come to such a different conclusion than his colleagues and who is right?

First, Acemoglu divides up the ways AI could affect productivity into four channels:

1. AI enables further (extensive-margin) automation.
Obvious examples of this type of automation include generative AI tools such as large language models taking over simple writing, translation and classification.

2. AI can generate new task complementarities, raising the productivity of labor in tasks it is performing.
For example, AI could provide better information to workers, directly increasing their productivity. Alternatively, AI could automate some subtasks (such as providing readymade subroutines to computer programmers) and simultaneously enable humans to specialize in other subtasks, where their performance improves.

3. AI could induce deepening of automation—meaning improving performance, or reducing costs, in some previously capital-intensive tasks.
Examples include IT security, automated control of inventories, and better automated quality control

4. AI can generate new labor-intensive products or tasks.

Each of these four channels is referring to specific mechanism in his task-based model of production.

Automation raises the threshold of tasks which are performed by capital instead of labor
Complementarities raises labor productivity in non-automated tasks
Deepening of automation raises capital productivity in already-automated tasks
New tasks are extra production steps that only labor can perform in the economy, for example, the automation of computers leads to programming as a new task.

The chief sin of this paper is dismissing the latter half of these mechanisms without good arguments or evidence.

“Deepening automation” in Acemoglu’s model means increasing the efficiency of tasks already performed by machines. This raises output but doesn’t change the distribution of tasks assigned to humans vs machines. AI might deepen automation by creating new algorithms that improve Google’s search results on a fixed compute budget or replacing expensi...
Five toy worlds to think about heritability

by David Hugh-Jones — 2024-06-28T13:11:55.041Z
Link: https://wyclif.substack.com/p/five-toy-worlds-to-think-about-heritability

Just a quick note from a

Twitter/X discussion

.

It’s an almost-universal scientific rule that empirics is blind without a model. The left picture below shows a bunch of points, and a regression line fitting them. It seems like a good fit. But why should we believe it? The right picture shows the same points with a curve that fits them perfectly. We prefer the left hand line because of some theory like “these two variables are probably linearly related, and also y is partly random”. That theory is embodied in an equation like y = a + bx + ε where b is the slope of the line and ε is random noise which makes the fit imperfect. Without that, we’d have to accept that the stupid right hand curve fits the data better.

Thirty points and two alternative models to explain them

Heritability is the proportion of variation in something that can be explained by people’s genes. (For social scientists: imagine doing the perfect regression on the outcome, using all relevant genetic variables. Heritability is the R-squared.

1

) The classic way you estimate heritability is by comparing identical to fraternal (non-identical) twins. Identical twins share all their genetic variation, fraternal twins share only half of it. Assuming no assortative mating! If people marry people with similar genes then fraternal twins and other siblings will have more than half their genes alike.

So you can back out heritability from that. If identical twins are exactly alike on the variable of interest, with a correlation of 1, and fraternal twins are correlated at 0.5, then the heritability is 1. More generally, the heritability is twice the difference in correlations.

Twin studies are genius because they leverage theory. We know people get half their genes from each parent, that in fraternal twins the genes are drawn independently, and in identical twins they are exactly the same. Without this insight, there would be no way to separate the effects of parental environment and genetics. Genes come from your parents, so does family background. A study of parents and children couldn’t disentangle these effects. The theory let scientists disentangle genes and family environment, even before it was practical to measure people’s DNA variants.

But are twin studies right? What if identical twins grow up in a more similar environment than fraternal twins? That seems plausible because maybe parents treat them more s...
How do natural sciences prove causation?
by Kongo Landwalker — 2024-06-28T11:58:49.643Z

Let's say we have 2 phenomena, A and B, each can be a value of 0 or 1, and we observe, that for them implication table A=>B is always true. (Third column represents whether the combinations of events can happen or cannot.)
A B A=>B

0 0 1

0 1 1

1 0 0

1 1 1

Thing we see is that combination A=1 and B=0 almost never happens, and three other combinations can happen. But how can we be sure, that it is not some kind of third event, which influences both of those to output those combinations of values?

What if the table is like this, based on &?

0 0 0

0 1 0

1 0 0

1 1 1

If at least one of events (any) happens, then the second happens too. How this relation would be called?

How many tables (of the 16) there are which could potentially represent causation?
For example,

000

010

101

111

is not in the set, because it says, that A not being true is impossible(has never been observed), but has no limitation on the value of B.

Given a table in this format (or just a string representing the third column), what a person would do next to test whether events influence one another or are both defined by a third? Does the further approach even depend on a type of table?
(I expect it will not, as everything would be observed in frequencies)

Is it like an cycle, where one makes an assumption "what if they both are defined by event C" and then shows there is no correlation with C, and repeats for many other possible C's? But then it looks it would not be possible to exhaust all possible C's.
Bayes' Theorem: In Search of Gold (Lesson 1)
by bayesyatina — 2024-06-28T08:39:16.638Z

[This text is a translation, and my English may not be perfect. I would appreciate any suggestions for stylistic improvements]

The fire crackled in the fireplace, while it was raining heavily outside the window. The young dwarves, soaked from the rain, were sitting in chairs around the older dwarf.

Welcome to the course "Bayes' Theorem: In Search of Gold" (started by an older dwarf standing in the center next to the board). My name is Tifius, and I will be your instructor for this practically useful theoretical course. The course is theoretical in that you will not be receiving gold at the end (there was a collective sigh from those closer to the window), but it is also practical in that it increases your chances of finding gold in the future.

As you all know, any intelligent dwarf wants to get closer to gold. Some of us become bankers, so that the shine of gold from the bank's vault will please them in the morning, instead of a cup of coffee. Others become jewellers, in order to hold gold more often in their hands. Those who really want to mine gold, go to mining schools like you.

You might have a question "what about blacksmiths, this is a traditional dwarven profession"? Unlike the students, perhaps you are not familiar with the life of Tifius.The teacher does not like blacksmiths, as one of them is rumored to have stolen his wife (although the teacher never had a wife himself). When Tifius discovered dynamite for gold mining and became very rich, he decided to establish a prize to encourage further discoveries in all areas of dwarf activity, except for blacksmithing.

What is the most important aspect of gold mining? It is certainly not what is taught in other courses. Although there is still pickaxes and lanterns in your curriculum, it's crazy because we have been using diode lanterns and automated drilling rigs for a long time. Due to the fact that advanced technology has become indistinguishable from magic, many even believe that dwarves have overcome their inability to perform magic. However, this is not the most significant aspect of gold mining. The most important aspect is the ability to accurately predict where gold deposits can be found, rather than physical skills or knowledge of new technologies.

How does one learn to predict accurately? You might need to take courses in astrology, numerology, and other esoteric practices. However, I'm joking. ...
How a chip is designed
by YM — 2024-06-28T08:04:27.392Z

Disclaimer: This is highly incomplete. I am not an expert in the field. There might be some unfamiliar terms. While I will try to explain things, explaining every single term would be beyond this post. You will usually be able to get a sufficient understanding by clicking the links or googling it.

Introduction

I think everyone, if they read about the chip industry long enough, has a moment where they have to put down a book or pause a podcast and simply remain stunned at the fact that it is possible to design and build something that is so incredibly impressive.

The Apple A17 chip contains 183 million transistors per square millimeter. All placed in a coherent manner and produced with extremely high reliability.

This is exactly why it is so fascinating to learn more about how it is actually done. On top of that, in a universe where compute is arguably the most important input in the AI production function, this knowledge is also crucial to effective AI governance.

So what follows is a quick introduction to the processes of getting a chip from a vague idea to sending your files to the manufacturer, also called the tape-out.

Background Knowledge

One of the most important decisions, a decision that significantly determines all the others, is what manufacturer will build your chip and what process they will use. There are companies that do both design and manufacturing (e.g. Intel), but especially when it comes to the most advanced logic chips, more and more companies are what is called “

fabless

” - they focus on the design and task a so-called “foundry” (e.g. TSMC) with the manufacturing.

Nowadays many fabs and fabless companies work together very closely in what is called Design-Technology Co-Optimization (DTCO). In practice, there are quite significant limitations in chip design, and the fab will check design plans and inform designers what can and can't be manufactured. This collaborative approach ensures that chip designs are optimized for the specific manufacturing process, balancing performance, power, area, and yield considerations. DTCO has become increasingly important as the industry approaches the physical limits of semiconductor scaling, requiring closer integration between design teams and process engineers to continue advancing chip capabilities.

The foundry sends the design company what is called the

process de

...
The Wisdom of Living for 200 Years
by Martin Sustrik — 2024-06-28T04:44:10.609Z

Scott Sumner writes:

Old people have a sort of double vision about the past — an ability to see the past from the perspective of today, and also from the perspective of the people who lived through those times. When then was now.

This double vision, according to Scott, brings wisdom, something you gain with age, an attitude that younger people are missing:

When I read some of my lamer posts from the early days, I cringe at their lack of wisdom. What was I thinking?

It's a little nebulous, but one can see how considering the current issue from multiple cultural perspectives - remember: past is a foreign country! - helps you to get a more balanced view.

Say, the political situation in Slovakia, the country which I am originally from, is not exactly rosy right now. We have a new Orbán or PiS-style government, which is trying hard to weaken the rule of law. Everybody in my social circle goes crazy about it. But there's a difference: While young people are simply horrified, older people do act as if they were horrified, but if you question them in private, they tend to admit that yes, it's not that bad, it used to be worse in 90s, when we used to have severed human heads in flower pots and whatnot.

It's a tacit knowledge that doesn't get passed on. Young people, born in 90s don't remember the severed heads, after all.

Scott further writes:

Of course this only applies to periods that we ourselves have lived through. I have no feel at all for the 1890s. I know that it was a disgrace for respectable women to show their legs in public, or to go out on the town without an escort, but I don’t actually have much of a feel for why.

Understood. But I have two questions: First, do we need the full experience of the past to get wise? Or would something that goes half the way be good enough? And second, is there a way to convey this tacit knowledge about the past, even if it's not perfect?

People today freak out about the war of the day, the democratic backslide, the conspiration theories, the AI doom. But then you look at someone like Tyler Cowen and it's surprising how equianimous he manages to remain in spite of all that. And it doesn't seem to be only about the age. One has to wonder whether it's simply linked to intimate knowledge of the history, the visceral realization that people are always freaking out about something. "When we run out of guano we are all going to...
A Generally Intelligent Game
by snerx — 2024-06-28T01:31:53.634Z

There are lots of arguments about how to test for general intelligence and I see debates about what thresholds count for generality, but it seems to me that a more interesting problem occurs after we attain a sufficient test for general intelligence — that the test becomes generally intelligent itself.

A Game For General Intelligences

There is currently no game I am aware of that you can play over the internet which is immune to AI supremacy,[1] meaning there is no online game that requires general intelligence to play (and consistently win). But let's grant someone eventually designs a game that requires general intelligence to play and win and which you can play online against AI engines. As soon as that game is created, we achieve as concomitant a good test for g factor since your proficiency at the game would be a direct measurement of the skill with which you exercise general intelligence. The reverse is true too — that if AI turbonerds ever figure out a good test for true g factor then as concomitant we learn how to game it.

The significance is that if we had a good and reliable way to test for general intelligence then we could design an adversarial game around it wherein two players could compete and the player with more comprehensive general intelligence, meaning faster lateral thinking across a general conceptual space, is the player that wins more often than not. Just as you can compete and get better at chess, basketball, TF2, or any other kind of game, and improve the skills relevant to what makes you good at those games along the way, you could play the game for general intelligence and improve your skill of exercising general intelligence the more you play. We could even implement an Elo-like scoring system and rank people by how general their intelligence is (how useful their minds are for thinking about generally complex problems).[1]

Since the g factor measured by IQ tests hasn't already been turned into this kind of adversarial multiplayer game, and probably can't be, this serves as evidence that IQ doesn't really measure general intelligence (which most people already believe by now anyways), or general intelligence just can't be gamified in the way described above.

While generalized intelligence means you are not limited by conceptual quality, it doesn't imply unlimited conceptual quantity. So while any being that is generally intelligen...
Corrigibility = Tool-ness?
by johnswentworth — 2024-06-28T01:19:48.883Z

Goal of This Post

I have never seen anyone give a satisfying intuitive explanation of what corrigibility (in roughly Eliezer’s sense of the word) is. There’s

lists of desiderata

, but they sound like scattered wishlists which don’t obviously point to a unified underlying concept at all. There’s also Eliezer’s

extremely meta pointer

:

We can imagine, e.g., the AI imagining itself building a sub-AI while being prone to various sorts of errors, asking how it (the AI) would want the sub-AI to behave in those cases, and learning heuristics that would generalize well to how we would want the AI to behave if it suddenly gained a lot of capability or was considering deceiving its programmers and so on.

… and that’s basically it.[1]

In this post, we’re going to explain a reasonably-unified concept which seems like a decent match to “corrigibility” in Eliezer’s sense.

Tools

Starting point: we think of a thing as corrigible exactly insofar as it is usefully thought-of as a tool. A screwdriver, for instance, is an excellent central example of a corrigible object. For AI alignment purposes, the challenge is to achieve corrigibility - i.e. tool-ness - in much more general, capable, and intelligent systems.

… that all probably sounds like a rather nebulous and dubious claim, at this point. In order for it to make sense, we need to think through some key properties of “good tools”, and also how various properties of incorrigibility make something a “bad tool”.

We broke off a separate post on

what makes something usefully thought-of as a tool

. Key ideas:

Humans tend to solve problems by finding partial plans with “gaps” in them, where the “gaps” are subproblems which the human will figure out later. For instance, I might make a plan to decorate my apartment with some paintings, but leave a “gap” about how exactly to attach the paintings to the wall; I can sort that out later.[2]
Sometimes many similar subproblems show up in my plans, forming a cluster.[3] For instance, there’s a cluster (and many subclusters) of subproblems which involve attaching things together.
Sometimes a thing (a physical object, a technique, whatever) makes it easy to solve a whole cluster of subproblems. That’s what tools are. For instance, a screwdriver makes it easy to solve a whole subcluster of attaching-things-together subproblems.

How does that add up to corrigibility?

R

...