trentmkelly/LessWrong-43k huggingface dataset:
Schools probably do do something
by Yair Halberstadt — 2021-09-26T07:21:33.882Z

It's a relatively commonly held view here on Less Wrong that school is mostly a waste of time.

I'm not going to comment on this directly. Instead I'm going to show that school probably has some impact on future life outcomes.

The evidence for this is the Relative Age Effect.

The term relative age effect (RAE), also known as birthdate effect or birth date effect, is used to describe a bias, evident in the upper echelons of youth sport and academia, where participation is higher amongst those born early in the relevant selection period (and correspondingly lower amongst those born late in the selection period) than would be expected from the normalised distribution of live births. The selection period is usually the calendar year, the academic year or the sporting season.

For example students in Oxford were well over 20% more likely to be born in September (the start of the academic year), than August (the end).

The classic explanation for this is that whilst there's not much of a difference in maturity between a 17 year old and an 18 year old, there's a large difference between a 4 year old and a 5 year old. So older kids shoot to the top of the class when they start school, and so are more likely to be engaged and interested in class, which keeps them at the top even once the difference in maturity stops being relevant.

This implies that either

A) School does something positive for those at the top of the class (pushes them up relative to kids who don't go to school at all).

B) School demotivates those at the bottom of the class (pushes them down relative to kids who don't go to school at all).

C) Given how difficult it is to get into Oxford, even 1 years worth of maturity can make a significant difference.

If we discount C, then school does have some impact on academic outcomes albeit we don't know if that outcome is positive or negative.

Further research could include:

is there a difference between students who took a gap year before applying and those who didn't? This would investigate option C above.

does this effect persist among home schooled children, where the classic explanation wouldn't apply.

does this effect persist into later life outcomes? Thai would measure whether the impact is short term or long term. According to Wikipedia this effect has been observed among CEOs of S&P 500 companies as well. However this is maybe just because they're more li

...
Book Review: Homo Deus
by Collisteru — 2021-09-25T21:36:34.101Z

Homo Deus is part two of Yuval Noah Harari’s humble quest to explain all of history. In Sapiens, he created a model of how humans rose to become Earth’s apex predator and most powerful ecological force. In Homo Deus, he refines his model and makes predictions about culture in a transhuman future.

Harari’s a bit of an intellectual maverick. His books bring you on a reckless tour through nearly every field of study, taking potshots at common opinion wherever they can. Each chapter escalates the weirdness until you feel peculiar yourself for agreeing with him.

Though anthropology is its principal subject, Homo Deus dips into fields as diverse as evolutionary psychology, computer science, and literary criticism. Even if you disagree with Harari’s thesis, you will learn something from this book.

In this review, I’ll look at Harari’s main thesis in three sections. A horizontal line divides each section into two parts: a summary of Harari’s ideas, and my own analysis based on relevant research. Though I will cover only a small fraction of the book's content, I hope you walk away with the information you need to decide if Homo deus is worth your time.

Intersubjective Reality

Homo Deus considers how science and technology will reshape culture. To explore this, Harari needs to establish what culture is, what motivates it, and how it shapes human activity. As many scholars do, Harari argues that culture is not just an ancillary byproduct of society— it's what made it possible for a particular species of Homo to rise above the rest.

Humans are not special. We are algorithms running on biological hardware, just like every other plant or animal. Early humans understood this, and were therefore animists— they saw the snakes, eagles, and elephants around them as being equal to themselves. Even when they killed an animal, they often made a sacrifice as penance to prevent nature from returning the favor.

Contrast this with the story told in the Bible, which was written by scholars of a much later, agrarian culture. God creates humans “in his own image.” He gives them dominion over bees and trees as well as a nice garden to play around in. When a wicked animal tricks Adam and Eve, he expels them for insubordination. Though other major religions show more empathy to animals, they all nevertheless see them as tools for humans. This mythological shift stands as a symbol for the larger h...
AXRP Episode 11 - Attainable Utility and Power with Alex Turner
by DanielFilan — 2021-09-25T21:10:26.995Z

YouTube link

This podcast is called AXRP, pronounced axe-urp and short for the AI X-risk Research Podcast. Here, I (Daniel Filan) have conversations with researchers about their papers. We discuss the paper and hopefully get a sense of why it’s been written and how it might reduce the risk of artificial intelligence causing an existential catastrophe: that is, permanently and drastically curtailing humanity’s future potential.

Many scary stories about AI involve an AI system deceiving and subjugating humans in order to gain the ability to achieve its goals without us stopping it. This episode’s guest, Alex Turner, will tell us about his research analyzing the notions of “attainable utility” and “power” that underlie these stories, so that we can better evaluate how likely they are and how to prevent them.

Topics we discuss:

Side effects minimization

Attainable Utility Preservation

AUP and alignment

Power-seeking

Power-seeking and alignment

Future work and about Alex

Daniel Filan:
Hello, everybody. Today, I’ll be speaking with Alexander Matt Turner, a graduate student at Oregon State University, advised by Prasad Tadepalli. His research tends to focus on analyzing AI agents via the lens of the range of goals they can achieve. Today, we’ll be talking about two papers of his, Conservative Agency via Attainable Utility Preservation, coauthored with Dylan Hadfield-Menell and Prasad Tadepalli, and Optimal Policies Tend to Seek Power, coauthored with Logan Smith, Rohin Shah, Andrew Critch, and Prasad Tadepalli. For links to what we’re discussing, you can check the description of this episode, and you can read a transcript at axrp.net. Alex, welcome to the show.

Alex Turner:
Thanks for having me.

Daniel Filan:
Before we begin, a note on terminology. In this episode, we use the terms “Q-value” and “Q function” a few times without saying what they mean. The “Q-value” of a state you’re in and an action that you take measures how well you can achieve your goal if you take that action in that state. The “Q function” takes states and actions, and returns the Q-value of that action in that state. So, to summarize, Q-values tell you how well you can achieve your goals. Now, let’s get back to the episode.

Side effects minimization

Daniel Filan:
So, I think, first of all, I want to talk about this first paper, Conservative Agency via Attainable Utility Preservati...
Cognitive Biases in Large Language Models
by Jan — 2021-09-25T20:59:51.755Z
Link: https://universalprior.substack.com/p/cognitive-biases-in-large-language?r=7inm4&utm_campaign=post&utm_medium=web&utm_source=

Humans, one might say, are the cyanobacteria of AI: we constantly emit large amounts of structured data, which implicitly rely on logic, causality, object permanence, history—all of that good stuff. All of that is implicit and encoded into our writings and videos and ‘data exhaust’. A model learning to predict must learn to understand all of that to get the best performance; as it predicts the easy things which are mere statistical pattern-matching, what’s left are the hard things.

Gwern

#[[

IAN says:

]] Hey #IAN ! Do you have any cognitive biases? IAN : "Oh, I have a ton of them, but you know them all already."

1

(TL;DR: LMs exhibit some cognitive biases. Additionally, might explain how cognitive biases can come about in humans. Raising questions about how universal deductive inference is.

Meta: This post summarizes the results from my project for the

AGI Saftey Fundamentals fellowship

by EA Cambridge. Code is available

here

.)

Introduction

Large language models like GPT-3 (or

#IAN

) get their capabilities by learning from copious amounts of text collected from the internet.

2

While this approach results in

remarkable general capabilities

3

it also comes with certain caveats. Since the text on the internet stems from humans

4

, it contains all of our good,

bad

and

ugly

. Interacting with a language model without safeguards can feel a bit like

opening Pandora's box

.

Reports

and

worry

about biases in large language models abound - with good reason. Removing these biases and constructing models that internalize human values (

as opposed to the unsatisfactory reality of human behavior

) appears critical for these models to reach their full potential (and, in fact, to be safe to use at all). Removing biases from large language models is a particularly illustrative case of what is more generally called the "alignment problem" - the problem of producing AI that is aligned with human values. The general problem

has many nuances and can be decomposed

, but the specific problem of removing unwanted biases is already tough enough to hint at the difficulty of the general problem.

While some problems of language models

disappear

with

increasing scale

(such as

arithmetic

), the opposite appears to be true for

societal

and

religious

biases, which are enhanced in large models. Multimodal models apparently are even worse by incorporating "

the worst of both worlds

" when it comes to biases...
Secular Therapy Project
by Adam Zerner — 2021-09-25T20:34:37.439Z
Link: https://www.seculartherapy.org

The purpose of the Secular Therapy Project is to help connect non-religious or secular persons who need mental health services with outstanding mental health professionals, such as psychologists, psychiatrists, counselors, and others. Using our system is simple and requires very little information from you. Our goal is to protect your confidentiality until you find a therapist to correspond with or to work with.

What’s unique about the STP is that we aren’t just a database of therapists. Instead, we very carefully screen potential therapists who want to become part of the STP. We screen them to make sure that a) they are appropriately licensed in their state or country, b) that they are secular in nature as well as practice, and c) that they actually use evidence-based treatments, which have been shown to be effective at helping improve mental health problems in controlled clinical trials. This means not only will our therapists not try to preach to you or convert you, but that they are also using the most well-supported types of treatment to help you.
Designing Low Upkeep Software
by jefftk — 2021-09-25T18:50:05.900Z

It's common for me to get excited about a personal project, put a
bunch of time into it, and then lose interest. As much as possible, I
want these projects to continue working; upkeep isn't fun. What does designing
for minimum maintenance look like?

The biggest piece is minimizing your dependencies, and limiting them
to ones that value backwards compatibility. Most of my projects are
on the web, which means I have an unavoidable dependency on browsers,
but this is fine because browsers strongly prioritize keeping existing
websites working.

On the server I run Ubuntu LTS until it's near the end of its
supported lifetime. Every two years I run do-release-upgrade
and move to the next one. This cost is shared over many
jefftk.com projects, so it isn't too bad.

Many projects can just be
hand-written HTML/JS/CSS. No build system, no libraries, just
speaking the browser's native languages. These don't need any
technical maintenance; they just keep working.

One step from there are projects where
I need a little bit of server-side support. For example, I write my
blog posts as plain HTML, but I need headers, footers, indexes, and
RSS. Each time I change my site I run a script
which creates/updates all these additional files. If I want to change
something about the presentation of my site then I need to dig into
code, and very occasionally something will break when updating the
site, but just displaying my existing stuff doesn't require any
maintenance.

Then we get to the tricky stuff: projects which need real time custom
code. Things like Bucket
Brigade and blog comment
inclusion. How I approach this:

Code in python, with no dependencies beyond the standard
library. As with browsers, python rarely drops support for widely
used functionality. Moving to python3 was a bit annoying, but I
waited a long time and then used 2to3. Avoiding dependencies made this
easy.

Store data on the file system, including for caching. It's not
as elegant as a proper database, but it doesn't require an additional
process or dependency. Debugging and backup are very simple, because
everything is visible.

Implement as much as possible on the client.

Leave out features if they can't be implemented simply, or
would require more than minimal server-side processing.

For example, I taught my comment requester to fetch comments from the
EA Forum ...
Pathways: Google's AGI
by Lê Nguyên Hoang — 2021-09-25T07:02:29.805Z

A month ago, Jeff Dean, lead of Google AI, announced at TED that Google is developing a "general purpose intelligence system". To give a bit of context, last January, Google already published a paper on a 1.6-trillion parameter model based on the architecture of switch transformers, which improves by on order of magnitude upon GPT-3. Yet, I've heard that Google usually only publishes a weaker version of the algorithms they actually develop and deploy at scale.

From a technical viewpoint, and given my understanding of switch transformers and of the challenges of scaling neural networks, I'm guessing that Pathways' model will now be decentralized on multiple machines (as it does not fit on a single machine), and its computation (both in forward pass and backprop) must optimize its "pathway" by only leveraging some of the machines Pathways is deployed on. Google seems to want to leverage this to build models with 100-trillion+ parameters (note that models have been roughly x10 per year since Bert).

As a comparison, the human brain is estimated to have hundreds of trillions of synapses connecting its 100 billion neurons. In terms of numbers, Google's algorithms may soon match the human brain. However, as opposed to a human brain, these algorithms crunch billions of data points per second. Moreover, these data are extremely informative, as they track the daily habits, behaviors and beliefs of billions of humans on earth, through their activities on Google Search, YouTube, Google Mail, Google Drive, Google Maps or even Google Smart Keyboard. Perhaps more importantly still, Google's algorithms leverage this "intelligence" to have a massive-scale impact, by choosing which information will be shown to which human on earth, especially through the YouTube recommendation algorithm and Google Adsense.

I'm curious to know how this news updates your beliefs on the following questions:

Elicit Prediction (forecast.elicit.org/binary/questions/ICy5uv219)

Elicit Prediction (forecast.elicit.org/binary/questions/XpuhHCKuR)

Elicit Prediction (forecast.elicit.org/binary/questions/mRtRf22m-)

EDIT: I see that many of you doubt that a recommendation algorithm can be an AGI. Does this mean that you reject the orthogonality thesis?

Elicit Prediction (forecast.elicit.org/binary/questions/xCBK7XM8X)

(if you believe tha...
This War of Mine
by lsusr — 2021-09-25T01:43:11.985Z

This War of Mine is too hard.

There are many kinds of war videogames on the market. First person shooters let you play as a marine, a robot soldier, a WWI soldier, a WWII soldier, a WWIII soldier or an alien soldier. Strategy games let you command armies, squads, nations and empires. You can kill Nazis, robots, ninjas, Rebels and Communists. You can shoot guns, wield swords, fire rocket launchers, operate flamethrowers and throw grenades. You can fly aircraft, command tanks, drive trucks, race humvees, pilot battlemechs and sail ships.

This War of Mine is based on the Siege of Sarajevo. You play as a noncombatant trying to not die.

You can burn your books to keep from freezing to death but if you do your avatar might get bored from having nothing to read. You can trade knives for food and diamonds for cigarettes. If you make a chair it'll save you energy during the day. If you make a bed you will be more likely to survive getting sick. But if you build a bed that's supplies you can't use for boarding up your windows or constructing a system to collect rainwater.

The constant risk of starving to permadeath is not what makes This War of Mine difficult.

Early in This War of Mine you come across a house while scavenging. There is an elderly couple living there. Do you steal the old man's medicine? You live a precarious existence. Small mistakes compound. Your friends are counting on you to bring back food and other desperately-needed supplies. Being a little hungry one day could cause a cascade of problems resulting in all of you dead.

On the other hand, stealing an old man's medicine is wrong.

The first time I played This War of Mine I thought long and hard about what to do. I turned the game off and went for a walk. The tenth time I stabbed the old man with a knife while his back was turned so I could practice the game's stealth mechanics.

There are opportunities to do good too. A young woman might come by and ask for help boarding up her house to protect against scavengers. If you accept it'll cost you a day's labor. You'll be a day hungrier with nothing to show for it.

If you accept the moral boost might keep your character from committing suicide.

In This War of Mine you're repeatedly forced to choose between risking your life and risking your soul. You don't know how long the siege will last. It could end tomorrow or it could end in a year. It's a challenge to survi...
The 2021 Less Wrong Darwin Game
by lsusr — 2021-09-24T21:16:35.356Z

It's fall and that means it's time for another Less Wrong Darwin Game. This year, you'll be designing up to ten species that will compete for food including (sometimes) eating each other.

Click here to participate [Entries are now closed.] You have one week from September 23 to design your species. Submit them by September 30th or earlier.

Each player starts with a population of organisms. Each round each of your organisms will be randomly paired with another organism. At this point, one of two things will happen:

If one organism can eat the other organism then it will do so.

If nobody gets eaten then both organisms get an opportunity to forage for plants.

After everyone has eaten, each organism will attempt to reproduce. The more an organism eats you eat the most descendents an organism can leave.

Food

Each round your organisms lose 20% of their energy to metabolism resulting (on average) in a 20% decrease in population. You must eat food to counteract metabolism. There are two sources of food: plants and other animals.

Predation

There are two phases to combat. In the first phase organisms size each other up to figure out which is the predator and which is prey. There are two ways for an organism to become the predator.

Venom. If one organism has venom but the other does not have antivenom then the organism with venom is the predator. (Antivenom is a prerequisite to venom.)

Weapons. Weapons represent claws, teeth and tusks. If either organism's weapons value exceeds the prey's weapons + armor then the organism with the higher weapons value will become the predator.

Venom takes priority over weapons. Once a predator-prey relationship is established (if a predator-prey relationship is established) the prey will get a chance to escape. If the prey's speed equals or exceeds the predator's then nobody gets eaten.

Venom, weapons and antivenom all make your organism bigger, which slows down reproduction.

Adaptation
Size
Notes

Venom
6
Requires Antivenom

Antivenom
1

Weapons×n
n
n≥0

Armor×n
3n4
n≥0

Speed×n
n
n≥0

Omnivores priorize meat over plants, when they can get it even if foraging for plants would be more metabolically efficient[1].

Predation has an efficiency of 0.95[2]. That means 95% of the prey's energy can be used by the predator.

Only organisms of different species eat each other. Cannibalism is disabled.

Foraging for Plants

There are var...
It's Good Enough -- A Party Game
by Zmavli Caimle — 2021-09-24T16:49:51.986Z

This is a crosspost from my site: It's Good Enough -- A Party Game.

"One hundred and forty-three thousand, two hundred and twenty steps.

It was doable."
-- "Worm, Interlude 29" by Wildbow

I had this idea after a friend and I talked about games and competitiveness. The objective of the game is to be the most average person at being average.

Rules

The game requires at least three players.

Each player presents an integer from 0 to 100.[1]

All players must present their number at the same time.[2]

The game lasts for at least three rounds. The number of rounds to be played is set before the game starts.[3]

The player who presents a number that is the median of all numbers presented is awarded a point. If there are an even number of players, then the two players which are closest to the median are awarded a point.[4]

If two or more players present the same number, they are disqualified from that round and cannot score any points. They are also fully ignored in the finding of the median for scoring.

If all players but two present the same number, the two players who are different score one point each.

If all players but one present the same number, the one player who is different scores a point.

If all players present the same number, no one scores any points.

Repeat until the set number of rounds is reached. All points are tabulated. The winner is the player whose number of points is the median among the numbers of points of all players.

Duplicate scores are considered to only be one score for the purposes of finding the median.[5]

Sample game one

Players
Round 1
Round 2
Round 3
Round 4
Round 5

Alice
99
50
73
88
97

Bob
0
50
22
70
78

Carol
50
50
6
75
39

Dave
49
1
25
97
27

Winner?
Carol, Dave
Dave
Bob, Dave
Carol, Alice
Carol, Bob

Sample scoring one

Players
Scores

Alice
1

Bob
2

Carol
3

Dave
3

Winner?
Bob!

Bob is the winner as Carol and Dave have the same score -- their scores are treated as one number. In {1, 2, 3}, the median is 2.

Sample game two

Players
Round 1
Round 2
Round 3
Round 4
Round 5

Xander
4
87
55
23
50

Yvonne
22
83
55
66
50

Zachary
89
59
0
50
50

Winner?
Yvonne
Yvonne
Zachary
Zachary
No one

Sample scoring two

Players
Scores

Xander
0

Yvonne
2

Zachary
2

Winner?
Tie.

There is a tie.

Ties?

In keeping with the theme of medianness, ties are resolved in the following manner. The first and last rounds ...