trentmkelly/LessWrong-43k huggingface dataset:
We need a new philosophy of progress
by jasoncrawford — 2021-08-23T21:31:40.171Z
Link: https://rootsofprogress.org/a-new-philosophy-of-progress

We live in an age that has lost its optimism. Polls show that people think the world is getting worse, not better. Children fear dying from environmental catastrophe before they reach old age. Technologists are as likely to be told that they are ruining society as that they are bettering it.

But it was not always so. Just a few centuries ago, Western thinkers were caught up in a wave of optimism for technology, humanity and the future, based on the new philosophy of the Enlightenment.

The Enlightenment was many things, but in large part, it was a philosophy of progress.

At the end of the 18th century, the Marquis de Condorcet gave expression to this philosophy and its optimism in his Sketch for a Historical Picture of the Progress of the Human Mind. In it, he predicted unlimited progress, not only in science and technology, but in morality and society. He wrote of the equality of the races and the sexes, and of peace between nations.

His optimism was all the more remarkable given that he wrote this while hiding out from the French Revolution, which was hunting him down in order to execute him as an aristocrat. Unfortunately, he could not hide forever: he was captured, and soon died in prison. Evidently, the perfection of mankind was slow in coming.

Material progress, however, was rocketing ahead. After the end of the Napoleonic Wars in Europe, and then the Civil War in America, the path was clear for technological innovation and economic growth: the railroad, the telephone, the light bulb, the internal combustion engine.

By the end of the 19th century, it was obvious that the world had entered a new age, and progress was its watchword. The naturalist Alfred Russel Wallace (best known for his work on evolution with Darwin) titled his book about the 1800s The Wonderful Century. In it, he attributed twenty-four “great inventions and discoveries” to the 19th century, as compared with only fifteen in all of human history preceding it. The boundless optimism of the early Enlightenment seemed to have been justified.

And if the material progress prophesied by Francis Bacon could be realized, perhaps the moral progress prophesied by Condorcet would come true as well. By the end of the 19th century, slavery had been ended in the West, and some hoped that the growth of industry and the expansion of trade would lead to and end to war and a new era of world peace.

They were wron...
Welcome to Northampton Astral Codex Ten Meetup
by Alex Liebowitz — 2021-08-23T21:18:22.372Z

We started with the 2018 Meetups Everywhere with a showing of 12 people. We've gained and lost some over time and currently have a rotation of about 15-20 regulars, of which anywhere from 4 to 7 might come on a typical meetup. Topics range wildly and on a given day we might talk about ACX material 50% of the time or not at all.

We usually meet at the Common House at Rocky Hill Cohousing (where one of our members lives), and occasionally when it isn't available we fall back to several bars and restaurants in Northampton, most often Packard's.

Needless to say, rationalists and EA folks of all stripes are welcome, including total newcomers. We've had people ranging from old-school rationalists dating back before Less Wrong, to people who just heard about rationalism the same day, to a literal baby (who, frankly, didn't really pull his weight in the conversation).

Look forward to seeing you!
Randal Koene on brain understanding before whole brain emulation
by Steven Byrnes — 2021-08-23T20:59:35.358Z

Background / Context

Some people, including me, think that it will be very hard and risky to write and run Artificial General Intelligence (AGI) code without risking catastrophic accidents—up to and including human extinction (see for example my post

here

).

If that’s true, one option that’s sometimes brought up is a particular

Differential Technological Development

strategy, wherein we specifically try to get the technology for

Whole Brain Emulation

(WBE) before we have the technology for writing AGI source code.

Would that actually help solve the problem? I mean, other things equal, if flesh-and-blood humans have probability P of accidentally creating catastrophically-out-of-control AGIs, well, emulated human brains would do the exact same thing with the exact same probability…. Right? Well, maybe. Or it might be more complicated than that. There’s a nice discussion about this in

the report from the 2011 “Singularity Summit”

. That's from a decade ago, but AFAICT not much progress has been made since then towards clarifying this particular strategic question.

Anyway, when considering whether or not we should strategically try to differentially accelerate WBE technology, one important aspect is whether it would be feasible to get WBE without incidentally first understanding brain algorithms well enough to code an AGI from scratch using similar algorithms. So that brings us to the point of this post:

The quote

Randal Koene

is apparently very big in WBE circles—he coined the term “WBE”, he’s the co-founder of

The Carboncopies Foundation

, he’s a PhD computational neuroscientist and neuroengineer, etc. etc. Anyway, in a recent interview he seems to come down firmly on the side of “we will understand brain algorithms before WBE”. Here’s his reasoning:

Interviewer (Paul Middlebrooks): Engineering and science-for-understanding are not at odds with each other, necessarily, but they are two different things, and I know this is an open question, but in your opinion how much do we need to understand brains, how much do we need to understand minds, and what is a mind, and how brains and minds are related, how much is understanding part of this picture? Randal, let’s start with you.

Interviewee (Randal Koene): I think I may have shifted my views on that a bit over time, as I understand more about the practical problem of how would you get from where we are to where you can do WBE

...
Generator Systems: Coincident Constraints
by J Bostock — 2021-08-23T20:37:38.235Z

The Prototype Plane Perfecter

You are asked with improving the design of a plane, which keeps falling out of the sky when it reaches 80 mph. This makes sense, as it is a prototype, put together with no knowledge of high-speed flight. Unfortunately they always seem to disappear over the horizon just before failure, and crash in such a huge fireball that no evidence as to the cause can be collected.

You have three hypotheses as to why: the engine is spinning itself apart; the wings are falling off; the instruments are failing. Each of these requires some cost to improve, so your bosses are insistent that you solve the issue, and no more. You make three new planes.

Each of them sets off, and each of them crashes at the exact same distance from the runway (to within random error of course). None of the improvements have increased the top speed.

Naturally, you assume that none of these are constraining it. You look for other reasons the planes might be crashing.

The Mortal Trees

A scattered group of trees wish to live forever. They do not age, so the only threat to them is being toppled by the wind. Each stormy night they all fear terribly for their lives. Their scientist-trees get to work. They find that 80 mph wind is generally fatal.

One school of medical researcher-trees studies trunks. They believe trunk-snapping is the ultimate cause of toppling. With a strong regiment of lignin-enhancers, they manage to fortify themselves physically.

Another school studies roots. They believe that uprooting is the ultimate cause of toppling. With soil rigidification, they ensure their balance is perfect.

The next storm, each waits with baited breath. Both groups find they have lost some of their own, and barely any fewer than the trees in the control group. Those still standing make peace, and accept the inevitability of toppling.

Lessons

In the first story, it is not so clear what's happening. In the second, it is. The difference is that the generator system for prototype plane designs is very different from the generator system for tree designs.

If a plane is put together with no knowledge of high speed flight, then the chances of all of its systems failing at exactly the same speed is very unlikely. In fact this is the case for most systems. In plant growth, one nutrient is usually limiting, the same is often true for manufacturing. In this case, locating the limiting factor ...
An Open Letter To Myself On How To Not Get Any Work Done.
by HarryO — 2021-08-23T07:18:02.254Z

This is a letter to myself on how to not get any work done. A skill I have perfected over years of practice. And leveraged to its full potential for most of my life. You could say I'm a master at it.

How To Not Get Any Work Done(while simultaneously feeling like you're getting work done)

Dear future Harry,

In your old age, I don't want you to get too good at doing things you want to do. So, I have taken the liberty of jotting down some tips on how not to do things you want to do. Follow these and you won't need to worry about doing things you want to do ever again.

General Tips

This is the best tip I have for you. Your phone notifications need to be on. And you need to be in as many large active Whatsapp and Messenger conversations as possible.

Keep your phone on your person. Better yet, put it within eyesight. Preferably next to your laptop or desktop.

Consume snacks until you feel sick. Then keep snacking.

Take a toilet break every 7 minutes.

Think about your to-do list constantly and half-assedly complete items on it.

Work on something you don't want to be working on.

Don't track your time. So you can fool yourself into thinking you have worked for 10 minutes.

Expect perfection the first time around. Don't allow any mistakes.

Tips On Your Work/Study Space

Make sure it's as messy as possible. Deep work can't sneak in while there is a blockade of crap surrounding you.

Make sure you can see the fridge or open cupboard.

If you can, sit where you can see lots of people.

Prowl around your work/study space looking for potential victims to have superficial conversations with.

me getting distracted

Tips For When Your Working On A Computer

Have as many apps open as possible. Turn their notifications on.

Ensure your internet browser has a minimum of 10 tabs open. Preferably about future shopping purchases or YouTube videos — videos with productivity or focus tips are an excellent choice.

Split-screen your computer allowing your favourite show to play in the background.

Have a messy desktop background. Cover it with lots of shortcuts. And while you're at it, put your favourite video game shortcut in the middle.

Play loud fast paced music with lyrics. Make sure to change the song every 2 minutes.

When you can't decide on a song, spend 45 minutes reading articles about the best music to

...
Cryonics prices were more complicated when I double-clicked
by tcelferact — 2021-08-23T01:26:41.592Z

I know there are a few folks signed up for cryonics on LessWrong. At time of writing, I have decided not to do so. This covers part of the research I did while deciding: how expensive is cryonics?

Life Insurance

I am in Canada where only one insurance company offers life insurance that will pay out to a cryonics company (I don't know why they care, but that's another question).

A lifetime insurance premium with the company that pays out $180K CAD will cost me $89.45 CAD per month up to 100 years of age.

But researching life insurance taught me lots about compounding interest. I realized that due to compounding interest, I can do better than the above by getting 20 year term insurance. If I do that, I will pay $16.60 per month for the first 20 years, $74.50 for the second 20, and $368.93 if necessary after that.

Assuming even low stock market performance of +7%/year, if I just invest the difference in lifetime vs 20 year term premium costs, compounding interest on that difference will give me the $180K after 45 years, plus extra cash the longer I live. At 12% growth per year I'd have the $180K after 32 years and $20M by the age of 100.

This taught me that regular savings deposits while I'm still young are a great idea. It also persuaded me that thinking about the cost of cryonics as a $20 per month subscription is not a great idea. Cryonics is a commitment to a five- or six-figure payout in your will that could have been inherited by another individual or organization, and that '$20 a month subscription' is just insurance in case you die before you've saved the requisite funds.

A five- or six- figure sum + membership fees + insurance when you're young in exchange for even a low probability chance of dodging death still sounds like a good deal to me, and I suggest advocates be more deliberate about framing the cost of cryonics in these terms.

(An aside: There are cryonics advocates who've written about why it isn't cheap, and you can find a different take to mine from Rudi Hoffman here. He doesn't address the effects of compounding interest, and I think they are a strong argument against his claim that 'the best life insurance for anyone to have is the one that is in force when you “die.”')

Standby, Stabilization and Transport

If you're living in the US, you can find a company responsible for standby, stabilization, and transport to your Cryonics provi...
A taxonomy of coordination problems
by damiensnyder — 2021-08-22T23:10:00.013Z

The LessWrong coordination/cooperation tag describes coordination as:

the challenge of distinct actors being able to jointly choose their actions to achieve a favorable outcome. [...] A closely related concept is that of cooperation – multiple actors choosing their actions in ways that maximize collective value despite the temptation of greater short-term individual gain by acting to the detriment of the group/other actors.

For the purposes of this post, I will define a "coordination problem" as a problem such that a coordinated group will likely create a good solution, but without coordination, an individual is unlikely to take steps toward that solution. A classic example of a coordination problem is a stag hunt, because the group can create a good solution (by all choosing stag), but until that problem is solved, an individual is more likely to choose rabbit. An example of a non-coordination problem is convincing people to get vaccinated. This is not a coordination problem, because most people are incentivized to get vaccinated regardless of coordination. (Those who reject vaccinates are still usually incentivized to get vaccinated, though they may believe otherwise.)

Coordination problem is a useful category, but it describes several distinct types of obstacles, which require different approaches to solve. I have identified five types of obstacles, but this is not the only way to categorize them. I am open to suggestions for adding or amending categories.

Taxonomy

1. Participants cannot communicate easily

Some coordination problems could be easily solved if participants could more easily talk to one another. For example: If I tried to meet my friends at a restaurant, but we couldn't message or visit each other beforehand, it would be pretty hard. We wouldn't know where everyone else would go or when, so we would have to hope to get lucky.

An obvious solution to problems like this is to facilitate communication better. If my friends and I could text, we could figure out restaurant plans easily. If this is impossible, another solution is to have a Schelling point solution that everyone can fall back on. This can be coordinated beforehand, or in a pinch you can guess by trying to model everyone else's thinking. For example, maybe there's a restaurant that my friends and I have been to a lot, so if I go there at 7 I'll probably run into some of them. This mi...
The Death of Behavioral Economics
by habryka — 2021-08-22T22:39:12.697Z
Link: https://www.thebehavioralscientist.com/articles/the-death-of-behavioral-economics

Edit: I recommend reading Scott's response to this essay in addition to the essay itself.

I've been tracking the replication crisis and how it affects a bunch of behavioral economics for a while. I found reading this post useful for a particularly negative take. Some key quotes:

It sure does look alive... but it's a zombie—inside and out.

Why do I say this?

Two primary reasons:

Core behavioral economics findings have been failing to replicate for several years, and *the* core finding of behavioral economics, loss aversion, is on ever more shaky ground.
Its interventions are surprisingly weak in practice.

Because of these two things, I don't think that behavioral economics will be a respected and widely used field 10-15 years from now.

[...]

It turns out that loss aversion does exist, but only for large losses. This makes sense. We *should* be particularly wary of decisions that can wipe us out. That's not a so-called "cognitive bias". It's not irrational. In fact, it's completely sensical. If a decision can destroy you and/or your family, it's sane to be cautious.

"So when did we discover that loss aversion exists only for large losses?"

Well, actually, it looks like Kahneman and Tversky, winners of the Nobel Prize in Economics, knew about this unfortunate fact when they were developing Prospect Theory—their grand theory with loss aversion at its center. Unfortunately, the findings rebutting their view of loss aversion were carefully omitted from their papers, and other findings that went against their model were misrepresented so that they would instead support their pet theory. In short: any data that didn't fit Prospect Theory was dismissed or distorted.

I don't know what you'd call this behavior... but it's not science.

This shady behavior by the two titans of the field was brought to light in a paper published in 2018: "Acceptable Losses: The Debatable Origins of Loss Aversion".

I encourage you to read the paper. It's shocking. This line from the abstract sums things up pretty well: "...the early studies of utility functions have shown that while very large losses are overweighted, smaller losses are often not. In addition, the findings of some of these studies have been systematically misrepresented to reflect loss aversion, though they did not find it."
Welcome to East Bay Thursday Dinner [Edit With Your Details]
by pax perplexus — 2021-08-22T21:15:41.186Z

(The following are our suggestions for what kind of information is best to include in the welcome post of your group, feel free to replace them with whatever you think is best)

What kind of events does your group usually run? What does it usually do?

How frequently does your group organize events or meet?

Who would be a good fit for you group?

Should they have any particular skills or have done some specific background reading?
Is top-down veganism unethical?
by Malmesbury — 2021-08-22T16:53:35.102Z
Link: https://www.telescopic-turnip.net/hogwash/is-top-down-veganism-unethical/

« Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away. »
– Antoine de Saint-Exupéry

Remember how the vegetables we eat everyday are very different from their ancestors from a few centuries ago? The same is true for animals. In half a century, farmers bred increasingly large races of chicken. Here is a comparison of the size of bones for modern and ancestral chickens:

Scale bar: 2 cm (source)

The leg on the left belongs to a modern broiler chicken. The one on the right belongs to a wild jungle chicken.

From the perspective of meat production, this is an improvement. From the perspective of animal suffering, things are more uncertain. Contemporary chicken are reaching pantagruelian proportions and now they have trouble walking and their legs often break under their own weight. One might even go as far as worrying this is a little bit unethical. Fortunately, there are solutions. I can think of three of them – the first two, you already know. The last one, however, I never see discussed anywhere.

1. Non-meat

The most fashionable solution now is to replace meat with plant-based construction materials that are claimed to look and taste similar to meat. My main problem is that plant-based meat is, at best, overlapping with real meat: the best-quality plant-meat is comparable to the lowest-quality meat. If you think the vegan burgers make accurate simulacra of meat, I’m afraid you are eating too much heavily processed shitty meat. We are still very far from the impossible® A5-rated wagyu, the impossible® pressed duck, the impossible® volaille de Bresse “en vessie” (which must be gently cooked in a plant-based impossible® pork bladder to be valid). As a typical Westerner, i have the opportunity to eat only about 90,000 meals in a lifetime, there is no way I’m wasting any of them on sub-delicious food. Still, this approach deserves some praise for actually existing and working, which cannot be said about the second approach –

2. Lab-grown meat

To be fair, the interest in lab-grown meat is increasing, slowly and steadily. Perhaps it will eventually catch up on sexbots. Here is a Frontiers review from last year, whose title alone drives the point home: “The Myth of Cultured Meat”. It is not that bad, really, but the current prototypes look like attempts at emulating the vegan attempts at emulating real meat. I don’...
AI Risk for Epistemic Minimalists
by Alex Flint — 2021-08-22T15:39:15.658Z

Financial status: This is independent research, now supported by a grant. I welcome further financial support.

Epistemic status: This is an attempt to use only very robust arguments.

Outline

I outline a case for concern about AI that does not invoke concepts of agency, goal-directedness, or consequential reasoning, does not hinge on single- or multi-principal or single or multi-agent assumptions, does not assume fast or slow take-off, and applies equally well to a world of emulated humans as to de-novo AI.

The basic argument is about the power that humans will temporarily or permanently gain by developing AI systems, and the history of quick increases in human power.

In the first section I give a case for paying attention to AI at all.

In the second section I give a case for being concerned about AI.

In the third section I argue that the business-as-usual trajectory of AI development is not satisfactory.

In the fourth section I argue that there are things that can be done now.

The case for attention

We already have powerful systems that influence the future of life on the planet. The systems of finance, justice, government, and international cooperation are things that we humans have constructed. The specific design of these systems has influence over the future of life on the planet, meaning that there are small changes that could be made to these systems that would have an impact on the future of life on the planet much larger than the change itself. In this sense I will say that these systems are powerful.

Now every single powerful system that we have constructed up to now uses humans as a fundamental building-block. The justice system uses humans as judges and lawyers and administrators. At a mechanical level, the justice system would not execute its intended function without these building-block humans. If I turned up at a present-day court with a lawsuit expecting a summons to be served upon the opposing party but all the humans in the justice system were absent then the summons would not end up being served.

The Google search engine is a system that has some power. Like the justice system, it requires humans as building-blocks. Those human building-blocks maintain the software, data centers, power generators, and internet routers that underlie it. Although individual search queries can be answered without human intervention, the transitive...