trentmkelly/LessWrong-43k huggingface dataset:
The AI Timelines Scam
by jessicata — 2019-07-11T02:52:58.917Z
Link: https://unstableontology.com/2019/07/11/the-ai-timelines-scam/

[epistemic status: that's just my opinion, man. I have highly suggestive evidence, not deductive proof, for a belief I sincerely hold]

"If you see fraud and do not say fraud, you are a fraud." --- Nasim Taleb

I was talking with a colleague the other day about an AI organization that claims:

AGI is probably coming in the next 20 years.

Many of the reasons we have for believing this are secret.

They're secret because if we told people about those reasons, they'd learn things that would let them make an AGI even sooner than they would otherwise.

His response was (paraphrasing): "Wow, that's a really good lie! A lie that can't be disproven."

I found this response refreshing, because he immediately jumped to the most likely conclusion.

Near predictions generate more funding

Generally, entrepreneurs who are optimistic about their project get more funding than ones who aren't. AI is no exception. For a recent example, see the Human Brain Project. The founder, Henry Makram, predicted in 2009 that the project would succeed in simulating a human brain by 2019, and the project was already widely considered a failure by 2013. (See his TED talk, at 14:22)

The Human Brain project got 1.3 billion Euros of funding from the EU.

It's not hard to see why this is. To justify receiving large amounts of money, the leader must make a claim that the project is actually worth that much. And, AI projects are more impactful if it is, in fact, possible to develop AI soon. So, there is an economic pressure towards inflating estimates of the chance AI will be developed soon.

Fear of an AI gap

The missile gap was a lie by the US Air Force to justify building more nukes, by falsely claiming that the Soviet Union had more nukes than the US.

Similarly, there's historical precedent for an AI gap lie used to justify more AI development. Fifth Generation Computer Systems was an ambitious 1982 project by the Japanese government (funded for $400 million in 1992, or $730 million in 2019 dollars) to create artificial intelligence through massively parallel logic programming.

The project is widely considered to have failed. From a 1992 New York Times article:

A bold 10-year effort by Japan to seize the lead in computer technology is fizzling to a close, having failed to meet many of its ambitious goals or to produce technology that Japan's computer industry wanted.

...

That attitude is a sharp contrast t

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Magic is Dead, Give me Attention
by Hazard — 2019-07-10T20:15:24.990Z

(cross posted from my personal personal blog (not to be confused with my personal blog)

Back story

So here's the thing. I absolutely LOVE attention. I also HATE asking for attention. This past weekend I've processed those last two statements on a much deeper level than I have previously. Sometimes you need to rediscover an insight multiple times to really get it.

The most recent batch of introspection was prompted by the book "Magic is Dead" by Ian Frisch. Spoiler, I'm a semi-professional close up magician and have a vested interest in many things magic. Ian was describing Chris Ramsay, the quintessential young-blood social media based cool kid magician. A quote:

[...] Ramsay's style has since evolved into a more high-end street-wear, hypebeast-esque aesthetic: A Bathing Ape jacket, Supreme cap and hoodie, adidas by Pharrell Williams NMD sneakers, etc.

I don't even know what A Bathing Ape jacket looks like, nor why the "A" is capitalized, but my gut reaction is revulsion. I know just enough about Supreme and "hypebeast"s to know that I don't like them. But why? Why do I spit venom when I hear about new performers on social media trying to "make magic cool again"?

Long story short, I LOVE attention, and I HATE asking for it. This has been the case since middle school. The hating to ask part comes with an attitude of "Fuck you, I'm not going to beg for you to give me something". So I had a chip on my shoulder in regards to asking for people's attention, and like any good chip, it needed a rationalized narrative to justify its existence. "People who need other people to pay attention to them are weak", "Wow hazard, you're such a strong rugged individual for not needing other people's attention"

Notice the switch from "I don't like asking for attention" to "I don't need attention". It's subtle. Sure took me 8+ years to notice.

As you may have guessed, I didn't magically stop wanting/needing attention from people in middle school. I just learned a new strategy to meet the need. The strategy was the personality that I began to develop in middle school and high school, that of the unflappable competent marauder. I always played calm and collected, I worked hard to get good at the tasks at hand (my primary social gro...
How can guesstimates work?
by Bird Concept — 2019-07-10T19:33:46.002Z

[Epistemic status: background is very hand-wavy, but I'd rather post a rough question than no question at all. I'm very confident that the two ingredients -- illegible cultural evolution and guesstimation -- are real and important things. Though the relation between the two is more uncertain. I'm not that surprised if my question ends up confused and dissolved rather than solved by answers.]

For a large part of human history, our lives were dictated by cultural norms and processes which appeared arbitrary, yet could have fatal consquences if departed from. (C.f. SSC on The Secret of Our Success, which will be assumed background knowledge for this question.)

Today, we live in a world where you can achieve huge gains if you simply "shut up and multiply". The world seems legible -- I can roughly predict how many planes fly every day by multiplying a handful rough numbers. And the world seems editable -- people who like to cook often improvise: exchanging, adding and removing ingredients. And this seems fine. It certainly doesn't kill them. Hugely succesful companies are built around the principle of "just try things until something breaks and then try again and improve".

I still think there are still large amounts of illegible cultural knowledge encoded in institutions, traditions, norms, etc. But something still seems very different from the horror stories of epistemic learned helplessness Scott shared.

What changed about the world to make this possible? How can guesstimates work?

Some hypotheses (none of which I'd put more than 15% on atm):

Almost all important aspects of our lives our governed by some kind of technology that we built (tables, airplanes, computers, rugs, restaurants, microwaves, legal contracts, clocks, beds, clothes, ... and so on and so forth). Technological development outpaced cultural evolution. The modern world is more legible and editable for the same reason that a codebase is more legible and editable than DNA.
Most systems that govern our lives have been optimised way harder since the industrial revolution and the ability to achieve economies-of-scale in a global market. Things are generally closer to optimal equilibria, and equilibria are more legible/predictable than non-quilibria.
The things we really care about today often follow very heavy-tailed distributions. Hence even a very rough gues

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Types of Boltzmann Brains
by avturchin — 2019-07-10T08:22:22.482Z
Link: https://philpapers.org/rec/TURTOB-2?fbclid=IwAR1ksDURr8dcC4g3CiKw-pJ1-HzY6l33ntihOUc6kWUnh8M5luwXcFR21HE

If at least one type of BBs is measure-dominating, we are BBs. To explore chances for that, we need a classification of the possible BBs. Around 10 types of BBs so far identified and are listed in our article "Types of Boltzmann brains."

However, there it is not a big problem to be a BB. Firstly, because BB-observer-moments could create chains, like in Egan's "dust theory", and these chains will look like normal worlds. Second, because for any BB there is a real world mind in the same observer state (if any real world minds exist).

Also, the argument for randomness of experiences of BBs is not working, because if you are a BB, you can't make true judgements about the randomness of the things you observe. One could see completely random mess and still think that it is in order.

Another source of non-randomness in BBs is that they may be structured as random neural nets, because it is needed to make an "act of observation". A cat-dog classifier would classify any random input noise as either "cat" or "dog", thus increasing the orderliness of the output, despite the randomness of the input.
Schism Begets Schism
by Davis_Kingsley — 2019-07-10T03:09:41.562Z

Related: On the importance of Less Wrong, or another single conversational locus

One thing that seems to be a pattern across the history of human organizations, projects, and even social scenes is that schism begets schism. In other words, if there is a large and central space, once people start splitting off from it this can often lead to the "floodgates opening" and lots and lots of new groups forming - often in a way that even those who initially wanted to change things dislike!

Perhaps the most obvious example of this is Protestantism. Martin Luther did not want to start his own church, told people not to call themselves "Lutherans", and disagreed quite aggressively with many of those who are now lumped in with him as "Protestant Reformers". However, once challenges to the authority and unity of the Church got started, they were hard to stop, and Luther soon found that those around him had at times gone in directions he did not want -- and now there are over 40 different Lutheran denominations in North America alone, to say nothing of all the other Protestant groups!

However, such a trend is not only limited to religious groups. Political movements sometimes have a similar scenario befall them -- for instance, the Republican side of the Spanish Civil War was substantially harmed by internal schisms, subfactions, and disputes. To use a less consequential example, I've been a part of online communities that have been hurt by repeated schisms over moderation policy -- once people get fed up with the moderation in one place, they start another with much the same purview but different moderators.

Once schism gets going, it can be hard to stop - and once things get split, much of the benefit of a single conversation locus begins to degrade. Indeed, the "LessWrong diaspora" quite harmed this project -- we still haven't fully recovered from having the community split as much as it did, even though things have been improving a bit on that front more recently.

Now, some will say that perhaps splits are good -- perhaps one space isn't right for everyone, and it would be better to have a diverse range of norms that can appeal to different interests. Hence we see things like the archipelago model of community standards, which aim to set up a situation where one broader community contains many subgroups with their own ...
Do bond yield curve inversions really indicate there is likely to be a recession?
by Ben Goldhaber — 2019-07-10T01:23:36.250Z

I've seen some recent commentary that the bond yield curve indicates there is likely to be a recession in the next year.

For example, from the New York fed:
https://www.newyorkfed.org/…/r…/capital_markets/Prob_Rec.pdf

and commentary:

https://www.newyorkfed.org/medialibrary/media/research/capital_markets/Prob_Rec.pdf
https://www.wsj.com/…/government-bond-market-measure-says-r…

I'm not sure how much stock to put into this, or for that matter what actions I should take if I expected there would be a recession in the next year.

Two part question:

How much confidence should I have in the yield curve inversion signal that a recession would happen by July 1st, 2020?
If I expected there would be a recession, what actions make sense to take as a personal investor? Or even more generally?
Would you join the Society of the Free & Easy?
by David Gross — 2019-07-10T01:15:27.002Z

Summary:

This post describes a peer-supported, self-directed, free (gratis y libre) method of self-improvement by means of practical exercises designed to deliberately instill useful habits. We have just gone public and I invite you to join us.

The “Society of the Free & Easy” is a group of people who are trying to help one other become better and more effective. We use self-directed, peer-supported, practical exercises to strengthen the skills that lead to a thriving, flourishing life.

The theory we’re operating under is this:

There are many character traits that help people to thrive.
These character traits are, by and large, habits that can be acquired and integrated into one’s character through practice.
We can help each other design and practice exercises that establish and strengthen these habits.
By doing this, we will improve and also benefit the culture around us.

In classical philosophy, the skills and habits that tend toward a thriving, beneficial life were called “The Virtues.” There was no single, canonical list of virtues that everybody agreed on, though many people and traditions came up with lists they liked.

We don’t have a canonical list either. Instead, we have collected (so far) about 250 different words that describe traits that may count as virtues. We use our list more as a menu than a scripture; we don’t have any dogma about which ones are the right ones or the most important ones. Each of us decides for herself or himself which virtues we think are most important and which ones we want to work on.

These virtues can be roughly divided into three categories:

Intellectual virtues, like imagination, rationality, curiosity, or attention
Social virtues, like honesty, hospitality, leadership, tact, or justice
Internal virtues, like honor, courage, endurance, hope, or initiative

Some virtues we learned as children, and they’re second-nature. Others we never picked up, and we find them difficult or frustrating to practice even as we admire them in others. Everybody has a different mix of virtues they’re fluent in and virtues they struggle with.

The key theory animating our project is this: A virtue is a sort of habit. You can acquire or strengthen such a habit by practicing it. With regular, deliberate practice, the habit will eventually become part of your character.

We also suspect that virtues have a way of building on each other. If you strengthen t...
Diversify Your Friendship Portfolio
by Davis_Kingsley — 2019-07-09T23:06:41.146Z

In investing, a common piece of advice recommends a diversified portfolio - in other words, having investments from a wide range of areas to avoid a crash in one area wiping out all your investments. Similarly, I have found that it can be beneficial to have a diversified friendship portfolio - in other words, friends across a wide range of communities or social circles.

For instance, I have a group of friends that I've known mostly since elementary/middle school, a group of friends that I know from the rationalist and EA community in Berkeley, a group of friends that I know from playing certain games competitively... there is some overlap between these groups, but by and large they are separate, and this can be quite valuable.

Because I'm active in multiple circles, if strange things are happening in one community I can step into another. If I need advice on a sensitive situation, I have people who know me well and aren't close to the matter to draw upon. Further, having these sorts of resources and perspectives available can open up options that might otherwise be difficult - if, for instance, I decided I could no longer be a part of one of those communities, leaving wouldn't be the end of my social life.

I sometimes see people -- in the rationalist community or elsewhere -- putting "all their eggs in one basket" when it comes to friendship, and I think that can often lead to pitfalls. If all your friends are from work, what happens if you leave your job? If all your friends are from a certain hobby, what happens if you get bored of it? If all your friends are from a certain social scene, what happens if there's a bunch of drama and that community splits? Having other social connections and communities to interact with can really help with such scenarios.

Lastly, I want to point out that having a range of friend groups can be a useful insulator against bad ideas. [1] Sometimes strange and unwelcome fads can spread across a community, and if that's the case it can suddenly become a less appealing place. If you have several friend groups to choose from, such things are much easier to "ride out" than if your whole social circle is suddenly into whatever new weird thing. Further, being able to run new stuff by people you know in other communities can serve as a good check on groupthink - being able to say "hey,...
The I Ching Series (2/10): How should I prioritize my career-building projects?
by DirectedEvolution — 2019-07-09T22:55:05.848Z

Note: See comments for my actual writings in response to I Ching Hexagram interpretations. This main post is for meta-reflection on the experiment.

The Rules:

No divination-related questions.
I will do ten I Ching sessions, about every six weeks. Eight out of ten sessions must produce at least one new piece of evidence, or else I'll abandon the practice. Overall, the evidence should fall within at least two of the following categories. Final evaluation: this session counts as a success.
Definition of valid evidence

Serious work, and "mid-term exam" success, on novel ideas generated by the I Ching, or on projects that I’ve neglected at least 6 weeks.
Insights that I can articulate, that I still fully agree with after six weeks, that seem to improve my daily decisions and mental health, and that seem sensible to my friends. I will keep the fact that I used the I Ching to generate these insights a secret until the end of the project.

I will treat the most challenging parts of my reading as if they were true and important. After all, the strangest parts of the reading might be most valuable, if the point of the I Ching is to bust you out of ruts.
Week 6 update (final):

I feel that my EA community projects and networking were successes.
Just yesterday, I discovered the concept of "Deep Work" and implemented a rules-based plan that I think will help me both work, play, and rejuvenate more effectively.
My habit of more careful academic work paid off, but I still was not 100% consistent with following the detailed assignment specs from my last class.

Week 4 update:

My EA community projects work has continued to be fruitful. We've conducted many interviews with EA career changers, set up an EA video chat service that's been used by about 40 people, and have more in the works.
I have done a great deal of networking via email and in-person meetings in the last two weeks, which led me to decide to change colleges and helped me hone in on what I want to study. I've preserved what I learned from each of these meetings and correspondences in a journal, which I think may prove useful to others as well.
"Joy time" has remained mostly unrewarding, and my QoL has declined over the last two weeks. I intend to focus on planning novel, social, unruly and self-expressive activities, and using meditation or reading rather than pot and TV to relax.

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Are there easy, low cost, ways to freeze personal cell samples for future therapies? And is this a good idea?
by Eli Tyre — 2019-07-09T21:57:28.537Z

I happened to come across this old post from 2015, that (in a sort of round about way) endorses freezing some cell samples today, because having frozen cell samples from your youth might prove important for future anti-aging therapies.

I am somewhat skeptical of this being a major factor for anti-aging, but I wonder if others have more information.
Outline of NIST draft plan for AI standards
by ryan_b — 2019-07-09T17:30:45.721Z

Previously I posted on the National Institute of Standards and Technology's plan for AI standards, which is now open for public comment. Reading Federal documents is tedious, so I have provided an outline below.

Outline of the Draft Plan

1. Standards and Artificial Intelligence

A. Why is a plan for Federal engagement in AI technical standards needed?

AI is important to the economy and national security.
Executive Order (EO 13859)
Reflect Federal priorities for innovation, public trust, and public confidence in systems using AI
Enable creation of new AI-related industries, and adoption by current industries
Federal agencies are major players in developing and using AI
Definition of AI:

Note: While definitions of AI vary, for purposes of this plan AI technologies and systems are considered to comprise of software and/or hardware that can learn to solve complex problems, make predictions or undertake tasks that require human-like sensing (such as vision, speech, and touch), perception, cognition, planning, learning, communication, or physical action. Examples are wide-ranging and expanding rapidly. They include, but are not limited to, AI assistants, computer vision systems, biomedical research, unmanned vehicle systems, advanced game-playing software, facial recognition systems as well as application of AI in both Information Technology (IT) and Operational Technology (OT).

AI and Trustworthiness:

Increasing trust in AI technologies is a key element in accelerating their adoption for economic growth and future innovations that can benefit society. Today, the ability to understand and analyze the decisions of AI systems and measure their trustworthiness is limited. AI standards and related tools, along with AI risk management strategies, can help to address this limitation and spur innovation. Among the characteristics that relate to trustworthy AI technologies are accuracy, reliability, robustness, security, explainability, safety, and privacy–but there still is much discussion about the range of characteristics that determine AI systems’ trustworthiness. Ideally, these aspects of AI should be considered early on in the design process and tested during the development and use of AI technologies.

B. What are technical standards and why are they important?

ISO/IEC Guide 2:2004 Standardization:

a document, established by consensus and approved by a recognized body, that pr

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How can I help research Friendly AI?
by avichapman — 2019-07-09T00:15:09.335Z

I've just started my journey toward a PhD in machine learning. My first steps are in computer vision. But my long term goal is to be able to help in the effort to solve the alignment problem and produce Friendly AI before any non-friendly alternatives emerge.

What sort of trajectory should I aim for with my research? What sort of post-PhD jobs should I be aiming for? Who should I be making contacts with as I go?