trentmkelly/LessWrong-43k huggingface dataset:
How feasible is long-range forecasting?
by Ben Pace — 2019-10-10T22:11:58.309Z
Link: https://www.openphilanthropy.org/blog/how-feasible-long-range-forecasting

Lukeprog posted this today on the blog at OpenPhil. I've quoted the opening section, and footnote 17 which has an interesting graph I haven't seen before.

How accurate do long-range (≥10yr) forecasts tend to be, and how much should we rely on them?

As an initial exploration of this question, I sought to study the track record of long-range forecasting exercises from the past. Unfortunately, my key finding so far is that it is difficult to learn much of value from those exercises, for the following reasons:

Long-range forecasts are often stated too imprecisely to be judged for accuracy.
Even if a forecast is stated precisely, it might be difficult to find the information needed to check the forecast for accuracy.
Degrees of confidence for long-range forecasts are rarely quantified.
In most cases, no comparison to a “baseline method” or “null model” is possible, which makes it difficult to assess how easy or difficult the original forecasts were.
Incentives for forecaster accuracy are usually unclear or weak.
Very few studies have been designed so as to allow confident inference about which factors contributed to forecasting accuracy.
It’s difficult to know how comparable past forecasting exercises are to the forecasting we do for grantmaking purposes, e.g. because the forecasts we make are of a different type, and because the forecasting training and methods we use are different.

Despite this, I think we can learn a little from GJP about the feasibility of long-range forecasting. Good Judgment Project’s Year 4 annual report to IARPA (unpublished), titled “Exploring the Optimal Forecasting Frontier,” examines forecasting accuracy as a function of forecasting horizon in this figure (reproduced with permission):

This chart uses an accuracy statistic known as AUC/ROC (see Steyvers et al. 2014) to represent the accuracy of binary, non-conditional forecasts, at different time horizons, throughout years 2-4 of GJP. Roughly speaking, this chart addresses the question: “At different forecasting horizons, how often (on average) were forecasters on ‘the right side of maybe’ (i.e. above 50% confidence in the binary option that turned out to be correct), where 0.5 represents ‘no better than chance’ and 1 represents ‘always on the right side of maybe’?”

For our purposes here, the key results shown above are, roughly speaking, that (1) regular forecasters did approximately no better t...
I would like to try double crux. 
by valentinslepukhin — 2019-10-10T21:34:41.542Z

Hello,

I would like to try double crux https://www.lesswrong.com/posts/exa5kmvopeRyfJgCy/double-crux-a-strategy-for-resolving-disagreement with someone. My statement A is "There is God" (I indeed believe in it, it is not just for the sake of trying the technique). I have three cruxes (well, two and a half, to be honest), according to the rules I do not publish it here so that you would prepare your cruxes independently.

Thank you!
The Baconian Method (Novum Organum Book 1: 93-107)
by Francis Bacon — 2019-10-10T18:54:43.975Z

This is the seventh post in the Novum Organum sequence. For context, see the sequence introduction.

In this section, Bacon lists reasons why we should believe much greater progress in science is possible, and in doing so begins to describe his own inductivist methodology in detail.

We have used Francis Bacon's Novum Organum in the version presented at www.earlymoderntexts.com. Translated by and copyright to Jonathan Bennett. Prepared for LessWrong by Ruby.

Ruby's Reading Guide

Novum Organum is organized as two books each containing numbered "aphorisms." These vary in length from three lines to sixteen pages. Bracketed titles of posts in this sequence, e.g. Idols of the Mind Pt. 1, are my own and do not appear in the original.

While the translator, Bennett, encloses his editorial remarks in a single pair of [brackets], I have enclosed mine in a [[double pair of brackets]].

Bennett's Reading Guide

[Brackets] enclose editorial explanations. Small ·dots· enclose material that has been added, but can be read as though it were part of the original text. Occasional •bullets, and also indenting of passages that are not quotations, are meant as aids to grasping the structure of a sentence or a thought. Every four-point ellipsis . . . . indicates the omission of a brief passage that seems to present more difficulty than it is worth. Longer omissions are reported between brackets in normal-sized type.

Aphorism Concerning the Interpretation of Nature: Book 1: 93–107

by Francis Bacon

93. We have to assume that the force behind everything is God; for our subject matter—·namely nature·—is good in such a way that it plainly comes from God, who is the author of good and the father of light. Now in divine operations even the smallest beginnings lead unstoppably to their end. It was said of spiritual things that ‘The kingdom of God cometh not with observation’ [Luke 17:20], and it is the same with all the greater works of divine providence: everything glides on smoothly and noiselessly, and the work is well under way before men are aware that it has begun. And don’t forget Daniel’s prophecy concerning the last ages of the world: ‘Many shall run to and fro, and knowledge shall be increased’ [Daniel 12:4], clearly indicating that the thorough exploration of the whole world is fated to coincide with the advancement of the sciences. (By ‘fated’ I mean ‘destined by ·God’s· providence’. I wou...
"Mild Hallucination" Test
by Logan Riggs — 2019-10-10T17:57:42.471Z

In Scott Alexander's Lot's of People Going Around with Mild Hallucinations All the Time, he shows that several people not currently on LSD still experience mild hallucinations commonly associated with currently taking LSD.

I would like to test to see if I could teach you how to see these mild hallucinations, regardless of experience with psychedelics. Below are 3 tests that should take 1-2 minutes to complete. If you choose to complete 1 or more of these, please comment both failed and successful attempts. Please also comment if you can already see some of these, even if you think it seems obvious.

Test 1: Visual Snow

Description: See the Visual Snow Wiki for a nice visualization on the top-right. I would describe it as "jumpy spiderwebs made out of light", similar in feel to the "black stars" people see when feeling faint (when they get up too quick).

I would say it's NOT the same experience as mental imagination or eye floaters.

[Edit: Honestly I mixed up different phenomena for "visual snow" in my description. Here's the update:

1. Visual Snow - Like a million very tiny dots. Very much like static/white noise in the wiki. More visible in low light conditions or when you're tired. I saw it for the first time this (8/12) morning in low-light conditions.

2. Patterned lines (?) - Like the geometric/kaleidoscopic shape in this picture. Doesn't have to be that consistent or patterned but is better described by "lines" than either of the other two. This is what I meant by "jumpy spiderwebs made out of light" and what I thought visual snow was.

3. Blue-sky Sprites - The picture is a nice animation (can be seen without looking at the blue sky but apparently it's more prominent in that case). Dots and wisps the size of a mm or a little bigger. Maybe 5-100 at a time vs the million in "visual snow". Resembles afterimages and the "black stars" when feeling faint.

4. (Also very possible there's more that I've missed)

]

Test: For 1 minute (click here for a 1 minute timer), close your eyes and try to see the back of your eyelids using your peripheral vision. If a minute elapses with nothing resembling "visual snow", then it's a failure.

If it's a success, then try to see visual snow with your eyes open, again for 1 minute at most.

Test 2: Afterima

...
What is the real "danger zone" for food?
by jefftk — 2019-10-10T11:00:01.792Z

In my post about

keeping dry food
warm in school lunches I wrote that "The general rule is that hot
food shouldn't be below 140F (60C) for more than two hours, because
substantial bacteria can grow, and the closer it is to 100F (37C)the
worse it is." Someone said they had heard 130F (55C) was the limit,
and asked where this rule came from, and I read more about it.

Bacteria that's most dangerous to us generally thrive best around body
temperature, so the farther you get from 100F (37C) the better. Food
safety material generally describes this as a "danger zone", between
refrigerator temperature and cooking temperature. This is what's
represented in the FDA's Food Code:

3-501.19.B.1

Time as a Public Health Control: Time - maximum up to 4
hours:

The FOOD shall have an initial temperature of 5C (41F) or
less when removed from cold holding temperature control, or
57C (135F) or greater when removed from hot holding
temperature control

It gives more detail in section 3-501.16's "The Safety of the Time as
a Public Health Control Provision from Cooking Temperatures (135F or
above) to Ambient":

FDA conducted in-house laboratory experiments to test the
safety of the existing TPHC provisions of 4 hours without temperature
control starting with an initial temperature of 135F or
above. Clostridium perfringens was chosen to represent a worst case
scenario pathogen for foods allowed to cool from cooking temperatures
to ambient without temperature control, because its spores can survive
normal cooking procedures, it can grow at relatively high temperatures
(>120F) and it has a short lag period. C. perfringens spores were
inoculated into foods that were cooked and then cooled to yield a
cooling curve that would promote outgrowth as quickly as possible. The
growth data suggest that the existing 4-hour TPHC provision will be
safe for 6 hours after cooking, with the additional 2-hour margin of
safety built-in for consumer handling.

There's a great chart in The
"Danger Zone" Reevaluated by Frank Bryan, showing how long food
can spend at various temperatures:

Since the time I care about is 4hr from packing to eating, even under
the food code guidelines it should be safe if it starts at cooking or
refrigerator temperatures. To be safe, though, I'm going to keep
using the thermal mass t...
Thoughts on "Human-Compatible"
by TurnTrout — 2019-10-10T05:24:31.689Z

The purpose of this book is to explain why [superintelligence] might be the last event in human history and how to make sure that it is not... The book is intended for a general audience but will, I hope, be of value in convincing specialists in artificial intelligence to rethink their fundamental assumptions.

Yesterday, I eagerly opened my copy of Stuart Russell's Human Compatible (mirroring his Center for Human-Compatible AI, where I've worked the past two summers). I've been curious about Russell's research agenda, and also how Russell argued the case so convincingly as to garner the following acclamations from two Turing Award winners:

Human Compatible made me a convert to Russell's concerns with our ability to control our upcoming creation—super-intelligent machines. Unlike outside alarmists and futurists, Russell is a leading authority on AI. His new book will educate the public about AI more than any book I can think of, and is a delightful and uplifting read.—Judea Pearl

This beautifully written book addresses a fundamental challenge for humanity: increasingly intelligent machines that do what we ask but not what we really intend. Essential reading if you care about our future. —Yoshua Bengio

Bengio even recently lent a reasoned voice to a debate on instrumental convergence!

Bringing the AI community up-to-speed

I think the book will greatly help AI professionals understand key arguments, avoid classic missteps, and appreciate the serious challenge humanity faces. Russell straightforwardly debunks common objections, writing with both candor and charm.

I must admit, it's great to see such a prominent debunking; I still remember, early in my concern about alignment, hearing one professional respond to the entire idea of being concerned about AGI with a lazy ad hominem dismissal. Like, hello? This is our future we're talking about!

But Russell realizes that most people don't intentionally argue in bad faith; he structures his arguments with the understanding and charity required to ease the difficulty of changing one's mind. (Although I wish he'd be a little less sassy with LeCun, understandable as his frustration may be)

More important than having fish, however, is knowing how to fish; Russell helps train the right mental motions in his readers:

With a bit of practice, you can learn to identify ways in which the achievement of more or less any fix

...
Welcome to Columbus SSC Meetup [Edit With Your Details]
by Mouth — 2019-10-10T02:54:07.553Z

(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?
Examples of Categories
by countedblessings — 2019-10-10T01:25:32.374Z

Before we go through any more conceptual talk, let's explore some examples of categories to get a better feel of what they are.

Categories do two things:

1) They function as mathematical structures that capture our intuition about how models of cause-and-effect (composition) work in general.

2) They generalize other mathematical structures that capture our intuition about how specific models work.

Obviously, 1 and 2 are related. We model particular pieces of reality with particular mathematical structures (e.g., we model shapes with geometry), so generalizing how we model the world and generalizing fields of mathematics are highly related tasks.

Because I'm assuming my audience isn't familiar with any mathematical structures, we can't just start tossing out examples. Essentially the art of "categorifying" a mathematical structure is as simple as identifying what are the objects and what are the associatively composable morphisms. See here for a list of examples (scroll down to the table), which ought to give you an idea that many different kinds of mathematics really are just examples of categories on some level.

To give just one example of a mathematical structure generalized by category theory, you might be relatively familiar with the category known as Set, the category whose objects are sets and whose morphisms are functions—functions being very nice maps between sets. Functions compose, as we've already seen, and you can check that this composition is associative, so, voila, we've "categorified" a mathematical structure.

Set as category:

Objects

: sets

Morphisms

: functions

Identity morphism

: identity function f(x)=x

Rule of composition

: function composition, e.g., 2x2

Associativity

: 2(x2)=(2×1)x2

Since Set is pretty important, we'll discuss it in a separate post to make sure we're all on the same page about sets and functions. But hopefully this gives you an idea of what it looks like to take a "math thing" and make it into a category.

***

Even if you're not a math expert, you probably know that 2 is bigger than 1. That's all the level of expertise required to understand a very important type of a category called a poset, which is category-speak for "partially ordered set." A partially ordered set is a set with an order than is at least partial.

A poset is any category for which there is at most one morphism between any two objects. I.e., if you have A→B in a categor...
Long Term Future Fund application is closing this Friday (October 11th)
by habryka — 2019-10-10T00:44:28.241Z
Link: https://docs.google.com/forms/d/e/1FAIpQLSdtAM4WcsR6ul1kwxOEPeM2MoPyISC9zab5wreJr9Q09A8H-A/viewform?usp=sf_link

Just a reminder that the Long Term Future Fund application is closing in two days. In past rounds we received 80% of our applications the day of the deadline, but I am not sure whether that is contingent on us reminding everyone that the application is closing soon, so I will continue creating these reminder posts for now.

As a reminder, here is an excerpt from the application form of what kinds of grants we are looking for:

We are particularly interested in small teams and individuals that are trying to get projects off the ground, or that need less money than existing grant-making institutions are likely to give out (i.e. less than ~$100k, but more than $10k). Here are a few examples of project types that we're open to funding an individual or group for (note that this list is not exhaustive):
+ To spend a few months (perhaps during the summer) to research an open problem in AI alignment or AI strategy and produce a few blog posts or videos on their ideas
+ To spend a few months building a web app with the potential to solve an operations bottleneck at x-risk organisations
+ To spend a few months up-skilling in a field to prepare for future work (e.g. microeconomics, functional programming, etc).
+ To spend a year testing an idea that has the potential to be built into an org.
We are also interested in applications for larger projects, or potential future long-term organizations that require more than $100k of funding.
You can find more details on the kind of project we are likely to fund on the fund page (in particular I recommend reading our past recommendation writeups): https://app.effectivealtruism.org/funds/far-future
Minimization of prediction error as a foundation for human values in AI alignment
by Gordon Seidoh Worley — 2019-10-09T18:23:41.632Z

I've mentioned in posts twice (and previously in several comments) that I'm excited about predictive coding, specifically the idea that the human brain either is or can be modeled as a hierarchical system of (negative feedback) control systems that try to minimize error in predicting their inputs with some strong (possibly un-updatable) prediction set points (priors). I'm excited because I believe this approach better describes a wide range of human behavior, including subjective mental experiences, than any other theory of how the mind works, it's compatible with many other theories of brain and mind, and it may give us an adequate way to ground human values precisely enough to be useful in AI alignment.

A predictive coding theory of human values

My general theory of how to ground human values in minimization of prediction error is simple and straightforward:

Neurons form hierarchical control systems.

cf. a grounding of phenomenological idealism using control systems, and its implications
cf. the hierarchy is recursive and reasserts itself at higher levels of organization

Those control systems aim to minimize prediction error via negative feedback (homeostatic) loops.
The positive signal of the control system occurs when prediction error is minimized; the negative signal of the control system occurs when prediction error is maximized.

There is also a neutral signal when there is insufficient information to activate the positive or negative signal "circuitry".
cf. feeling/sensation is when the mind makes a determination about sense data, and sensations are positive, negative, or neutral

"Good", "bad", and "neutral" are then terms given to describe the experience of these positive, negative, and neutral control signals, respectively, as they move up the hierarchy.

I've thought about this for a while so I have a fairly robust sense in my mind of how this works that allows me to verify it against a wide variety of situations, but I doubt I've conveyed that to you already. I think it will help if I give some examples of what this theory predicts happens in various situations that accounts for the behavior people observe and report in themselves and others.

Mixed emotions/feelings are the result of a literal mix of different control systems under the same hierarchy receiving positive and negative signals as a result of producing less or more prediction error.
Hard-to-predict

...
Expected Value- Millionaires Math
by Matt Goldenberg — 2019-10-09T14:50:26.732Z
Link: https://foreverjobless.com/ev-millionaires-math/

I credit reading this post years ago as the first step towards making me instinctively THINK in terms of expected value when considering opportunities. I consider it to be among the best "Why" resources for thinking in expected value, and wish it was more known among the LW crowd.
On Collusion - Vitalik Buterin
by Matt Goldenberg — 2019-10-09T14:45:20.924Z
Link: https://hackernoon.com/on-collusion-fk1xr3png

...if there is a situation with some fixed pool of resources and some currently established mechanism for distributing those resources, and it’s unavoidably possible for 51% of the participants can conspire to seize control of the resources, no matter what the current configuration is there is always some conspiracy that can emerge that would be profitable for the participants.

...This fact, the instability of majority games under cooperative game theory, is arguably highly underrated as a simplified general mathematical model of why there may well be no “end of history” in politics and no system that proves fully satisfactory; I personally believe it’s much more useful than the more famous Arrow’s theorem, for example.

I've found this post quite useful in thinking about mechanism design and problems of designing stable systems.
Regularly Scheduled: Day-of Reminders
by jefftk — 2019-10-09T11:00:01.830Z

Two years ago I wrote

Regularly Scheduled, a
tool to make it easier for people to handle repeated events:

I mostly use it for a recurring dinner we host with some friends from
college. It works well, and has been running with basically no
maintenance. After twice now forgetting I was hosting dinner in the
few days between RSVPing "yes" and people showing up at my house,
however, I realized it needed to be sending reminder emails day-of. I
added
these today, and they look like:

They only go to people who RSVP'd yes; they're a reminder to come not
a reminder to RSVP.

If you have an event you'd like to set up with it, feel free! Let me
know if you run into any issues and I'll try to get the code back into
my head.