trentmkelly/LessWrong-43k huggingface dataset:
Goal-directedness is behavioral, not structural
by adamShimi — 2020-06-08T23:05:30.422Z

Goal-directedness is the term used by the AI Safety community to point to a specific property: following a goal. It comes from Rohin Shah's post in his sequence, but the intuition pervades many safety issues and current AI approaches. Yet it lacks a formal definition, or even a decomposition into more or less formal subcomponents.

Which questions we want to answer about goal-directed systems underlies the sort of definition we're looking for. There are two main questions that Rohin asks in his posts:

Are non goal-directed systems or less goal-directed ones inherently safer than fully goal-directed ones?
Can non-goal-directed systems or less goal-directed ones be competitive with fully goal-directed ones?

Answering these will also answer the really important meta-question: should we put resources into non-goal-directed approaches to AGI?

Notice that both questions above are about predicting properties of the system based on its goal-directedness. These properties we care about depend only on the behavior of the system, not on its internal structure. It thus makes sense to consider that goal-directedness should also depend only on the behavior of the system. For if it didn't, then two systems with the same properties (safety, competitiveness) would have different goal-directedness, breaking the pattern of prediction.

Actually, this assumes that our predictor is injective: it sends different "levels" of goal-directedness to different values of the properties. I agree with this intuition, given how much performance and safety issues seem to vary according to goal-directedness. But I wanted to make it explicit.

Reiterating the point of the post: goal-directedness is a property of behavior, not internal structure. By this I mean that given the complete behavior of a system over all environment, goal-directedness is independent of what's inside the system. Or equivalently, if two systems always behave in the same way, their goal-directedness is the same, regardless of if one contains a big lookup table and the other an homonculus.

This is not particularly original: Dennett's intentional stance pretty much says the same thing. (The Intentional Stance, p 15)

Then I will argue that any object -- or as I shall say, any system -- whose behavior is well predicted by this strategy [considering it as moving towards a goal] is in the fullest sense

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What does “torture vs. dust specks” imply for insect suffering?
by Tejas Subramaniam — 2020-06-08T20:37:43.411Z

There is a non-negligible probability that insects suffer. Many insects have nociception. Furthermore, the argument-by-analogy approach to determining whether an animal suffer works—an insect’s response to stimuli that would cause pain in other animals is similar. It is estimated that there are 10^19 insects living at any point in time. If one believes that dust specks on a sufficiently large number of people (this doesn’t have to be 3^^^3 after all) is worse than torture of one person, does that mean insect suffering should swamp many other considerations when prioritizing social problems to address? (This is not meant to be a “proves-too-much” argument against siding with dust specks; it’s a genuine question.)
GAN Discriminators Don't Generalize?
by tryactions — 2020-06-08T20:36:08.069Z

Disclaimer: I just started reading about GANs, so am almost certainly missing some context here.

Something that surprised me from the BigGAN paper:

We also observe that D’s loss approaches zero during training, but undergoes a sharp upward jump at collapse (Appendix F). One possible explanation for this behavior is that D is overfitting to the training set, memorizing training examples rather than learning some meaningful boundary between real and generated images. As a simple test for D’s memorization (related to Gulrajani et al. (2017)), we evaluate uncollapsed discriminators on the ImageNet training and validation sets, and measure what percentage of samples are classified as real or generated. While the training accuracy is consistently above 98%, the validation accuracy falls in the range of 50-55%, no better than random guessing (regardless of regularization strategy). This confirms that D is indeed memorizing the training set; we deem this in line with D’s role, which is not explicitly to generalize, but to distill the training data and provide a useful learning signal for G.

I'm not sure how to interpret this. The validation accuracy being close to 50% seems strange -- if the discriminator has 'memorized' the training set and has only seen training set vs generated images, why would it not guess close to 0% on things in the test set? Presumably they are both 1. not-memorized and 2. not optimized to fool the discriminator like generated images are. Maybe the post title is misleading, and we should think of this as "discriminators generalize surprisingly well despite also 'memorizing' the training data." (EDIT: See comment thread here for clarification)

Note that the discriminator has far fewer parameters than there are bytes to memorize, so it necessarily is performing some sort of (lossy) compression to do well on the training set. Could we think of the generator as succeeding by exploiting patterns in the discriminator's compression, which the discriminator then works to obfuscate? I would expect more obfuscation to put additional demands on the discriminator's capacity. Maybe good generator task performance then comes from defeating simpler compression schemes, and it so happens that simple compression schemes are exactly what our visual system and GAN metrics are measuring.

Does this indicate that datasets are still just too small? Later in

...
The "hard" problem of consciousness is the least interesting problem of consciousness
by Hazard — 2020-06-08T19:00:57.962Z

Cross-posted from my roam-blog. Nothing new to anyone who's read about these ideas, meant to be a reference for how I think about things.

If you come up with what you think is a decent and useful theory/partial-theory of consciousness, you will be visited by a spooky daemon who will laugh and inform you that you merely dabble in the "easy problem of consciousness" and have gotten nowhere near "The Hard Problem of ConsciousnessTM"

(the aforementioned daemon in his penultimate form: Mr. Bean undercover at a rock concert)

Chalmers put the hard problem like this:

What makes the hard problem hard and almost unique is that it goes beyond problems about the performance of functions. To see this, note that even when we have explained the performance of all the cognitive and behavioral functions in the vicinity of experience—perceptual discrimination, categorization, internal access, verbal report—there may still remain a further unanswered question: Why is the performance of these functions accompanied by experience? A simple explanation of the functions leaves this question open

The idea goes that even if you explained how the brain does everything it does, you haven't explained why this doing is accompanied by subjective experience. It's rooted in this idea that subjective experience is somehow completely isolated from, and separate to behavior.

This supposed isolation is already a little suspicious to me. As Scott Aaronson points out in Why Philosophers Should Care About Complexity Theory, people judge each other to be conscious and capable of subjective experience after very short interactions. From a very short interaction with my desk I've concluded it doesn't have subjective experience. After a few years of interacting with my dog, I'm still on the fence on if it has subjective experience.

So when I hear a claim that "subjective experience" and "qualia" are divorced from any and all behavior or functionality in the mind, I'm left with a sense that Chalmers is talking about something very different from my subjective experience, and what it seems like to be me. My subjective experience seems deeply integrated with my behavior and functioning.

Colors of Experience

To explore this more, let's briefly look at a classic puzzler:

What if everyone say different colors? What if when we looked at the sky, and the ocean, we both used the English word "Blue", but you experienced

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COVID-19: The Illusion of Stability
by PeterMcCluskey — 2020-06-08T18:46:54.259Z
Link: http://www.bayesianinvestor.com/blog/index.php/2020/06/07/covid-19-the-illusion-of-stability/

New infections have been declining at an almost adequate pace (10% per
week?) in most parts of the US, and probably the rest of the developed
world.

The overall reported new cases look more discouraging, for two reasons.

One reason is the increase in testing. I estimate that two months ago, a
bit less than 10% of new infections were being confirmed by tests, and I
estimate that now it's above 20%, maybe getting close to 25%. That means
that if the new infection rate were unchanged, we'd be seeing a roughly
10% per week increase in reported cases.

Nearly all parts of the country have done a good deal better than that.

I estimate the change in new infections since the early April peak by
multiplying the early April confirmed daily cases by 10 or 12, and the
June ones by 4 or 5, and I get a current rate that's about 1/4 to 1/3 of
the peak.

The bad news is that there are some heavily populated areas for which
the trend doesn't look very good over the past few weeks. When the rate
of new infections remains constant in some areas, but declines at
exponential rates in others, the exponential declines stop affecting the
total numbers before too long. E.g. much of California has suppressed
the pandemic, but a few cities, such as Los Angeles and Oakland, are
enough to keep the state's total count of new infections steady.

I'll base this analysis mostly on Alameda county, where I live. It looks
like new infections are coming heavily from low-income workers whose
jobs require them to meet many people. They presumably get infected on
the job, and also spread it within crowded homes.

I presume a nontrivial number of new cases are being reported from
nursing homes. That might just be because authorities have finally
gotten around to massive testing of nursing homes. I presume that if the
spread in nursing homes has not already been reduced, then the new
reports will trigger some action to fix the problems there. But there
are no videos of, say, Gov.
Cuomo
directly infecting nursing home residents, and maybe it's hard for the
US to do much about deaths that don't generate distinctive videos, so I
still have some mild worries here.

I did a cursory check for other problem areas. Elevators? Two nearby
cities, Emeryville and Albany, stand out as having a much larger
fraction of high-rise apartment buildings. If elevators were an
important source of infections, they'd have more cases th

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We've built Connected Papers - a visual tool for researchers to find and explore academic papers
by discordy — 2020-06-08T18:44:56.467Z

Hi LessWrong. I'm a long time lurker and finally have something that I'm really proud to share with you.

After a long beta, we are releasing

Connected Papers

to the public!

Connected papers is a unique, visual tool to help researchers and applied scientists find and explore papers relevant to their field of work.

First - let's look at a couple of examples graphs for work that is representative of this community:

Nick Bostrom:

https://www.connectedpapers.com/main/7bba95b3d145564025e26b49ca67f13f884f8560/Superintelligence-Paths-Dangers-Strategies/graph

Eliezer Yudkowsky, Nate Soares:

https://www.connectedpapers.com/main/61c368138b0211323e8773174ac3132122da07ef/Functional-Decision-Theory-A-New-Theory-of-Instrumental-Rationality/graph

Did you find new and interesting papers to read? Would this be helpful as an introduction to the literature of a new field of study?

The problem

Almost every research project in academia or industry involves phases of literature review. Many times we find an interesting paper, and we’d like to:

Find different methods and approaches to the same subject
Track down the state of the art research in the field
Identify seminal works and background reading
Explore and immerse ourselves in the topic and become aware of the trends and dynamics in the literature

Previously, the best ways to do this were to browse reference lists, or hope to find good keywords in textual search engines and databases.

Enter Connected Papers

It started as a side project between friends. We’ve felt the pains of academic literature review and exploration for years and kept thinking about how to solve it.

For the past year we’ve been meeting on weekends and prototyping a tool that would allow a very different type of search process for academic papers. When we saw how much it improved our own research and development workflows — and got increasingly more requests from friends and colleagues to use it — we committed to release it to the public.

You know… for science.

So how does it work?

Connected Papers is not a citation tree. Those have been done before.
In our graph, papers are arranged according to their similarity. That means that even papers that do not directly cite each other can be strongly connected and positioned close to each other in the graph.

To get a bit technical, our similarity is based primarily on the conc...
Legibility: Notes on "Man as a Rationalist Animal"
by Hazard — 2020-06-08T02:18:01.935Z

Cross-posted on my roam-blog. This post is meant to be part of a series that explores the ideas in samzdat's The Uruk Series, and it also serves as a standalone introduction to the idea of legibility.

The first book that Lou rings in is Seeing Like a State by James C. Scott, and with it comes the ideas of Legibility and High Modernism. High Modernism is a movement/aesthetic/frame-of-mind that peaked around the middle of the 1900's (the shadow of which, we still live in), and legibility refers to the more abstract process that High Modernism represents.

Lou is mostly in the game of connecting the dots, and in introducing legibility he skips over a lot of the juicy details that appear in the book. I'd recommend Scott Alexander's book review of Seeing Like a State if you want to recover a lot of the concrete examples that ground out Lou's more abstract points. If you want the shortest possible intro to legibility and High Modernism, check out the ribbonfarm post on it. If all of those sound like too much reading, here's some highlights from all sources.

Here is the recipe:

Look at a complex and confusing reality, such as the social dynamics of an old city
Fail to understand all the subtleties of how the complex reality works
Attribute that failure to the irrationality of what you are looking at, rather than your own limitations
Come up with an idealized blank-slate vision of what that reality ought to look like
Argue that the relative simplicity and platonic orderliness of the vision represents rationality
Use authoritarian power to impose that vision, by demolishing the old reality if necessary
Watch your rational Utopia fail horribly

From Scott Alexander:

The first part of the story is High Modernism, an aesthetic taste masquerading as a scientific philosophy. The High Modernists claimed to be about figuring out the most efficient and high-tech way of doing things, but most of them knew little relevant math or science and were basically just LARPing being rational by placing things in evenly-spaced rectangular grids.

James C. Scott himself describing High Modernism:

A strong, one might even say muscle-bound, version of the self-confidence about scientific and technical progress, the expansion of production, the growing satisfaction of human needs, the mastery of nature (including human nature), and above all, the rational design of social order co

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An Illustrated Proof of the No Free Lunch Theorem
by  — 2020-06-08T01:54:27.695Z
Link: https://mlu.red/muse/52449366310.html

This is a proof of one of the many No Free Lunch Theorems in statistical learning. Rafael Harth already did a very good writeup here of the same proof. I had a vision for doing some very nice diagrams which could help bridge the many summations and inequalities in this proof. I think I maybe only executed up to ~20% of that vision.

I have a good amount of experience making graphics and visuals, and this was still challenging. I think, until I find a better method, that I'll probably not make more of these. I felt a combination of:

difficulty using my tool (Inkscape) to get the "real" result in my head

frustration that the similarities between the images couldn't be abstracted out in some nice tool

For these sorts of graphs, I feel like Mermaid is maybe half-way there. But I feel like there's a lot of value to finding the specific visuals that you as the author think are good to help convey the intuition, so I'm a little hesitant to just use a compositional tool...
Growing Independence
by jefftk — 2020-06-07T20:20:02.805Z

Note: this is based on my experience with my two kids, currently
four and six. It may not generalize as much as I think it does.

People start out dependent on their parents for food, changing,
contact, motion, and even sleep timing. Typically they end up as
adults, no longer dependent on their parents at all. Part of my
approach to parenting has been that I want to let my kids be as
independent as possible, as early as possible. Not only does
it make their lives better, because they can meet their own needs how
they want, but it makes my life easier, because they can handle more
on their own. Sometimes this involves a bit more effort up front, but
I think it's substantially less effort in total.

Examples:

If Lily (6y) comes to
me and says "Anna (4y)
pushed me," my first response will probably be "have you talked to
Anna?" I'll still help some, often by listening to them negotiate and
clarifying rules ("you can't push people, even when they happen to be
between you and your desired toy") but over time they've gotten much
better at this. There's a whole post worth of thoughts that could go
here on what's worked and what hasn't, but at this point they can get
up an hour before we do and (nearly always) resolve their own
conflicts without waking us.

The kids will often ask for help while I'm cooking. If I'm in
the middle of something, which I usually am, I'll say something like
"I can help you as soon as I finish mixing this". During that time
they're often able to solve their own problem. If they do still need
help when I'm ready, they get my full attention. This is acting as a
cost, paying with their time, which filters their requests so I only
get the ones where it's worth it to them. And then while they're
bored waiting for me they'll often try a bit harder at doing up the
snaps on their shirt or whatever, and often that extra focused effort
is what they need to do it on their own.

Similarly, when Anna was learning to ride her trike and she got to a
sidewalk bump that was hard to pedal over, she would call for help. I
found that if I walked far enough behind her she would keep trying
while she waited for me to catch up, and then often didn't need me by
the time I was there.

If I hear crying, I don't automatically do something about it.
As I was writing this post I heard Anna get up. Then I heard some
crying. Not "I've been

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Quarantine Bubbles Require Directness, and Tolerance of Rudeness
by Raemon — 2020-06-07T19:52:51.600Z

Berkeley recently introduced a rule where:

You always wear a mask within 30' of people, except...
You can have a 12-person "Quarantine Social Bubble" of people who interact with each other normally.
You can rotate people in your Social Bubble every three weeks.

I think these are the sensible longterm rules, for people who can coordinate well.

I think most people can't coordinate well, but it was the right decision for Berkeley to make this the rule, because it is actually the obvious Schelling Rule, and people would probably rebel and say "fuck it" if they couldn't do this.

But, I am quite worried about it anyway.

If people get excited about rotating social bubbles, they may screw up and hurt themselves or people they care about. Even if they're smart people who know better.

Twelve people is a lot, and it only takes one roommate or friend who didn't communicate clearly, or took an extra risk without telling everyone, to ruin things for everyone.

I think there are some very important norms about honesty, reliability, and clarity that are very essential to have, if you want to be able to have social-bubbles without risking harm to yourself, your friends and the broader local community.

I don't think we currently have those norms, and they are hard to create from scratch. Creating them will be uncomfortable.

It needs to be common, and acceptable, to ask someone "Hey, have you interacted with any non-social-bubble people without a mask? Even for a little bit? Are you sure? Are you confident that all the other people you interacted with also haven't interacted with people without masks? How do you know? Did you ask them?"

Different people have different risk tolerances, and different beliefs about what actions are risky. But it has to be possible to say:

"Alas. I understand this is hard, and you (or your roommate) are trying your best in a difficult time, but [Action X] means that I won't be interacting with you or the people in your social bubble for another 3 weeks. I still care about you as a friend but it's important for me and my other roommates to stay safe."

I *hope* that people can do all that with compassion. I hope people actually cultivate the skillset of being firm, but empathetic. But, if you don't have the skills of being firm, and willing-to-ask-direct-questions, and empathetic all at once, I'm willing to go on record saying:

If you can't do all three

...