trentmkelly/LessWrong-43k huggingface dataset:
Rapid Antigen Tests for COVID
by Tornus — 2021-10-21T15:26:25.986Z

Update 2022-01-07: It's pretty clear now that antigen tests are less effective against Omicron, probably for three reasons: they are less sensitive to Omicron, viral loads rise faster with Omicron than with Delta, and Omicron is more infectious than Delta.

Based on the current data, I'm changing two things in the original writing, with the caveat that these are just guesses that are not backed up by hard data:

The test validity window goes from 12 hours to 6 hours.

The likelihood of detecting a person who is infectious but asymptomatic goes from 75% to 50%.

Personally, I've started using the throat swab technique: https://www.youtube.com/watch?v=5qHTBlxfNes That technique was likely more effective for detecting Delta, and there are strong theoretical reasons to think it might be much more effective for detecting Omicron.

Introduction

Home antigen tests for COVID are an imperfect but useful tool. In this post I’ll discuss the four scenarios where I think they’re most useful, share a few thoughts about using them correctly, and finish by taking a deep look at the data on accuracy.

If you don’t already understand concepts like sensitivity and positive predictive value, you might want to read this first.

I’ll focus on the Abbott BinaxNOW test because I think it’s overall the best and most available home antigen test in the US as of October 2021 (the situation is different in other countries). Sensitivity varies somewhat between different tests, but they are all roughly comparable and have the same strengths and weaknesses.

Epistemic status

This is a complex topic that is evolving quickly and is only partly understood. My analysis is grounded in hard data but necessarily involves a certain amount of extrapolation.

I have no relevant credentials but this writing has been reviewed by a medical epidemiologist who works full time on COVID.

Application 1: risk reduction

I consider antigen tests to be most useful for reducing the risk of asymptomatic transmission at social events. In that context, I believe a negative BinaxNOW test reduces the probability that you are infectious by about 50% for the 6 hour period immediately after taking the test. (There's no hard data behind the 6 hour cutoff—it's just a reasonable extrapolation based on what we know about viral load during the early stages of infection, and based on early data about Omicron).

When I host social events, ...
Covid 10/21: Rogan vs. Gupta
by Zvi — 2021-10-21T15:10:02.391Z

I finally got my booster shot yesterday. I intended to get it three weeks ago, but there was so much going on continuously that I ended up waiting until I could afford to be knocked out for a day in case that happened, and because it’s always easy to give excuses for not interacting with such systems. When I finally decided to do it I got an appointment literally on my block an hour later for that and my flu shot, and I’d like to be able to report there were no ill effects beyond slightly sore arms, but I’m still kind of out of it, so I’ll be fine but if I made some mistakes this week that’s likely the reason. I also had to wait the fifteen minutes. I would have simply walked out the moment they weren’t looking, but they held my vaccine card hostage until time was up.

We now have full approval for every iteration of booster shots, including mix and match, for those sufficiently vulnerable. If you’re insufficiently vulnerable but would still rather be less vulnerable, there’s a box you’ll need to check.

I got a chance to listen to the Rogan podcast with Gupta, and have an extensive write-up on that. It was still a case of ‘I listen so you hopefully do not have to’ but it was overall a pleasant surprise, and better than most of what passes for discourse these days.

Executive Summary

Conditions continue to improve.
Booster sequences including mix-and-match have been approved.
Rogan did a podcast and I listed to it so you don’t have to.

Let’s run the numbers.

The Numbers

Predictions

Prediction from last week: 481k cases (-12%) and 9,835 deaths (-11%).

Results (from data source unadjusted): 472k cases (-15%) and 11,605 deaths (+1%).

Results (adjusted for Oklahoma which will be baseline for next week): 472k cases (-15%) and 10,705 deaths (-3%).

Prediction for next week: 410k cases (-13%) and 9,600 deaths (-10%).

Wikipedia reported over 1,100 deaths in Oklahoma this week. That’s not plausible, so I presume it was a dump of older deaths or an error of some kind, and removed 900 of them from the total.

There’s no hard and fast rule for when I look for such errors or how I do the fixes, so you can decide if what I’m doing is appropriate. Basically if an entire region gives a surprising answer I’ll look at the individual states for a large discrepancy, which is at least slightly unfair since sometimes it makes the number look ‘normal’ when it shouldn’t...
NATO: Cognitive Warfare Project
by ChristianKl — 2021-10-21T09:57:03.475Z
Link: https://web.archive.org/web/20230220003823/https://www.innovationhub-act.org/cw-documents-0

NATO seems to have a project on cognitive warfare and a few public reports online:

Interim Report

Based on the Understanding Phase findings, NATO has identified the following priorities:
- Develop a Critical Thinking online course
- Develop improvements to the decision making processes

- Leverage technologies, including VR and AI to develop tools in support of better cognition and better decision making

1 Jun 21 Cognition Workshop Report

Cognition includes three interrelated aspects that are reflected in the structure of the workshop: information, decision-making and neuroscience.

Cognitive Warfare

As global conflicts take on increasingly asymmetric and "grey" forms, the ability to manipulate the human mind employing neurocognitive science techniques and tools is constantly and quickly increasing. This complements the more traditional techniques of manipulation through information technology and information warfare, making the human increasingly targeted in the cognitive warfare.
Successful Mentoring on Parenting, Arranged Through LessWrong
by supposedlyfun — 2021-10-21T08:27:57.794Z

Introduction

In June 2021, Zvi posted

The Apprentice Thread

, soliciting people to offer, or request, mentoring or apprenticeship in virtually any area.

Gunnar_Zarncke

offered advice on parenting, as the parent of four boys (incidentally, true of my grandmother as well) between the ages of 9 and 17, with the usual suite of observational skills and knowledge that comes with being a regular on this site. I

responded with interest

as my first child is due in November.

Gunnar and I are sharing our experience as an example of what a successful mentoring process looks like, and because his key points on parenting may be interesting to current and future parents in this community. I had several breakthrough-feeling insights which helped me to connect my LessWrong/rationalist schema to my parenting schema.

Gunnar and I began by exchanging messages about the parameters of what we were getting into. I was interested in his insight based on these messages and other comments and posts he had made on this site about parenting. We arranged a Google Meet video call, which confirmed that our personalities and philosophies were compatible for what we were undertaking.

We did not have a structured reading list, although I investigated resources as Gunnar suggested. As we went along, Gunnar translated into English samples of notes taken by his children’s mother throughout their childhood and shared them with me. She had also systematically described the daily and weekly tasks a parent could expect in various development phases of the child’s life. I was an only child and have not parented before, so I found this extremely educational.

We had several video calls over the next few months and discussed a wide range of parenting-related topics. Gunnar also suggested this post, to report on our experience. I drafted the post, and Gunnar provided comments, which I merged, and after he reviewed the final version, we published it as a joint post.

By call number two, I was realizing that parenting was never going to be the sort of thing where I could read the “correct” book for the upcoming developmental stage, buy the “correct” tools, and thereby maximize outcomes. Instead, it would be a constant process of modeling the child’s mind, providing new inputs, observing behaviors, updating the model as needed, researching helpful tools, and iterating more or less until the kid is in its 20s...
Experimenting with Android Digital Wellbeing
by Yair Halberstadt — 2021-10-21T05:43:41.789Z

inspired by this post

Introduction: Small Deaths

I'm a morning person.

I usually wake up at about 6 AM. I read on my phone in bed until the toddler wakes up at 6:30, at which point I look after him till I take him to daycare at about 7:15. I then have till 9 AM free, during which time I get a lot of stuff done - both chores and personal projects.

I finish work at 6 PM. Either we have dinner with the kid, or I feed him dinner, and then we have dinner once he's in bed at about 7:30.

So by 8:30 PM I've eaten dinner, jobs are all done, and kid's in bed. I might put on the dishwasher, but other than that my evening's free till I start getting ready for bed at about 10:30 PM.

So what do I do in those 2 hours?

Sometimes I read a book. Sometimes I go for a walk.

But most of the time I stare at my phone. I catch up on lesswrong, gitter, emails, twitter, discord, and then once I've done all that I go back again and refresh them all in case something new has turned up.

Once I'm convinced that nothing exciting is going to pop up on my regular haunts I start to think about all the sites that might have fresh content. Maybe Scott Aaronson has posted something on Shtetl Optimized? And didn't I once read a blog by X which I vaguely enjoyed? He's probably posted something in the last year...

Eventually I probably find a sequence or short story I haven't read yet, or some random Wikipedia article - I wonder where the third lowest lake on earth is? What about the highest roads and villages, or northernmost islands?

I couldn't say I enjoy this experience. I'm vaguely bored and unhappy throughout, and I'd probably be happier just going straight to bed. The moment I stop and do something I immediately feel better and invigorated. But stopping is just so difficult!

I view this time as a small death. Time I'm just trying to kill. It doesn't relax me. I don't enjoy it. It has no benefits - it might as well not exist. I might as well be dead for those 2 hours.

How do I break out of it?

Experiment: Digital Wellbeing

I don't want to not be able to use my phone at all after 7 - I'm not brave enough for that.

Ideally I would be able to just turn off chrome after 7, since that removes anything open ended - I can only check apps I have installed on my phone.

Google provides Digital WellBeing controls on modern android phones. Unfortunately it doesn't have the ability to turn off specific apps at specific t...
Emergent modularity and safety
by Richard_Ngo — 2021-10-21T01:54:08.581Z

Biological neural networks (i.e. brains) and artificial neural networks have sufficient commonalities that it's often reasonable to treat our knowledge about one as a good starting point for reasoning about the other. So one way to predict how the field of neural network interpretability will develop is by looking at how neuroscience interprets the workings of human brains. I think there are several interesting things to be learned from this, but the one I'll focus on in this post is the concept of modularity: the fact that different parts of the brain carry out different functions. Neuroscientists have mapped many different skills (such as language use, memory consolidation, and emotional responses) to specific brain regions. Note that this doesn’t always give us much direct insight into how the skills themselves work - but it does make follow-up research into those skills much easier. I’ll argue that, for the purposes of AGI safety, this type of understanding may also directly enable important safety techniques.

What might it look like to identify modules in a machine learning system? Some machine learning systems are composed of multiple networks trained on different objective functions - which I’ll call architectural modularity. But what I’m more interested in is emergent modularity, where a single network develops modularity after training. Emergent modularity requires that the weights of a network give rise to a modular structure, and that those modules correspond to particular functions. We can think about this both in terms of high-level structure (e.g. a large section of a neural network carrying out a broad role, analogous to the visual system in humans) or lower-level structure, involving a smaller module carrying out more specific functions. (Note that this is a weaker definition than the one defended in philosophy by Fodor and others - for instance, the sets of neurons don’t need to contain encapsulated information.)

In theory, the neurons which make up a module might be distributed in a complex way across the entire network with only tenuous links between them. But in practice, we should probably expect that if these modules exist, we will be able to identify them by looking at the structure of connections between artificial neurons, similar to how it’s done for biological neurons. The first criterion is captured in a definition proposed

by

...
[$10k bounty] Read and compile Robin Hanson’s best posts
by Richard_Ngo — 2021-10-20T22:03:47.376Z

I think Robin Hanson's ideas are not read nearly as widely as they should be, in part because it's difficult to navigate his many, many blog posts (I estimate he's written 2000 of them exactly 3302 of them). So I'd like to pay someone to read through all his writings and compile the best ones into a more accessible format. The default output would be an ebook like Rationality: from AI to Zombies, containing several thematically-linked sequences of posts; possible extensions of this include adding summaries or publishing physical copies (although let me know if you have any other suggestions).

I expect this to take 1-2 months of work, and plan to pay around $10k USD (more details to be determined as we get a better idea of the scope of the project). My gmail address is richardcngo; email me with the subject line "Hanson compilation", plus any relevant information about yourself, if you might be interested in doing this.
AGI Safety Fundamentals curriculum and application
by Richard_Ngo — 2021-10-20T21:44:23.584Z
Link: https://docs.google.com/document/d/1mTm_sT2YQx3mRXQD6J2xD2QJG1c3kHyvX8kQc_IQ0ns/edit?usp=sharing

Over the last year EA Cambridge has been designing and running an online program aimed at effectively introducing the field of AGI safety; the most recent cohort included around 150 participants and 25 facilitators from around the world. Dewi Erwan runs the program; I designed the curriculum, the latest version of which appears in the linked document. We expect the program to be most useful to people with technical backgrounds (e.g. maths, CS, or ML), although the curriculum is intended to be accessible for those who aren't familiar with machine learning, and participants will be put in groups with others from similar backgrounds. If you're interested in joining the next version of the course (taking place January - March 2022) apply here to be a participant or here to be a facilitator. Applications are open to anyone and close 15 December. EDIT 10 Dec: Facilitators will be paid $1000; the time commitment is 2-3 hours a week for 8 weeks. We've now also released the curriculum for the governance track.

This post contains an overview of the course and an abbreviated version of the curriculum; the full version (which also contains optional readings, exercises, notes, discussion prompts, and project ideas) can be found here. Comments and feedback are very welcome, either on this post or in the full curriculum document; suggestions of new exercises, prompts or readings would be particularly helpful. I'll continue to make updates until shortly before the next cohort starts.

Course overview

The course consists of 8 weeks of readings, plus a final project. Participants are divided into groups of 4-6 people, matched based on their prior knowledge about ML and safety. Each week (apart from week 0) each group and their discussion facilitator will meet for 1.5 hours to discuss the readings and exercises. Broadly speaking, the first half of the course explores the motivations and arguments underpinning the field of AGI safety, while the second half focuses on proposals for technical solutions. After week 7, participants will have several weeks to work on projects of their choice, to present at the final session.

Each week's curriculum contains:

Key ideas for that week
Core readings
Optional readings
Two exercises (participants should pick one to do each week)
Further notes on the readings
Discussion prompts for the weekly session

Week 0 replaces the small group discussions with a l...
[AN #167]: Concrete ML safety problems and their relevance to x-risk
by Rohin Shah — 2021-10-20T17:10:03.690Z

Alignment Newsletter is a weekly publication with recent content relevant to AI alignment around the world. Find all Alignment Newsletter resources here. In particular, you can look through this spreadsheet of all summaries that have ever been in the newsletter.

Audio version here (may not be up yet).

Please note that, while I work at DeepMind, this newsletter represents my personal views and not those of my employer.

HIGHLIGHTS

Unsolved Problems in ML Safety (Dan Hendrycks, Nicholas Carlini, John Schulman, and Jacob Steinhardt) (summarized by Dan Hendrycks): To make the case for safety to the broader machine learning research community, this paper provides a revised and expanded collection of concrete technical safety research problems, namely:

1. Robustness: Create models that are resilient to adversaries, unusual situations, and Black Swan events.

2. Monitoring: Detect malicious use, monitor predictions, and discover unexpected model functionality.

3. Alignment: Build models that represent and safely optimize hard-to-specify human values.

4. External Safety: Use ML to address risks to how ML systems are handled, including cyberwarfare and global turbulence.

Throughout, the paper attempts to clarify the problems’ motivation and provide concrete project ideas.

Dan Hendrycks' opinion: My coauthors and I wrote this paper with the ML research community as our target audience. Here are some thoughts on this topic:

1. The document includes numerous problems that, if left unsolved, would imply that ML systems are unsafe. We need the effort of thousands of researchers to address all of them. This means that the main safety discussions cannot stay within the confines of the relatively small EA community. I think we should aim to have over one third of the ML research community work on safety problems. We need the broader community to treat AI safety at least as seriously as safety for nuclear power plants.

2. To grow the ML safety research community, we need to suggest problems that can progressively build the community and organically grow support for elevating safety standards within the existing research ecosystem. Research agendas that pertain to AGI exclusively will not scale sufficiently, and such research will simply not get enough market share in time. If we do not get the machine learning community on board with proactively mitigating risks that already exist, ...
Sentience, Sapience, Consciousness & Self-Awareness: Defining Complex Terms
by LukeOnline — 2021-10-20T13:48:40.304Z

The terms in the title are commonly used in crucial debates surrounding morality & AI. Yet, I feel like there is no clear consensus about the meaning of those terms. The words are often used interchangeably, causing people to think they are all the same or very closely related. I believe they're not. Clearly separating these terms makes it a lot easier to conceptualize a larger "spectrum of consciousness".

Disclaimer: I expect some people to be upset for 'taking' terms and changing their definition. Feel free to propose different terms for the concepts below!

Consciousness

"Consciousness" is often taken to mean "what we are". "Our" voice in our heads, the "soul". I propose a more limited definition. A conscious entity is a system with an "internal observer". At this very moment, these words are being read. Hello, 'observer'! You probably have eyes. Focus on something. There is an image in your mind. Take the very core of that: not the intellectual observations connected to it, not the feelings associated with it, just the fact that a mental image exists. I think that is the unique ability of a conscious individual or system.

Sentience

Wikipedia claims that consciousness is sentience. Wiktionary has a definition for sentient that includes human-like awareness and intelligence. Once again, I propose a more limited definition. A sentient entity is a system that can experience feelings, like pleasure and pain. Consciousness is a prerequisite: without internal observer, there is nothing to experience these feelings.

I believe sentience is the bedrock of morality. Standing on a rock probably doesn't generate any observations - certainly not pleasant or unpleasant ones. Standing on a cat seems to produce deeply unpleasant feelings for the cat. Defining morality as a system that tries to generate long-term positive experiences and to reduce negative experiences seems to work pretty well. In that case, standing on cats is not recommended.

In these terms, consciousness is not the threshold of morality. Perhaps we discover that rocks are conscious. When we stand on them, we slightly compress their structure and rocks somehow hold an internal observer that is aware of that. But it doesn't have any feelings associated with that. It doesn't experience pain or joy or fear or love. It literally doesn't care what you do to it. It would be strange, it wou...