trentmkelly/LessWrong-43k huggingface dataset:
Depositions and Rationality
by Pablo Repetto — 2021-11-04T00:10:21.908Z

Reading this guide on deposition strategy I was impressed by how many of the techniques lawyers use on uncooperative witnesses seem like good rationality techniques (a deposition is a sworn oral testimony taken out of court without a supervising judge).

Searching LessWrong, nobody seems to have noticed the parallel. Searching the CFAR participant handbook, a number of these techniques are fitting and novel.

Applicability

These techniques are designed to pull out answers from uncooperative witnesses that are legally compelled to answer truthfully. Uncooperative witnesses are often coached by a defense team in avoidance techniques.

Avoiding difficult or unpleasant questions is a common self-defeating impulse. This is true both individually, and in social interactions. Hesitation is always easy, rarely useful. Legal repercussions are normally absent, so social and group truth-seeking are not fully identical to a deposition, but the formal commitment to finding a truthful answer may be a sufficient common factor.

Summary of techniques

Technique zero is to recognize that it is likely that you will face an evasive witness, and commit explicitly to generate a written plan to deal with them.

"Marshal the facts and standards that you can use to build toward your ultimate question". Before requesting a conclusion ("did the motor carrier you represent violate Federal Motor Carrier Safety Regulations?") request individual facts that build up to your conclusion ("does FMCSR apply to your company?", "does FMCSR requires that your company ensure compiance by drivers?", "do you provide training and testing for your drivers on the contents of the FMCSR?", "does FMCSR requires that drivers keep accurate logs of their trips?", etc).

Exhaustion. Make the witness commit to their answer by asking "what else?", "is that all?", "is there any material you need to fully answer the question?".

Avoiding rabbit trails. The correct response is to let go or write down the tempting line of questioning and proceed with exhaustion.

Example: "Q. Give me all the reasons you believe Dr. Smith conformed to the standard of care. A. He identified the median nerve at the time of the surgery which was abnormally small and congenitally demyelinated, he protected the median nerve with [...]."

Incorrect response: "Q. What do you mean abnormally small?"

Correct response: "Q. Is there any other reason y

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If I have a strong preference for remote work, should I focus my career on AI or on blockchain?
by Malleable_shape — 2021-11-03T23:03:37.217Z

Hello LessWrong crew,

I am familiar with the ideas of Effective Altruism as I have read the 80,000 Hours career guide. I think it is a great guide and it definitely put a new perspective on the way I view my career.

A bit of my background:

I have a master's degree in computer science. I am currently working remotely as a machine learning engineer.

Here is a list of the things that I am looking for in my career, ordered from most important to least important:

Remote work
High salary
Impact

Maybe I'm not the paragon of Effective Altruism values, but if I'm being honest, I value remote work and high salary more than impact. Impact has the 3rd place, but it is still a factor.

Now onto my question:

A few years ago I read Superintelligence and got scared that AGI might make humanity go extinct. I then started focusing on machine learning and after graduating I ended up as a machine learning engineer, where I'm working currently.

Recently, however, I began questioning whether what I was doing is the right thing to do impact-wise. I believe blockchain to be a great technology as well (even though we are in a bubble right now). Fundamentally, I think blockchain is going to bring "power to the people" and I think that's great. It's got it weaknesses now, sure, but over time I think they'll get ironed out.

Here are my top three reasons why I think I should switch to blockchain:

Given my strong remote work preferences, I don't think I will make any impact in anything AI safety related. I think that the main discoveries are being made in companies such as OpenAI and DeepMind and they all require going to the office. Since I don't want to go to the office (my remote work preference is higher than my impact preference), I don't think I will be a part of a team that reaches a fundamental breakthrough. With blockchain, on the other hand, most jobs are remote and I could therefore contribute more.
I am not 100% convinced that AI safety is an existential risk. There are some indications toward this (such as this one), but I think that it may very well be that worrying about AGI safety (as in it's an existential risk for all humans) is the same as worrying that aliens will come and destroy Earth or something similar. I am not denying the problems with current AI systems, but what I am saying is that I don't see a clear path to AGI and I think there's a lot of hand waving that goe

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The Opt-Out Clause
by Raymond Douglas — 2021-11-03T22:02:53.680Z

(cross-posted from my blog)

Let me propose a thought experiment with three conditions.

First, you're in a simulation, and a really good one at that. Before you went in, the simulators extracted and stored all of your memories, and they went to great lengths to make sure that the simulation is completely faultless.

Second, you can leave any time you like. All you have to do to end the simulation, regain your memories, and return to reality is recite the opt-out passphrase: "I no longer consent to being in a simulation". Unfortunately, you don't know about the opt-out condition: that would kind of ruin the immersion.

Third, although you're never told directly about the opt-out condition, you do get told about indirectly, phrased as a kind of hypothetical thought experiment. Maybe someone poses it to you at a party, maybe you read it on twitter, maybe it's a blog post on some niche internet forum. You're guaranteed to hear about it at least once though, to give you a fair chance of leaving. But it's vague and indirect enough that you can dismiss it if you want, and probably forget about it in a week.

It's not enough to think the opt-out phrase, you have to actually say it or write it. So the question is, hypothetically, would you?
Apply to the ML for Alignment Bootcamp (MLAB) in Berkeley [Jan 3 - Jan 22]
by habryka — 2021-11-03T18:22:58.879Z

We (Redwood Research and Lightcone Infrastructure) are organizing a bootcamp to bring people interested in AI Alignment up-to-speed with the state of modern ML engineering. We expect to invite about 20 technically talented effective altruists for three weeks of intense learning to Berkeley, taught by engineers working at AI Alignment organizations. The curriculum is designed by Buck Shlegeris (Redwood) and Ned Ruggeri (App Academy Co-founder). We will cover all expenses.

We aim to have a mixture of students, young professionals, and people who already have a professional track record in AI Alignment or EA, but want to brush up on their Machine Learning skills.

Dates are Jan 3 2022 - Jan 22 2022. Application deadline is November 15th. We will make application decisions on a rolling basis, but will aim to get back to everyone by November 22nd.

Apply here

AI-Generated image (VQGAN+CLIP) for prompt: "Machine Learning Engineering by Alex Hillkurtz", "aquarelle", "Tools", "Graphic Cards", "trending on artstation", "green on white color palette"

The curriculum is still in flux, but this list might give you a sense of the kinds of things we expect to cover (it’s fine if you don’t know all these terms):

Week 1: PyTorch — learn the primitives of one of the most popular ML frameworks, use them to reimplement common neural net architecture primitives, optimization algorithms, and data parallelism
Week 2: Implementing transformers — reconstruct GPT2, BERT from scratch, play around with the sub-components and associated algorithms (eg nucleus sampling) to better understand them
Week 3: Training transformers — set up a scalable training environment for running experiments, train transformers on various downstream tasks, implement diagnostics, analyze your experiments
(Optional) Week 4: Capstone projects

We’re aware that people start school/other commitments at various points in January, and so are flexible about you attending whatever prefix of the bootcamp works for you.

Logistics

The bootcamp takes place at Constellation, a shared office space in Berkeley for people working on long-termist projects. People from the following organizations often work from the space: MIRI, Redwood Research, Open Philanthropy, Lightcone Infrastructure, Paul Christiano’s Alignment Research Center and more.

As a participant, you’d attend communal lunches and events at Constellation...
Paths Forward: Scaling the Sharing of Information and Solutions
by Zvi — 2021-11-02T23:50:01.283Z

Follow-up to: An Unexpected Victory: Container Stacking in the Port of Long Beach

My chronicle of how Ryan managed to change the container stacking rule in the Port of Long Beach quickly became the most viewed post I’ve ever had. A lot of people were excited to spread the word about this story. This makes one think about the stretch goal, where we get to do things like this more often, potentially even creating this virtuous cycle:

Identify a concrete problem.
Explain the gears behind the problem.
Present a solution to the problem, and explain how it would work.
People notice this, and amplify the signal.
Signal causes people with ability to implement solutions to notice.
Solution is implemented.
Victory.
Except, you know, with planning and strategy involved.
Every time this happens, it becomes more normal to do it again, and it becomes easier to get good solutions amplified and implemented.
We get to thinking we can solve problems, and change things for the better…

Including when the solutions are less and less trivial
Including they require non-zero downsides or non-zero amounts of time
It becomes standard to solve problems and blameworthy to not solve them.

Setting aside for now how much the rule change mattered. For this to be exciting, it must be an asymmetric weapon. Does this work for positive-sum solutions to problems without working, or working less well, for zero-sum resource grabs?

My instinct was clearly yes, this only worked because it was obviously correct. If it had not been obviously correct, the effort fails, for overdetermined reasons. This isn’t obvious to others, and a lot of this post explores the gears involved.

Asymmetric Attention Weapons

I was highly frustrated to see this reaction, which I instinctively (if unfairly) translated as ‘actually, attempting to communicate information that might cause people to do things is bad, because the reference class is zero-sum games that compete for attention’:

It’s important to intuition pump why this is the opposite of most of the attention economy, and why such strategies are asymmetric. The information and solution both being true and important was central to the Tweetstorm’s success.

From my previous post‘s ‘I see what you did there’ list.

Starts with a relatable physical story of a boat ride, and a friendly tone.
Tells a (mostly manufactured) story that implies (without sa

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What's the difference between newer Atari-playing AI and the older Deepmind one (from 2014)?
by Raemon — 2021-11-02T23:36:26.389Z

My impression was that thing that put Deepmind on the map was an AI that could play multiple Atari games. Lately there's been new Atari-playing AI (both from Deepmind and other companies) that are making the news. Are they doing basically the same thing 2014 Deepmind was doing but better? Are they doing a fundamentally different thing? Can someone explain the diff like I'm five?
Transcript: "You Should Read HPMOR"
by TurnTrout — 2021-11-02T18:20:53.161Z

The following is the script of a talk I gave for some current computer science students at my alma mater, Grinnell College. This talk answers "What do I wish I had known while at Grinnell?".

Hi, I'm Alex Turner. I’m honored to be here under Sam’s invitation. I'm in the class of 2016. I miss Grinnell, but I miss my friends more—enjoy the time you have left together.

I’m going to give you the advice I would have given Alex2012. For some of you, this advice won’t resonate, and I think that’s OK. People are complicated, and I don’t even know most of you. I don’t pretend to have a magic tip that will benefit everyone here. But if I can make a big difference for one or two of you, I’ll be happy.

I’m going to state my advice now. It’s going to sound silly.

You should read a Harry Potter fanfiction called

Harry Potter and the Methods of Rationality

(HPMOR).

I’m serious. The intended benefits can be gained in other ways, but HPMOR is the best way I know of. Let me explain.

When I was younger, I was operating under some kind of haze, a veil, distancing me from what I really would care about.

I responded to social customs and pressure, instead of figuring out what is good and right by my own lights, how to make that happen, and then executing. Usually it’s fine to just follow social expectations. But there are key moments in life where it’s important to reason on your own.

At Grinnell, I exemplified a lot of values I now look down on. I was extremely motivated to do foolish or irrelevant things. I fought bravely for worthless side pursuits. I don’t even like driving, but I thought I wanted a fancy car. I was trapped in my own delusions because I wasn’t thinking properly.

Why did this happen, and what do I think has changed?

On Caring

First, I was disconnected from what I would have really cared about upon honest, unflinching reflection. I thought I wanted Impressive Material Things. I thought I wanted a Respectable Life. I didn’t care about the bible, but I brought it with me to my dorm anyways so that I’d be more “wholesome” according to my cultural background. Chasing something someone convinced me to believe I wanted, but which I don’t care about.

I became motivated to unironically reflect on what is good, how I want the universe to look by the time I’m done with it—to reason about what matters without asking for permission. Not s...
Why we need prosocial agents
by Akbir Khan — 2021-11-02T15:19:57.424Z

Context: I recently submitted an application to the Open Philanthropy AI Fellowship, and ended up thinking a lot about why studying Multi-Agent Interactions is important.
To build machine-learning systems (agents) that are useful in the real world, they need to be able to cooperate with each other and with humans, not only at deployment but throughout their lifetime. I predicate my research on this and the following beliefs:

Multi-agent deployment: Transformative AI is unlikely to appear in isolation, but will instead be developed by multiple competing actors, giving rise to a large population of capable agents [1, 2].

Multi-agent training: Transformative AI is likely to be produced by an automatic curriculum, and one promising approach for this is multi-agent curricula [3].

Lifetime learning: Agents are not only trained then deployed in the real-world, but are continually trained afterwards. This training will likely be decentralised and within a population of competing agents, as such, the boundary between training and deployment will become less clear.

This creates the following concerns:

It is difficult to deploy cooperative agents: Apriori, agents that are cooperative or altruistic are vulnerable to being exploited by more selfish agents. Thus, agents successful in competitive markets are likely to be selfishly motivated. Large populations of selfish agents easily lead to catastrophic events, for example large market failures [4] or resource exhaustion [5].

It is difficult (post-deployment) to train cooperative agents: Agents that are trained in a population of selfish agents will be unable to develop cooperative strategies [6]. This restricts our ability to create cooperative agents over time, thus making selfish (misaligned) AI more likely.

It is difficult to de-risk multi-agent systems: Transformative AI trained by multi-agent interactions are not only shaped by their reward function but the interactions with other agents in their population [7]. System failure cannot be attributed to a single-agent, thus work on (single agent) interpretability or reward modelling is likely insufficient to de-risk these interactions [8].

To address the risk from these concerns, we need to:

Develop prosocial agents: Altruistic agents do not survive in competitive markets whilst the behaviour of selfish agents leads to cooperation failure [9]. Thus we require prosocial age...
Forecasting Newsletter: October 2021.
by NunoSempere — 2021-11-02T14:07:23.771Z

Highlights

Polymarket is being investigated by the CFTC
Metaculus solves long-lasting UX problem: it now allows more expressive distributions.
David Friedman looks at the track record of IPCC predictions

Index

Prediction Markets & Forecasting Platforms
Job Board
In the News
Blog Posts
Long Content

You can sign up for this newsletter on substack, or browse past newsletters here. If you have a content suggestion or want to reach out, you can leave a comment or find me on Twitter.

Prediction Markets & Forecasting Platforms

Polymarket

Polymarket is being investigated by the US Commodity Futures Trading Commission (a). Back in 2008, several Nobel Prize winners and other academics called on US agencies to clarify and establish regulations on prediction markets (a). So at this point, I feel it's on the US Securities Exchange Commission and the Commodity Futures Trading Commission to have regulated this sooner, not on Polymarket not to have acted somewhat unilaterally.

Otherwise, Polymarket has continued to make more incremental usability improvements which make it more convenient for users to trade, add and withdraw funds from the site.

Metaculus

"nobody freak out but now you can asymmetrically adjust the tails of your logistic curves on continuous input questions on Metaculus" — @casens

SimonM (a) kindly curated the top comments from Metaculus this past August (a). They are:
SimonM (a) calculates a market-implied probability of US default
TeeJayKay (a) gets deep into analysing Spotify's top songs
Matthew_Barnett (a) bets Robin Hanson that AGI will arrive before ems (and shares his logic)
PeterWildeford (a) goes long on Trump
SimonM (a) shares the historic General Social Survey data on sexlessness in young people
NunoSempere (a) lays out his logic for the rate of new donors appearing in the EA space
Metaculus held a panel discussion on its collaboration with the Virginia Health Department (a):

Since March 2020, Metaculus has provided forecasting and modeling resources to public health professionals as they've made crucial decisions in tracking and combating COVID-19. These efforts include the ongoing Keep Virginia Safe and the recently concluded Virginia Lightning Round forecasting tournaments, which were developed in partnership with the Virginia Department of Health and the University of Virginia Biocomplexity Institute, and were designed to enhance COVID-19 modeling efforts whil

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Welcome to Oxford Rationalish
by Sam F. Brown — 2021-11-02T14:06:32.262Z

Oxford Rationalish is a social group for people interested in things like cognitive biases (ways we might be wrong about what we know or how we think), critical thought (how we might become "less wrong" about the world), and good-faith debate (hoping to discover truth, rather than just win an argument).
It's associated with websites like Less Wrong and SlateStarCodex/AstralCodexTen, and to the Effective Altruism movement, but isn't really tied to any one thing.
We go to the pub roughly once a month, and chat about things like AI, decision theory, ethics, prediction, ...
We also do "applied rationality" events, like Circling and Double Crux workshops. Suggestions always welcome!
If you’re reading this, you’re invited!
Vaccine Requirements, Age, and Fairness
by jefftk — 2021-11-02T12:10:07.790Z

In talking about

potentially

resuming contra dancing,
with a vaccination requirement, one reaction I've received from
several people is that it's not fair to start until everyone can get
vaccinated. The idea is that since some people are younger than the
current limit, or have children who are younger, it would not be
appropriately inclusive to resume.

I do really like that contra dancing is so open. I started dancing at
NEFFA when I was very little, and
have brought my kids with me to all sorts of dances. They've danced
at family dances and in a
carrier at regular dances, and come with me when organizing local
dances, playing dance
weekends, and on tour.
Including children in our community is very important to me.

On the other hand, if this means we can't hold dances until all ages
can get vaccinated, we're going to be waiting a long time. While we
are now frustratingly close to allowing vaccination for kids 5-11 (FDA
approved last
week, CDC is meeting today),
the 2-4 cohort is not expected until 2022 at the earliest, with
younger children even later. Which means for the next few months at
minimum, if we are going to require vaccination (no one has been
pushing for allowing unvaccinated children), the choice is between a
dance for adults and older children, or no dance.

The feedback from both the spontaneous
Porchfest dance and the outdoor contra was
really positive: this is something a lot of people have really been
missing. While I would much prefer it if all ages could safely be
included, given a choice between (a) dances for ~98% of regular
participants now and everyone later and (b) nothing now, everyone
later, I think we should go with (a).

(Asking other parents (n=5), I haven't found anyone who thinks dances
need to hold off for age fairness reasons; I've only heard this from
non-parents (n=4). I then asked Lily (7y) and Anna (5y) what they
thought, and they both said that until everyone could get vaccinated
it wasn't fair to resume, even if that takes a very long time. I
asked what they would think if they could get vaccinated but Nora (4m)
still couldn't, and Anna said yes while Lily said she couldn't
decide.)

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