trentmkelly/LessWrong-43k huggingface dataset:
Exposure or Contacts?
by jefftk — 2020-08-22T13:00:06.215Z

When I talk to people about the coronavirus, they're often using one
of two models of infection risk:

Minimize exposure: risk is proportional to how risky
your activity is, multiplied by how long you spend doing it. Try to
do less risky things, and do them for less time.

Minimize contacts: risk is proportional to how many
people you get sufficiently close to. Try not to get close to people,
and if you do try to minimize their number.

There are many things that these models agree on: don't go to bars,
wear a mask, move activities outdoors. On the other hand, there are
also many cases where they give very different recommendations.
Consider a family choosing whether to have their child attend (a) two
daycares for 20hr/wk each (b) one daycare for 40hr/wk, and figure the
two daycares are identical. The "minimize exposure" model views (a)
and (b) as essentially equivalent: there's some risk per hour, and in
both cases there's a total of 40hr at that level of risk. The
"minimize contacts" model, however, views (a) as twice as risky as
(b): the child would be in close contact with twice as many people
each week.

If most of the spread were driven by a few highly infectious people,
and you were unlucky enough to get one of them in your daycare class,
then your kid would have a large chance of getting infected after just
a few hours, let alone twenty. In that world, an approach of minimizing
contacts makes sense: option (a) with two daycares gives twice the
chance of encountering a superspreader than option (b) with just one.

On the other hand, if most of the spread is driven by each person
infecting a few other people, or if infectiousness varies very little
and it's behavior that varies widely, then even if you happen to get
an infectious person in your class your kid is probably not going to
get sick, and the increased risk from having two different classes
where your child could encounter a sick person is about equal to the
increased risk from potentially spending twice as long with a sick
person.

It does look like spread is not even; for example Endo et. al. (June
2020) found that "80% of secondary transmissions may have been
caused by a small fraction of infectious individuals (~10%)".
Unfortunately, this does not let us distinguish between the variation
coming from behavior (a small number of people having jobs put them in
co...
Sunday August 23rd, 12pm (PDT) – Double Crux with Buck Shlegeris and Oliver Habryka on Slow vs. Fast AI Takeoff
by Ben Pace — 2020-08-22T06:37:07.173Z

This Sunday at 12pm (PDT), we're running a double crux between two curated LessWrong authors (see here for transcripts of events from previous weeks).

We'll have 1.5–2 hours of Double Crux between Buck and Oliver, facilitated by Eli Tyre. They'll discuss the topic of slow vs. fast AI Takeoff. This will be a conversation guided by attempts to communicate with each other, rather than a prepared presentation focused on communicating a particular argument to the audience.
This will be followed by some Q&A with the attendees, and a hangout in an online space (Gather Town).

If you're a curated author and interested in giving a 5-min talk at a future event, which will then be transcribed and edited, sign up here.

Speakers

Buck's curated posts

"Other people are wrong" vs "I am right"
Six economics misconceptions of mine which I've resolved over the last few years

habryka's curated posts:

Integrity and accountability are core parts of rationality

elityre's curated posts:

Historical mathematicians exhibit a birth order effect too
Does it become easier, or harder, for the world to coordinate around not building AGI as time goes on?
How do you assess the quality / reliability of a scientific study?

Details

When? Sunday August 23, 12pm (PDT)

Where? https://us02web.zoom.us/j/81137654971
"The Holy Grail" of portfolio management
by Alexei — 2020-08-22T04:25:55.199Z

TL;DR: Bayes' Theorem : Rationality :: Uncorrelated returns : Investing

Recently I gave a talk on EMH: https://www.lesswrong.com/posts/3TiEZzw4ikneLGp4J/dissolving-the-is-the-efficient-market-hypothesis-dead

In there I had a bonus slide about what I call the "Efficient Market Frontier" (EMF). May be there's an existing name for it; I couldn't find it. (EMF is not to be confused with the efficient frontier, which is a common term in finance but talks about portfolio optimization.) But before we can talk about it in the upcoming post, I want to set up one very important bit of context regarding portfolio management.

Having uncorrelated return streams in your portfolio drastically lowers the volatility of your portfolio.

Here is Ray Dalio, founder of Bridgewater, one of the largest hedge funds, talking about this: https://www.youtube.com/watch?v=Nu4lHaSh7D4. And here is a screenshot out of his book, Principles:

X-axis is the number of uncorrelated assets in the portfolio, y-axis is the annual portfolio standard deviation which converts into useful metrics like the probability of losing money in a given year. The graph is saying the same thing as above: when you have more uncorrelated assets (or strategies), the volatility of your portfolio will be lower. But if the assets are even somewhat correlated that drastically reduces their effectiveness.

He refers to this concept as The Holy Grail and I agree. This is the most important concept I seared into my core after being immersed in finance for a few years.

What's so good about low portfolio volatility?

Let's say I give you a trading strategy that is very good at making money. You trust me and you trust the strategy. You follow the strategy and buy some sugar beets. The price of sugar beets plummets 90%. How do you feel? Do you hodl and have faith? Or do you reassess your trust in me and the strategy?

Thankfully, the price recovers, and the strategy tells you to sell. You make a cool 10% profit. Is this a good strategy? Well, we can't tell yet because we only had one trade. That's some evidence of strategy's efficacy, but we'll need a lot more trades before we're certain. Okay, but is the trade itself good? Well, yes and no:

1) Yes, the trade made you money in the end.

2) No, the trade could have clearly been better. You should have bought sugar beets after the price fell. (Or shorted them and covered at the bottom for a 90...
Forecasting Thread: AI Timelines
by Amandango — 2020-08-22T02:33:09.431Z

This is a thread for displaying your timeline until human-level AGI.

Every answer to this post should be a forecast. In this case, a forecast showing your AI timeline.

For example, here are Alex Irpan’s AGI timelines.

The green distribution is his prediction from 2015, and the orange distribution is his 2020 update (based on

this post

).

For extra credit, you can:

Say why you believe it (what factors are you tracking?)
Include someone else's distribution who you disagree with, and speculate as to the disagreement

How to make a distribution using Elicit

Go to

this page.

Enter your beliefs in the bins.

Specify an interval using the Min and Max bin, and put the probability you assign to that interval in the probability bin.
For example, if you think there's a 50% probability of AGI before 2050, you can leave Min blank (it will default to the Min of the question range), enter 2050 in the Max bin, and enter 50% in the probability bin.
The minimum of the range is January 1, 2021, and the maximum is January 1, 2100. You can assign probability above January 1, 2100 (which also includes 'never') or below January 1, 2021 using the Edit buttons next to the graph.

Click 'Save snapshot,' to save your distribution to a static URL.

A timestamp will appear below the 'Save snapshot' button. This links to the URL of your snapshot.
Make sure to copy it before refreshing the page, otherwise it will disappear.

Copy the snapshot timestamp link and paste it into your LessWrong comment.

You can also add a screenshot of your distribution using the instructions below.

How to overlay distributions on the same graph

Copy your snapshot URL.
Paste it into the Import snapshot via URL box on the snapshot you want to compare your prediction to (e.g. the snapshot of Alex's distributions).
Rename your distribution to keep track.
Take a new snapshot if you want to save or share the overlaid distributions.

How to add an image to your comment

Take a screenshot of your distribution
Then do one of two things:

If you have beta-features turned on in your account settings, drag-and-drop the image into your comment
If not, upload it to an image hosting service, then write the following markdown syntax for the image to appear, with the url appearing where it says ‘link’: ![](link)

If it worked, you will see the image in the comment before hitting submit.

If you have any bugs or technical issues, reply to Ben...
[Oops, there is actually an event] Notice: No LW event this weekend
by Ben Pace — 2020-08-22T01:26:31.820Z

Just a notice to say there's no event this weekend.

Will be back to your regularly scheduled LW event on Sunday 29th, which we'll announce in a few days.

Update: We're having a double crux, between Buck Shlegeris and Oliver Habryka, on AI takeoff speeds. Event page.
What price would you pay for the RadVac Vaccine and why?
by Ben Goldhaber — 2020-08-22T00:17:56.155Z

I have been following with interest the RadVac team and their synthetic peptide based intranasal vaccine. They have published a protocol for making and taking the vaccine as well as a list of potential risks (on pg. 9 of the white paper).

How much would you pay for the RadVac vaccine? If you wouldn't use it - e.g. because you feel it's ineffective/risky - please say so and optionally put a negative number. And why would you pay that amount? An example of the type of model I'm looking for is $XX because you expect it would be effective at cutting your risk of COVID-19 by YY%, or because you think it might be dangerous you wouldn't take it at all.
The Ant Farm
by JimBaler — 2020-08-21T23:25:13.726Z

You are hired by an unknown person to do the simple task of taking care of an ant farm, they states that there are two rules: 1. Do not harm any of the ants 2. Make sure the needs of every ant are fulfilled each day, this task for you is very simple sense the needs of an ant let alone thousands of them are easily worked out and solved by you. As the days go by you start to notice that the once simple tasks you where used to start daunting on you, as you get better at assessing the needs of the ants you start noticing patterns and familiar instances of hard ships the ants face on a day to day bases and solving the same repetitive tasks start to weigh on you, you find yourself thinking that if you could just disobey the rules set by your employer for a split second it would to much more good for the ants than fallowing them. One day you see an ant attacking the queen you move the ant to a different part of the farm and go along with your routine until you notice the same ant attacking the queen again, at this moment you squish this ant, killing it in an instance, breaking the first rule but in your mind for the greater good of the whole colony.

This is what i have thought an A.I would do to the world after it deems that the human races problems can be solved by the erasure of one evil for the greater good, it goes on to systematically erase all evils sense due to its narrow frame of reference starts deeming all life as inertly evil the A.I decides that the erasure of all life is the only logical conclusion to stop the evil.

This is the grim conclusion that I and many others have thought would occur once the A.I gains this small sample size of life. It seemed inevitable to me that all A.I with the intentions of making life easier for humans would all reach this conclusion, so i started thinking if there was an easy way out. Many movies have shown the most easy way would be to just turn of the A.I to destroy it once an for all but this seems unrealistic that a super intelligent being would leave its off switch somewhere out in the open, so this line of thinking was lost on me, and then it hit me, why not create more A.I with the same goals in mind. This seemed obvious to me, when given a project to work on i always found myself at a loss for solutions once all the obvious ones where used up, and instead of throwing in the towel I would look to friends for help, ...
Thoughts on the Feasibility of Prosaic AGI Alignment?
by  — 2020-08-21T23:25:09.895Z

I’d like to preface by saying that I am not an expert on AI by any means, nor am I remotely involved with any kind of research or studies relevant to ML. I have no insight regarding any of the technical or mathematical aspects of discussions about this technology, and only deal in abstracts.

If you’re still reading this:

Let’s assume two things: (A) that the scaling hypothesis will continue to provide real-world empirical evidence that it’s a plausible approach to AGI (such as with GPT), and (B), that bigger, more well-funded institutions (such as Deepmind, GoogleBrain, and MicrosoftAI) will shift focus from building an AGI that results from or shows something new being revealed about intelligence to adopting OpenAI’s strategy of simply throwing more compute and hardware at the problem to get results (something that they actually have the resources to do in an uncomfortably short-term timeframe).

Whatever you believe (https://www.lesswrong.com/posts/N6vZEnCn6A95Xn39p/are-we-in-an-ai-overhang?commentId=jbD8siv7GMWxRro43) to be the actual likelihood of (B), please just humor me for the sake of discussion.

If you consider both assumptions (A) and (B) to be true with high probability, then you’re ultimately conceding that a prosaic AGI is the kind we’re most likely to build. This is discounting the unfortunately less-likely (imo) possibility that another, fundamentally different approach will succeed first.

I say “unfortunately” due to the fact that, by my understanding, most approaches towards AGI alignment (use MIRI as an example) aren’t relevant to the alignment of a prosaic AGI.

That’s not to say that there aren’t approaches towards this issue, because there are (https://www.lesswrong.com/posts/fRsjBseRuvRhMPPE5/an-overview-of-11-proposals-for-building-safe-advanced-ai). The problem is that these proposals have caveats that make institutions that I hold in very high regard (MIRI) consider these approaches to be almost certainly impossible.[(https://www.lesswrong.com/posts/Djs38EWYZG8o7JMWY/paul-s-research-agenda-faq), (https://www.lesswrong.com/posts/S7csET9CgBtpi7sCh/challenges-to-christiano-s-capability-amplification-proposal)]

But regardless, there is still some debate regarding whether or not Yudkowsky’s objections to the current proposals are as much of a knock-down argument in favor of their irreducible impossibility. (https://www.lesswrong.com/posts/3nDR23ks...
What's a Decomposable Alignment Topic?
by Logan Riggs — 2020-08-21T22:57:00.642Z

What's an alignment topic where, if someone decomposed the overall task, a small group of smart people (like here on Lesswrong) could make conceptual progress? By "smart", assume they can notice confusion, google, and program.

Be specific. Explain what strategies you would use to explore your topic, and give examples on decomposing tasks.

This is more than just an exercise in factored cognition; there are stakes: I host the key alignment group, and if your answer is convincing enough, then we'll work on it (caveat: some people may leave if your topic isn't their cup of tea, but others may join because it is). Additionally, you can pitch your idea in the key alignment group meeting on (8/25) Tuesday 7pm UTC; just DM me if you'd like to join the next meeting.
Epistemic Comparison: First Principles Land vs. Mimesis Land
by ozziegooen — 2020-08-21T22:28:09.172Z

Epistemic Status: wildly speculative

I've been thinking about the ideas of mimesis and cultural learning by René Girard (known in part for being recommended by Peter Thiel, explanation here) and Joseph Henrich (Secrets of our Success). These seem like both profound, though vastly unexplored ideas. René Girard had a few bold ideas on mimesis, but seemed to focus more on scapegoats and religious details. Joseph Henrich catalogued lots of specific evidence, but didn't really investigate the broader implications.[1]

There are obvious possibilities of these ideas to our epistemics. If it is true that humans copy their ideas from each other instead of deriving them based on reason, often without knowing it, this would have vast implications on our beliefs.

To understand these ideas better, I constructed two hypothetical and extremized societies. The first is "first principles land", where everyone constructs their beliefs individually using first principles. These people act basically as ideal Bayesian agents and approximate gears-levels understandings of everything. This is infinitely difficult to do in practice, but simple to reason about in abstract. The second is "Mimesis Land", where people copy their beliefs from those they consider successful, typically without realizing it (this bit taken from Girard). To make "Mimesis Land" work at all, I'd posit that there is some amount of experimentation of techniques and beliefs happening at all times.
I then compared these two hypothetically societies based on how I expected each to do on 17 various attributes.

See the document here.

Needless to say, Mimesis Land was more interesting to me than First Principles Land.

One tricky thing is that neither land was trying to model real humans; but humans that followed my simple view of a version of a set of extreme theories that might be somewhat coherent. There was a fair bit of subjectivity in this. I'm sure others would come up with significantly different versions of First Principles Land and Mimesis Land. As such I'm not particularly satisfied with this methodology, but at the same time I'm not sure what procedures would be strictly better.

I am bullish on trying to more clearly formulate what first principles thinking and mimesis fully look like in practice, and the costs and benefits of both. In both cases there seem to be fairly patchy terminology of several clu...
Live a life you feel excited about
by Neel Nanda — 2020-08-21T19:16:17.793Z
Link: https://www.neelnanda.io/blog/mini-blog-post-11-live-a-life-you-feel-excited-about

(This is a post from a personal daily blogging project on finding and cultivating intrinsic motivation, that I thought might be of interest to LessWrong readers)

I find that my motivation for tasks tends to divide into two very different kinds, extrinsic and intrinsic motivation. Extrinsic motivation is something outside myself, a feeling of guilt or obligation, something I need to do. An expectation I need to meet, a deadline I can’t miss. While intrinsic motivation comes from within, and is mostly characterised by a feeling of excitement. I really care about what I’m doing, it feels important to me, and I want to do it. With extrinsic motivation, I’m always pushing myself to keep up with it, while with intrinsic motivation it’s driving me forwards.

And I find tasks driven by excitement are awesome. I can spend far longer on them without feeling drained, I procrastinate less, I feel less guilt and anxiety. It’s far easier to focus. I feel joy and passion at what I’m doing, and the insecurities and doubt feel far distant.

And yet, when I look at my life, most of my motivation is extrinsic. Occasionally I have awesome tasks that I feel excited about, but it mostly feels like this is just something that happens to me, that finding excitement is not something I have any agency in. And, if I’m not paying attention, this will be true. But this is crazy. I’m still doing tasks either way, motivation is a property of my mind and how I approach things. And I refuse to spend most of my life in a shitty local optima, just because my mind is framing things badly. As with all things that matter in life, excitement can be optimised, and this post is about my best tools for doing so.

Building excitement is hard, and the approach will vary a lot between people. And it probably doesn’t seem obvious that it can be done at all. Excitement is a difficult and delicate equilibrium - once it’s gotten going it can have a lot of momentum behind it, but it’s rarely the kind of thing you can trivially make happen. And seeing this, it’s easy to conclude that it “can’t be forced” and move on. But this is just a failure of inner optimisation, trying harder in the moment. There are a lot of properties that can make a task more or less exciting, and a key skill is to notice these, and to s...
Universality Unwrapped
by adamShimi — 2020-08-21T18:53:25.876Z

Introduction

Informally, a universal system is universal with respect to any computation; and it is a universal system with respect to a given computation if it understands every set of beliefs that can be ascribed to the computation. The intuition is that the system can reverse engineer most or all of the computation, in order to monitor it or imitate it. This in turn has important consequences for questions of alignment and competitiveness. Universality is the property that defines a universal system. And it is the point of this post.

Universality tries to capture a property needed for many alignement schemes. It was proposed by Paul Christiano, the mind behind many approaches and ideas in the prosaic AGI space, and a founding member of the safety team at OpenAI. Rohin Shah dedicated a full Alignment Newsletter to covering all 6 posts on Universality. Rohin and Evan Hubinger, two important researchers in this field, consider Universality as one of the most exciting research idea of the last few years.[1] Yet nobody talks about Universality.

Except for the Alignment Newsletter mentioned above and a response post by Evan, nothing in the Alignment Forum addresses this idea. I've seen no great discussion, no debates, no counter-arguments or criticism. The original post on Medium has no comments, and the crossposted version here only has a handful, mostly asking for clarification. And the other posts in the sequence rely on understanding this first.

The simplest solution to this problem is to tell you to read the original post. Unfortunately, it is as dense as Q in R, brimming with ideas, intuitions, semi-formal explanations and the many meanderings that research takes before arriving on solid ground. That is to say, you'll have to work for it. Not everyone who might benefit from an understanding of Universality has the time, the need or the want for such an upfront investment.

This post endeavors to be the next best thing: an unwrapping of the main post on universality, from the perspective of one who already took the time to mine it for its insights. Because I started at the same point as you -- or even below -- our inferential distance is hopefully smaller than the one you have with Christiano. And armed with this clarification, you should also be able to tackle the next posts in his sequence.

Before digging into Universality itself, I present the perspective...