trentmkelly/LessWrong-43k huggingface dataset:
Willpower Schedule
by SquirrelInHell — 2016-08-22T13:05:41.997Z

TL;DR: your level of willpower depends on how much willpower you expect to need (hypothesis)

Time start: 21:44:55 (this is my third exercise in speed writing a LW post)

I.

There is a lot of controversy about how our level of willpower is affected by various factors, including doing "exhausting" tasks before, as well as being told that willpower is a resource that depletes easily, or doesn't etc.

(sorry, I can't go look for references - that would break the speedwriting exercise!)

I am not going to repeat the discussions that already cover those topics; however, I have a new tentative model which (I think) fits the existing data very well, is easy to test, and supersedes all previous models that I have seen.

II.

The idea is very simple, but before I explain it, let me give a similar example from a different aspect of our lives. The example is going to be concerned with, uh, poo.

Have you ever noticed that (if you have a sufficiently regular lifestyle), conveniently you always feel that you need to go to the toilet at times when it's possible to do so? Like for example, how often do you need to go when you are on a bus, versus at home or work?

The function of your bowels is regulated by reading subconscious signals about your situation - e.g. if you are stressed, you might become constipated. But it is not only that - there is a way in which it responds to your routines, and what you are planning to do, not just the things that are already affecting you.

Have you ever had the experience of a background thought popping up in your mind that you might need to go within the next few hours, but the time was not convenient, so you told that thought to hold it a little bit more? And then it did just that?

III.

The example from the previous section, though possibly quite POOrly choosen (sorry, I couldn't resist), shows something important.

Our subconscious reactions and "settings" of our bodies can interact with our conscious plans in a "smart" way. That is, they do not have to wait to see the effects of what you are doing, to adjust to it - they can pull information from your conscious plans and adjust *before*.

And this is, more or less, the insight that I have added to my current working theory of willpower. It is not very complicated, but perhaps non-obvious. Sufficiently non-obvious that I don't think anyone has suggested it before, even after seei...
DARPA accepting proposals for explainable AI
by morganism — 2016-08-22T00:05:32.180Z

"The XAI program will focus the development of multiple systems on addressing challenges problems in two areas: (1) machine learning problems to classify events of interest in heterogeneous, multimedia data; and (2) machine learning problems to construct decision policies for an autonomous system to perform a variety of simulated missions."

"At the end of the program, the final delivery will be a toolkit library consisting of machine learning and human-computer interface software modules that could be used to develop future explainable AI systems. After the program is complete, these toolkits would be available for further refinement and transition into defense or commercial applications"

http://www.darpa.mil/program/explainable-artificial-intelligence
Meetup : SF Meetup: Fun and Games
by maia — 2016-08-20T15:13:24.383Z

Discussion article for the meetup : SF Meetup: Fun and Games

WHEN:
22 August 2016 06:15:10PM (-0700)

WHERE:
1597 Howard St., SF

We’ll be meeting to play board (and other) games!

I have Dominion, Ticket to Ride, Suburbia, Set, and standard playing cards. Please feel free to bring other games you’d like to play.

For help getting into the building, please call (or text, with a likely-somewhat-slower response rate): three zero one, three five six, five four two four.

Format:

We meet and start hanging out at 6:15, but don’t officially start doing the meetup topic until 6:45-7 to accommodate stragglers. Usually there is a food order that goes out before we start the meetup topic.

About these meetups:

The mission of the SF LessWrong meetup is to provide a fun, low-key social space with some structured interaction, where new and non-new community members can mingle and have interesting conversations. Everyone is welcome.

We explicitly encourage people to split off from the main conversation or diverge from the topic if that would be more fun for them (moving side conversations into a separate part of the space if appropriate). Meetup topics are here as a tool to facilitate fun interaction, and we certainly don’t want them to inhibit it.

Discussion article for the meetup : SF Meetup: Fun and Games
Corrigibility through stratified indifference
by Stuart_Armstrong — 2016-08-19T16:11:33.343Z

A putative new idea for AI control; index here.

Corrigibility through indifference has a few problems. One of them is that the AI is indifferent between the world in which humans change its utility to v, and world in which humans try to change its utility, but fail.

Now the try-but-fail world is going to be somewhat odd - humans will be reacting by trying to change the utility again, trying to shut the AI down, panicking that a tiny probability event has happened, and so on.

That's not what we really want for indifference. We'd really want the AI to be indifferent between worlds where humans choose utility u, and worlds where they choose utility v. This kind of "causal" counterfactual has a problem: it allows infinite improbability drives.

Half a chance of winning the 1:9 lottery

Let's illustrate the problem with causal counterfactuals by considering a lottery scenario. An AI is currently hesitating between utilities u and v. Which one it will maximise will be determined at a later date, by human choice. Currently, it estimates that there is a 50-50 chance of humans deciding for either option.

However, the AI can influence human decision - let's say, for simplicity, that it could, if it wanted, force the human to pick either u or v with certainty. Its to this effect that we want to make it indifferent.

The AI has a lottery ticket, which will win with probability 0.1. If the ticket does win, the AI will be able to invest the cash to set u or v to the value 1; it can do so after the humans decide which utility is correct. If not, utility u will remain at 0 while utility v will be at 0.5.

Thus, currently, the expected utility of u is 0.5*0.1*1=0.05 (u will only increase if the AI both wins the lottery and the humans select u as the utility to maximise), while the expected utility of v is 0.5*0.1*1 + (1-0.5*0.1*1)0.5 = 0.525.

Obviously, this requires the use of some form of indifference, or else the AI will simply force humans to choose v, giving it 0.55 utility (not 0.525, as the AI is no longer uncertain over the human's choice).

Indifference

Standard indifference would be something like giving the AI compensatory returns, if v is chosen, that makes up the difference between that and if u was chosen.

This breaks the symmetry between u and v, though. To make it more symmetric, one could instead use these compensatory returns to move the expectation of both ...
Weekly LW Meetups
by FrankAdamek — 2016-08-19T15:40:31.378Z

This summary was posted to LW Main on August 19th. The following week's summary is here.

New meetups (or meetups with a hiatus of more than a year) are happening in:

Bay City Meetup: 19 August 2016 01:25PM

Irregularly scheduled Less Wrong meetups are taking place in:

Australian-ish Online Hangout: 20 August 2016 07:30PM
Baltimore Area Weekly Meetup: 21 August 2016 08:00PM
European Community Weekend: 02 September 2016 03:35PM

The remaining meetups take place in cities with regular scheduling, but involve a change in time or location, special meeting content, or simply a helpful reminder about the meetup:

[Moscow] Games in Kocherga club: FallacyMania, Zendo, Tower of Chaos: 24 August 2016 07:40PM
San Jose Meetup: Park Day (VII): 21 August 2016 03:00PM
Sydney Rationality Dojo - September 2016: 04 September 2016 04:00PM
Sydney Rationality Dojo - October 2016: 02 October 2016 04:00PM
Vienna: 20 August 2016 03:00PM
Washington, D.C.: Mini Talks: 21 August 2016 03:30PM

Locations with regularly scheduled meetups: Austin, Berlin, Boston, Brussels, Buffalo, Canberra, Columbus, Denver, Kraków, London, Madison WI, Melbourne, Moscow, New Hampshire, New York, Philadelphia, Research Triangle NC, San Francisco Bay Area, Seattle, Sydney, Tel Aviv, Toronto, Vienna, Washington DC, and West Los Angeles. There's also a 24/7 online study hall for coworking LWers and a Slack channel for daily discussion and online meetups on Sunday night US time.

If you'd like to talk with other LW-ers face to face, and there is no meetup in your area, consider starting your own meetup; it's easy (more resources here). Check one out, stretch your rationality skills, build community, and have fun!

In addition to the handy sidebar of upcoming meetups, a meetup overview is posted on the front page every Friday. These are an attempt to collect information on all the meetups happening in upcoming weeks. The best way to get your meetup featured is still to use the Add New Meetup feature, but you'll also have the benefit of having your meetup mentioned in a weekly overview. These overview posts are moved to the discussion section when the new post goes up.

Please note that for your meetup to appear in the weekly meetups feature, you need to post your meetup before the Friday before your meetup!

If you check Less Wrong irregularly, consider subscribing to one or m...
Modeling the capabilities of advanced AI systems as episodic reinforcement learning
by jessicata — 2016-08-19T02:52:13.000Z

Here I'll summarize the main abstraction I use for thinking about future AI
systems. This is essentially the same model that Paul uses.
I'm not actually introducing any new ideas in this post; mostly this is intended to summarize my current views.

Introduction

If we are to think of highly advanced AI systems, it is useful to treat some AI capabilities as a kind of black box: we need a good understanding of where the optimization power made possible by future hardware and algorithms is going, so that we can think about what the optimized things look like without knowing the exact details of the optimization algorithm. I'm going to state a generalization over some of these capabilities, which is based on current ML practice (training policies to optimize training objectives). The current single best model I know of for reasoning about highly capable AI systems is to assume that they have this general capability and no other capabilities.

The general capability can be stated as: trained policies will receive a high average within-episode training score, compared to alternative policies with similar resource bounds. I'll call this capability "general episodic RL".

To clarify "within-episode", we could consider a single classification task (classify this picture) as a single episode in a supervised learning context, where the policy is the classifier; we could consider solving a single SAT problem to be an episode in a SAT solving context, where the policy is a SAT solver; and of course we have episodes in an episodic RL context. So systems with this general capability are, among other things, good supervised learners, SAT solvers, and episodic RL agents.

Implications

If advanced AI systems have this general capability (and no other capabilities), this implies that:

We don't have good performance guarantees when test episodes are distinguishable from training episodes (i.e. when some distinguisher can look at an episode and tell whether it is a training episode or a test episode).

When the test episode is similar to training episodes (e.g. in an online learning context), we should expect trained policies to act like a rational agent maximizing its expected score in this test episode; otherwise, the policy that acts as a rational agent would would get a higher expected test score than this one, and would therefore receive the highest training score.

In pa

...
Deepmind Plans for Rat-Level AI 
by moridinamael — 2016-08-18T16:26:05.540Z

Demis Hassabis gives a great presentation on the state of Deepmind's work as of April 20, 2016. Skip to 23:12 for the statement of the goal of creating a rat-level AI -- "An AI that can do everything a rat can do," in his words. From his tone, it sounds like this is more a short-term, not a long-term goal.

I don't think Hassabis is prone to making unrealistic plans or stating overly bold predictions. I strongly encourage you to scan through Deepmind's publication list to get a sense of how quickly they're making progress. (In fact, I encourage you to bookmark that page, because it seems like they add a new paper about twice a month.) The outfit seems to be systematically knocking down all the "Holy Grail" milestones on the way to GAI, and this is just Deepmind. The papers they've put out in just the last year or so concern successful one-shot learning, continuous control, actor-critic architectures, novel memory architectures, policy learning, and bootstrapped gradient learning, and these are just the most stand-out achievements. There's even a paper co-authored by Stuart Armstrong concerning Friendliness concepts on that list.

If we really do have a genuinely rat-level AI within the next couple of years, I think that would justify radically moving forward expectations of AI development timetables. Speaking very naively, if we can go from "sub-nematode" to "mammal that can solve puzzles" in that timeframe, I would view it as a form of proof that "general" intelligence does not require some mysterious ingredient that we haven't discovered yet.
The Future of Humanity Institute is hiring!
by crmflynn — 2016-08-18T13:09:13.522Z

FHI is accepting applications for a two-year position as a full-time Research Project Manager. Responsibilities will include coordinating, monitoring, and developing FHI’s activities, seeking funding, organizing workshops and conferences, and effectively communicating FHI’s research. The Research Program Manager will also be expected to work in collaboration with Professor Nick Bostrom, and other researchers, to advance their research agendas, and will additionally be expected to produce reports for government, industry, and other relevant organizations.

Applicants will be familiar with existing research and literature in the field and have excellent communication skills, including the ability to write for publication. He or she will have experience of independently managing a research project and of contributing to large policy-relevant reports. Previous professional experience working for non-profit organisations, experience with effectiv altruism, and a network in the relevant fields associated with existential risk may be an advantage, but are not essential.

To apply please go to https://www.recruit.ox.ac.uk and enter vacancy #124775 (it is also possible to find the job by searching choosing “Philosophy Faculty” from the department options). The deadline is noon UK time on 29 August. To stay up to date on job opportunities at the Future of Humanity Institute, please sign up for updates on our vacancies newsletter at https://www.fhi.ox.ac.uk/vacancies/.
The barriers to the task
by Elo — 2016-08-18T07:22:56.612Z

Original post: http://bearlamp.com.au/the-barriers-to-the-task/

For about two months now I have been putting in effort to run in the mornings. To make this happen, I had to take away all the barriers to me wanting to do that. There were plenty of them, and I failed to leave my house plenty of times. Some examples are:

Making sure I don't need correct clothes - I leave my house shirtless and barefoot, and grab my key on the way out.

Pre-commitment to run - I take my shirt off when getting into bed the night before, so I don't even have to consider the action in the morning when I roll out of bed.

Being busy in the morning - I no longer plan any appointments before 11am. Depending on the sunrise (I don't use alarms), I wake up in the morning, spend some time reading things, then roll out of bed to go to the toilet and leave my house. In Sydney we just passed the depths of winter and it's beginning to get light earlier and earlier in the morning. Which is easy now; but was harder when getting up at 7 meant getting up in the dark.

There were days when I would wake up at 8am, stay in bed until 9am, then realise if I left for a run (which takes around an hour - 10am), then came back to have a shower (which takes 20mins - 10:20), then left to travel to my first meeting (which can take 30mins 10:50). That means if anything goes wrong I can be late to an 11am appointment. But also - if I have a 10am meeting I have to skip my run to get there on time.

Going to bed at a reasonable hour - I am still getting used to deciding not to work myself ragged. I decided to accept that sleep is important, and trust to let my body sleep as long as it needs. This sometimes also means that I can successfully get bonus time by keeping healthy sleep habits. But also - if I go to sleep after midnight I might not get up until later, which means I compromise my "time" to go running by shoving it into other habits.

Deciding where to run - google maps, look for local parks, plan a route with the least roads and least traffic. I did this once and then it was done. It was also exciting to measure the route and be able to run further and further each day/week/month.

What's in your way?

If you are not doing something that you think is good and right (or healthy, or ot...
Meetup : Baltimore Area Weekly Meetup
by iarwain1 — 2016-08-18T00:24:28.643Z

Discussion article for the meetup : Baltimore Area Weekly Meetup

WHEN:
21 August 2016 08:00:00PM (-0400)

WHERE:
1726 reisterstown road pikesville maryland 21208

Pikesville DoubleTree - Hilton, at the restaurant / bar or at one of the tables outside.

Discussion article for the meetup : Baltimore Area Weekly Meetup
Meetup : Games in Kocherga club: FallacyMania, Zendo, Tower of Chaos
by Alexander230 — 2016-08-17T18:39:34.200Z

Discussion article for the meetup : Games in Kocherga club: FallacyMania, Zendo, Tower of Chaos

WHEN:
24 August 2016 07:40:00PM (+0300)

WHERE:
Moscow, B.Dorogomilovskaya, 5-2

Welcome to Moscow LW community makeshift games! In that games, some rationality skills are involved, so you can practise while you playing!

FallacyMania: it is a game where you guess logical fallacies in arguments, or practise using logical fallacies yourself (depending on team in which you will be).

Details about the game: http://goo.gl/BtRVhB

Zendo: table game with guessing the rules about items placement on the table.

Game rules: https://goo.gl/RW2Fx7

Tower of Chaos: funny game with guessing the rules of human placement on a Twister mat.

Game rules: https://goo.gl/u9qgc3

Come to antikafe "Kocherga", ul.B.Dorogomilovskaya, 5-2. The map is here: http://kocherga-club.ru/#contacts . Nearest metro station is Kievskaya. If you are lost, call Sasha at +7-905-527-30-82.

Games begin at 19:40, the length is 3.5 hours.

Discussion article for the meetup : Games in Kocherga club: FallacyMania, Zendo, Tower of Chaos
Superintelligence via whole brain emulation
by AlexMennen — 2016-08-17T04:11:28.914Z

Most planning around AI risk seems to start from the premise that superintelligence will come from de novo AGI before whole brain emulation becomes possible. I haven't seen any analysis that assumes both uploads-first and the AI FOOM thesis (Edit: apparently I fail at literature searching), a deficiency that I'll try to get a start on correcting in this post.

It is likely possible to use evolutionary algorithms to efficiently modify uploaded brains. If so, uploads would likely be able to set off an intelligence explosion by running evolutionary algorithms on themselves, selecting for something like higher general intelligence.

Since brains are poorly understood, it would likely be very difficult to select for higher intelligence without causing significant value drift. Thus, setting off an intelligence explosion in that way would probably produce unfriendly AI if done carelessly. On the other hand, at some point, the modified upload would reach a point where it is capable of figuring out how to improve itself without causing a significant amount of further value drift, and it may be possible to reach that point before too much value drift had already taken place. The expected amount of value drift can be decreased by having long generations between iterations of the evolutionary algorithm, to give the improved brains more time to figure out how to modify the evolutionary algorithm to minimize further value drift.

Another possibility is that such an evolutionary algorithm could be used to create brains that are smarter than humans but not by very much, and hopefully with values not too divergent from ours, who would then stop using the evolutionary algorithm and start using their intellects to research de novo Friendly AI, if that ends up looking easier than continuing to run the evolutionary algorithm without too much further value drift.

The strategies of using slow iterations of the evolutionary algorithm, or stopping it after not too long, require coordination among everyone capable of making such modifications to uploads. Thus, it seems safer for whole brain emulation technology to be either heavily regulated or owned by a monopoly, rather than being widely available and unregulated. This closely parallels the AI openness debate, and I'd expect people more concerned with bad actors relative to accidents to disagree.

With de novo artificial superintelligence, ...
Meetup : Washington, D.C.: Mini Talks
by RobinZ — 2016-08-17T03:19:32.362Z

Discussion article for the meetup : Washington, D.C.: Mini Talks

WHEN:
21 August 2016 03:30:00PM (-0400)

WHERE:
Donald W. Reynolds Center for American Art and Portraiture

This week, we will be meeting in the courtyard to take turns delivering short lectures on random topics.

As always, side conversations are allowed and encouraged.

Upcoming meetups:

Aug. 28: Legos

Sep. 4: Fun & Games

Sep. 11: Singing

Discussion article for the meetup : Washington, D.C.: Mini Talks