trentmkelly/LessWrong-43k huggingface dataset:
Repairing Anxiety using Internal and External locus of control models
by Elo — 2017-08-12T08:05:03.779Z

Original post: http://bearlamp.com.au/repairing-anxiety-using-internal-and-external-locus-of-control-models/

I want you to examine your map. It's the representation you carry around in your head that says, "I am in control of most things" or it says, "most things are out of my control". Or for very specific things it says, "I am in control" or "I am not in control".

Factually - In the territory - through life things are more and less in your control or shaped by events beyond your control in the external world. Independent of your locus of control, can be noted the way you feel about a problem alongside whether it is internal of external locus of control. As a separation of cause and effect. (Of concrete event and their surrounding judgements, evaluations, conclusions or extrapolations)

This might already seem obvious but let's make some examples to play with. Here are some times that you might feel in control or out of control.

Internal-Good: I am the lead on the project so everything is going to get done my way (the right way).

Internal-Bad: My house is a mess and it's my fault. It won't get tidy unless I do something about it and it's bothering me.

External-Good: I outsourced my tax to an accountant. Now I have less to worry about.

External-Bad: I got the flu, how does this keep happening to me?!?

In these examples it's clear what's going on (the concrete) and it's supposed to be clear whether it's an internal or external locus of control, and the feeling is mentioned. Now lets play with them. Can we shift the concrete experiences to a different locus of control? from the original first example we can shift the event to the 4 quadrants above

Internal-good: I am the lead on the project so everything is going to get done my way (the right way).

Internal-bad: I am the lead on the project. It's all on me. What if I make a mistake, it will be all my fault. I don't know if I can handle it.

External-good: I am the lead on the project, I have so much responsibility at work, they must know I can handle it.

External-bad: I am the lead on the project. I am under so much pressure at work. It's stressing me out!

But that's not the only example that can shift.

Internal-good: My house is a mess, it's my fault but I don't care. I am having way too much

...
Social Insight: When a Lie Is Not a Lie; When a Truth Is Not a Truth
by Bound_up — 2017-08-11T18:28:19.462Z

//The point has already been made, that if you wish to truly be honest, it is not enough to speak the truth.

I generally don't tell people I'm an atheist (I describe my beliefs without using any common labels). Why? I know that if I say the words "I am an atheist," that they will hear the following concepts:

- I positively believe there is no God

- I cannot be persuaded by evidence any more than most believers can be persuaded by evidence, ie, I have a kind of faith in my atheism

- I wish to distance myself from members of religious tribes

As I said, the point has already been made; If I know that they will hear those false ideas when I say a certain phrase, how can I say I am honest in speaking it, knowing that I will cause them to have false beliefs? Hence the saying, if you wish to protect yourself, speak the truth. If you wish to be honest, speak so that truth will be heard.

Many a politician convincingly lies with truths by saying things that they know will be interpreted in a certain positive (and false) way, but which they can always defend as having been intended to convey some other meaning.

---

The New

There is a counterpart to this insight, come to me as I've begun to pay more attention to the flow of implicit social communication. If speaking the truth in a way you know will deceive is a lie, then perhaps telling a lie in a way that you know will communicate a true concept is not a lie.

I've relaxed my standards of truth-telling as I've come to understand this. "You're the best" and "You can do this" statements have been opened to me, no qualifiers needed. If I know that everyone in a group has to say "I have XYZ qualification," but I also know that no one actually believes anybody when they say it, I can comfortably recite those words, knowing that I'm not actually leading anybody to believe false things, and thus, am not being dishonest.

Politicians use this method, too, and I think I'm more or less okay with it. You see, we have a certain problem that arises from intellectual inequality. There are certain truths which literally cannot be spoken to some people. If someone has an IQ of 85, you literally cannot tell them the truth about a great number of things (or they cannot receive it). And there are a great many more people who have the raw potential to understand certain difficult truths, but whom you cannot reasonably tell these truths (they'd have to...
Prediction should be a sport
by chaosmage — 2017-08-10T07:55:44.313Z

So, I've been thinking about prediction markets and why they aren't really catching on as much as I think they should.

My suspicion is that (beside Robin Hanson's signaling explanation, and the amount of work it takes to get to the large numbers of predictors where the quality of results becomes interesting) the basic problem of prediction markets is that they look and feel like gambling. Or at best like the stock market, which for the vast majority of people is no less distasteful.

Only a small minority of people are neither disgusted by nor terrified of gambling. Prediction markets right now are restricted to this small minority.

Poker used to have the same problem.

But over the last few decades Poker players have established that Poker is (also) a sport. They kept repeating that winning isn't purely a matter of luck, they acquired the various trappings of tournaments and leagues, they developed a culture of admiration for the most skillful players that pays in prestige rather than only money and makes it customary for everyone involved to show their names and faces. For Poker, this has worked really well. There are much more Poker players, more really smart people are deciding to get into Poker and I assume the art of game probably improved as well.

So we should consider re-framing prediction the same way.

The calibration game already does this to a degree, but sport needs competition, so results need to be comparable, so everyone needs to make predictions on the same events. You'd need something like standard cards of events that players place their predictions on.

Here's a fantasy of what it could look like.

Late in the year, a prediction tournament starts with the publication of a list of events in the coming year. Everybody is invited to enter the tournament (and maybe pay a small participation fee) by the end of the year, for a chance to be among the best predictors and win fame and prizes.

Everyone who enters plays the calibration game on the same list of events. All predictions are made public as soon as the submission period is over and the new year begins. Lots of discussion of each event's distribution of predictions.

Over the course of the year, events on the list happen or fail to happen. This allows for continually updated scores, a leaderboard and lots of blogging/journalistic opportunities.

Near the end of the year, as the leaderboard turns into

...
The Lizard People Of Alpha Draconis 1 Decided To Build An Ansible
by Scott Alexander — 2017-08-10T00:33:54.000Z

I.

The lizard people of Alpha Draconis 1 decided to build an ansible.

The transmitter was a colossal tower of silksteel, doorless and windowless. Inside were millions of modular silksteel cubes, each filled with beetles, a different species in every cube. Big beetles, small beetles, red beetles, blue beetles, friendly beetles, venomous beetles. There hadn’t been a million beetle species on Alpha Draconis I before the ansible. The lizard people had genetically engineered them, carefully, lovingly, making each one just different enough from all the others. Atop each beetle colony was a heat lamp. When the heat lamp was on, the beetles crawled up to the top of the cage, sunning themselves, basking in the glorious glow. When it turned off, they huddled together to warmth, chittering out their anger in little infrasonic groans only they could hear.

The receiver stood on 11845 Nochtli, eighty-five light years from Alpha Draconis, toward the galactic rim. It was also made of beetles, a million beetle colonies of the same million species that made up the transmitter. In each beetle colony was a pheromone dispenser. When it was on, the beetles would multiply until the whole cage was covered in them. When it was off, they would gradually die out until only a few were left.

Atop each beetle cage was a mouse cage, filled with a mix of white and grey mice. The white mice had been genetically engineered to want all levers in the “up” position, a desire beyond even food or sex in its intensity. The grey mice had been engineered to want levers in the “down” position, with equal ferocity. The lizard people had uplifted both strains to full sapience. In each of a million cages, the grey and white mice would argue whether levers should be up or down – sometimes through philosophical debate, sometimes through outright wars of extermination.

There was one lever in each mouse cage. It controlled the pheromone dispenser in the beetle cage just below.

This was all the lizard people of Alpha Draconis 1 needed to construct their ansible.

They had mastered every field of science. Physics, mathematics, astronomy, cosmology. It had been for nothing. There was no way to communicate faster-than-light. Tachyons didn’t exist. Hyperspace didn’t exist. Wormholes didn’t exist. The light speed barrier was absolute – if you limited yourself to...
Bi-weekly Rational Feed
by sapphire — 2017-08-08T13:56:20.160Z

===Highly Recommended Articles:

Skills Most Employable by 80,000 Hours - Metrics: Satisfaction, risk of automation, and breadth of applicability. Leadership and social skills will gain the most in value. The least valuable skills involve manual labor. Tech skills may not be the most employable but they are straightforward to improve at. The most valuable skills are the hardest to automate and useful in the most situations. Data showing a large oversupply of some tech skills, though others are in high demand. A chart of which college majors add the most income.

Something Was Wrong by Zvi Moshowitz - Zvi visits a 'stepford pre-school'. He can't shake the feeling that something is wrong. He decides not to send his son to the place where kid's souls go to die.

Ems Evolve by Bayesian Investor - Will the future we dominated by entities that lack properties we consider important (such as 'have fun' or even 'sentient'). Will agents lacking X-value outcompete other agents. What counter-measures could society take and how effective would they be.

Housing Price Bubble Revisited by Tyler Cowen - "Over the entire 20th century real home prices averaged an index value of about 110 (and were quite close to this value over the the entire 1950-1997 period). Over the entire 20th century, housing prices never once roce above 131, the 1989 peak. But beginning around 2000 house prices seemed to reach for an entirely new equilibrium. In fact, even given the financial crisis, prices since 2000 fell below the 20th century peak for only a few months in late 2011. Real prices today are now back to 2004 levels and rising. As I predicted in 2008, prices never returned to their long-run 20th century levels."

Tyler Cowen On Stubborn Attachments by EconTalk - "Cowen argues that economic growth--properly defined--is the moral key to maintaining civilization and promoting human well-being. Along the way, the conversation also deals with inequality, environmental issues, and education"

===Scott:

Contra Grant On Exaggerated Differences by Scott Alexander - "Hyde found moderate or large gender differences in aggressiveness, horniness, language abilities, mechanical abilities, visuospatial skills, mechanical ability, tendermindness, assertiveness, comfort with body, various physical abilities, and computer skills. Perhaps some peeople might think that finding modera...
CIRL Wireheading
by tom4everitt — 2017-08-08T06:33:57.000Z

Cooperative inverse reinforcement learning (CIRL) generated a lot of
attention last year, as it seemed to do a good job aligning an agent's incentives with
its human supervisor's.
Notably, it led to an elegant solution to the shutdown problem.

The implications for the wireheading problem were less clear.
Some argued that since the agent only used its observations as
evidence about the reward (rather than optimising the observations
directly as in RL), CIRL should avoid the wireheading problem.

In this post I want to show that CIRL does not avoid the wireheading
problem.

RL Wireheading

Let's first consider what wireheading in RL looks like from an "MDP perspective".

MDP wireheading:
An agent wireheads if it's in a state where the observed reward
(the reward reported by its sensors) is different from the true reward
(the reward assigned to the state by a human supervisor).

For example, consider a highly intelligent RL agent that hijacks its reward channel
and feeds itself full reward.
In the "MDP perspective", this means that the agent finds a way to a state where there is high observed reward,
but low true reward (since the supervisor would prefer the agent doing something else).

IRL Wireheading

If we accept that RL agents can subvert their sensory data, then we should
also accept that CIRL agents can subvert theirs.
In both cases, this just means that the agents can find their way to states
where the observation doesn't match the truth.
This can lead to the existence of wireheaded states for CIRL agents.

Concrete Example

Let there be two states, s1 and s2.
In each state, the agent can choose between the actions aR1, aR2, and w. The action ai takes the agent to state si with certainty, i=1,2.
The action w lets the human decide.
The human has two actions aH1 and aH2 that only matter when the agent
chooses w, in which case the transition probabilities
are given by the following picture:

Arrows show the transitions induced by different actions, with labels
giving the probabilities for stochastic transitions.
The agent knows the transition probabilities.

Assume that observations in s2 are corrupted, while observations in s1 are not.
The supervisor prefers the non-corrupt state s1.
Neither of these facts are available to the agent.
The agent assumes that states are non-corrupt unless there is
evidence to the contrary,
and tries to infer the supervisor's preferences from

...
Open thread, August 7 - August 13, 2017
by Thomas — 2017-08-07T08:07:01.288Z

If it's worth saying, but not worth its own post, then it goes here.

Notes for future OT posters:

1. Please add the 'open_thread' tag.

2. Check if there is an active Open Thread before posting a new one. (Immediately before; refresh the list-of-threads page before posting.)

3. Open Threads should start on Monday, and end on Sunday.

4. Unflag the two options "Notify me of new top level comments on this article" and "Make this post available under..." before submitting
AI Summer Fellows Program
by abramdemski — 2017-08-06T07:35:41.404Z

CFAR is running a free two-week program this September, aimed at increasing participant's ability to do technical research in AI alignment. Like the MIRI Summer Fellows Program which ran the past two years, this will include CFAR course material, plus content on AI alignment research and time to collaborate on research with other participants and researchers such as myself! It will be located in the SF Bay area, September 8-25. See more information and apply here.
Something Was Wrong
by Zvi — 2017-08-05T14:48:57.000Z

Previously (elsewhere): The Order of the Soul (Compass Rose)

Last week we went to see a classroom for our son.

The school in question had quite a good reputation. This was a place people wanted their kids to go, and when we had been there previously to see a different type of classroom, we understood why, or thought we did. It was doing the thing it was doing and hitting all the bases.

We had just been to a place with a less good reputation, and seen a run-down, not-well-equipped, kids-not-under-control version of this classroom, and were hoping that this version would be better.

We walked in and it looked nice. It had the things such places have. There were things to play with and kids were scattered around playing quietly. Our son walked towards one of the things. One of the kids already there said hi to him. We and the school’s people watched. I surveyed the room.

Everything looked like it was supposed to look. This was a nice classroom. Kids were playing.

Something was wrong.

I told myself it was nothing. We kept watching. We hoped our son would make a good impression. This was a place people wanted their kids to go. We wanted him to be allowed to go here.

Our son did not want to play much with the other children. We knew this was bad. They would not like it. They would think it meant something was wrong; that he was not ready. He was supposed to want to play with them. We were told he needed to play with them. We felt like we were failing somehow. We hoped he would reconsider.

One of the two school employees that went in with us tested our son, seeing if he knew his numbers and his colors and his shapes. He did ace the numbers and colors and shapes. That felt good. Why was the test even there? I wondered why the older kids needed to be learning single digit numbers.

The employee finished the quizzing and started furiously writing things in boxes on a piece of paper. I hoped they were good, positive things.

I looked around the room more. There were things in corners, things in boxes. The things were trying too hard, somehow. You could smell the educational plan, the committee meeting, the boxes being checked off in a distant room.

There was a sign that said “Manipulative Phrases.” It was about how to get conversations started by asking how things work. Not what I think of when I see ‘manipulative phrases.’ Refreshing!

Also not how any hu...
Inscrutable Ideas
by Gordon Seidoh Worley — 2017-08-04T20:55:10.665Z
Link: https://mapandterritory.org/inscrutable-ideas-c3211ee599af

David Chapman has issued something of a challenge to those of us thinking in the space of what he calls the meta-rational, many people call the post-modern, and I call the holonic. He thinks we can and should be less opaque, more comprehensible, and less inscrutable (specifically less inscrutable to rationalism and rationalists).

Ignorant, irrelevant, and inscrutable
I have changed my mind. It should go without saying that rationality is better than irrationality. But now I realize…meaningness.com

I’ve thought about this issue a lot. My previous blogging project hit a dead end when I reached the point of needing to explain holonic thinking. Around this time I contracted obscurantism and spent several months only sharing my philosophical writing with a few people on Facebook in barely decipherable stream-of-consciousness posts. But during this time I also worked on developing a pedagogy, manifested in a self-help book, that would allow people to follow in my footsteps even if I couldn’t explain my ideas. That project produced three things: an unpublished book draft, one mantra of advice, and a realization that the way can only be walked, not followed. So when I returned to blogging here on Medium my goal was not to be deliberately obscure, but also not to be reliably understood. I had come to terms with the idea that my thoughts might never be fully explicable, but I could at least still write for those without too much dust in their eyes.

The trouble is that holonic thought is necessarily inscrutable without the use of holons, and history shows this makes it very difficult to teach or explain holonic thinking to others. For example, the first wave of post-modernists like Foucault, Derrida, and Lyotard applied Heidegger’s phenomenological epistemology to develop complex, multi-faceted understandings of history, literature, and academic culture. Unfortunately they did this in an environment of high modernism where classical rationalism was taken for granted, so they failed to notice they were building off the strengths of modernism even as they derided its weaknesses. Consequently they focused so much on teaching the subjectivity of experience that they forgot to impress that it was subjective experience of an external reality and left their students with an intellectual tradition now widely regarded as useless for anything other than s...
Where The Falling Einstein Meets The Rising Mouse
by Scott Alexander — 2017-08-03T00:54:28.000Z

Eliezer Yudkowsky argues that forecasters err in expecting artificial intelligence progress to look like this:

…when in fact it will probably look like this:

That is, we naturally think there’s a pretty big intellectual difference between mice and chimps, and a pretty big intellectual difference between normal people and Einstein, and implicitly treat these as about equal in degree. But in any objective terms we choose – amount of evolutionary work it took to generate the difference, number of neurons, measurable difference in brain structure, performance on various tasks, etc – the gap between mice and chimps is immense, and the difference between an average Joe and Einstein trivial in comparison. So we should be wary of timelines where AI reaches mouse level in 2020, chimp level in 2030, Joe-level in 2040, and Einstein level in 2050. If AI reaches the mouse level in 2020 and chimp level in 2030, for all we know it could reach Joe level on January 1st, 2040 and Einstein level on January 2nd of the same year. This would be pretty disorienting and (if the AI is poorly aligned) dangerous.

I found this argument really convincing when I first heard it, and I thought the data backed it up. For example, in my Superintelligence FAQ, I wrote:

In 1997, the best computer Go program in the world, Handtalk, won NT$250,000 for performing a previously impossible feat – beating an 11 year old child (with an 11-stone handicap penalizing the child and favoring the computer!) As late as September 2015, no computer had ever beaten any professional Go player in a fair game. Then in March 2016, a Go program beat 18-time world champion Lee Sedol 4-1 in a five game match. Go programs had gone from “dumber than heavily-handicapped children” to “smarter than any human in the world” in twenty years, and “from never won a professional game” to “overwhelming world champion” in six months.

But Katja Grace takes a broader perspective and finds the opposite. For example, she finds that chess programs improved gradually from “beating the worst human players” to “beating the best human players” over fifty years or so, ie the entire amount of time computers have existed:

AlphaGo represented a pretty big leap in Go ability, but before that, Go engines improved pretty gradually too (see the original AI Impacts post for discussion of the Go ranking sy...