trentmkelly/LessWrong-43k huggingface dataset:
50 Ways To Leave Your Therapist: Termination and why it's important
by squidious — 2017-11-05T01:00:01.646Z

I've heard a number of people talk negatively about professionals they feel stuck with. "I feel like my dentist is judging me for not flossing enough", "I don't feel like I can be honest with my doctor", "I wish my hair stylist didn't ask so many questions". We feel stuck with these people because, despite the lack of a personality fit, they may be really good at their job, perhaps better than anyone else we've turned to. We are hesitant to look for someone else, and risk it with someone who may not do a good job.

When it comes the therapeutic work, the alliance between client and therapist is widely considered to be the most important part -- more than theory or technique. So although we may feel compelled to continue, a therapist we cannot deeply trust isn't going to be as helpful as one we do -- in some cases, the wrong therapist can actually prevent us from moving forward.

A good therapist may be attuned to this. Some therapists will ask a client about how they feel therapy is going, and occasionally, a therapist may even refer a client to someone else if they feel they cannot do a good job. Most times, though, it is on the client to decide how well therapy is working for them. This means that if therapy isn't working, they have to decide what to do about that.

The most common way for a therapeutic relationship to end is that the client disappears. Sometimes, they call to cancel the appointment and never reschedule. Other times, they stop showing up altogether. Either way, the client and therapist never get to go through a true termination phase (the final phase of the therapeutic process).

The termination phase is arguably where the most work gets done. Clients who have trouble with endings (attachment issues, grief and loss, separation anxiety) may grow the most here, and having a planned, positive termination can be crucial for the client's growth. We don't often get a chance to experience positive ends to relationships, and this is one of the few ways we do. If termination is planned in advance, therapist and client can work together to find something special to do together for the last session. Sometimes that's a special activity, other times it's just a discussion on the client's growth over the course of therapy and things to keep in mind going forward. Some therapists like to use a transitional object -- a gift of sorts, to remind the client of their

...
Moloch's Toolbox (1/2)
by Eliezer Yudkowsky — 2017-11-04T21:46:32.597Z

Follow-up to: An Equilibrium of No Free Energy

There’s a toolbox of reusable concepts for analyzing systems I would call “inadequate”—the causes of civilizational failure, some of which correspond to local opportunities to do better yourself. I shall, somewhat arbitrarily, sort these concepts into three larger categories:

1. Decisionmakers who are not beneficiaries;

2. Asymmetric information;

and above all,

3. Nash equilibria that aren’t even the best Nash equilibrium, let alone Pareto-optimal.

In other words:

1. Cases where the decision lies in the hands of people who would gain little personally, or lose out personally, if they did what was necessary to help someone else;

2. Cases where decision-makers can’t reliably learn the information they need to make decisions, even though someone else has that information; and

3. Systems that are broken in multiple places so that no one actor can make them better, even though, in principle, some magically coordinated action could move to a new stable state.

I will then play fast and loose with these concepts in order to fit the entire Taxonomy of Failure inside them.

For example, “irrationality in the form of cognitive biases” wouldn’t obviously fit into any of these categories, but I’m going to shove it inside “asymmetric information” via a clever sleight-of-hand. Ready? Here goes:

If nobody can detect a cognitive bias in particular cases, then from our perspective we can’t really call it a “civilizational inadequacy” or “failure to pluck a low-hanging fruit.” We shouldn’t even be able to see it ourselves. So, on the contrary, let’s suppose that you and some other people can indeed detect a cognitive bias that’s screwing up civilizational decisionmaking.

Then why don’t you just walk up to the decision-maker and tell them about the bias? Because they wouldn’t have any way of knowing to trust you rather than the other five hundred people trying to influence their decisions? Well, in that case, you’re holding information that they can’t learn from you! So that’s an “asymmetric information problem,” in much the same way that it’s an asymmetric information problem when you’re trying to sell a used car and you know it doesn’t have any mechanical problems, but you have no way of reliably conveying this knowledge to the buyer because for all they kno...
War(Craft) Never Changes
by Raemon — 2017-11-04T21:09:40.885Z

This was a Facebook post, which I decided I wanted in some kind of blog form. Requires at least some familiarity with WarCraft. Relevant to those who have sought the Sword of Good and Heard the Scream. (Obviously not suited for the front-page, although more LW-relevant than I was expecting when I started writing)

The new WarCraft expansion cinematic punches me right in the "what the fuck is wrong with you people, you have just spent 10 years learning to work together against world-ending horrors can you not spent 5 FUCKING SECONDS chilling out before going to war again?"

Also punches me in the feels.

When I ranted about this to my girlfriend, she said "they just finished stopping a Big Bad together and now they're back to infighting? Honestly... that sounds pretty realistic."

And I briefly reflect upon history... and, sure. Okay. Humans are in fact shitty, and metaphorical stand-ins for humans are shitty too.

Geopolitical stability is hard. Giant war machines are going to lobby to keep being useful. People are going to want to reclaim their ancestral homeland and the new people living in that ancestral homeland are going to be upset. Par for the course.

Fine.

But, Sylvannas and Anduin are specific individual people with history and agency and shit. Why are they leading the charge in this pointless cycle of violence?

[Shoulder-Cynic says "Really, you have faith in individuals at the top of giant geopolitical war machines to not warp themselves in the face of social pressure to do the things their angsty, riled up fellows want, at least some of whom might be powerful enough to take command if the king slipped?"]

Well, when you put it that way, no, I don't. But...

[Shoulder-Scientist says "did you actually explore hypothesis space and form probability distributions before getting mad at the artistic directors?"]

...no.

[Shoulder-Different-Cynic says "Sure, it's boring that War Never Changes and that the Horde and Alliance haven't gotten over their bullshit in 25 years. But, how long do you observe Real World Powers taking to get over their bullshit?]

But, they just literally killed Satan together!

[And Russia and the Allied folk killed Hitler together. How'd that work out?]

Okay. When I stop, and think about what the World of Azeroth is actually like, and what pressures Anduin and Sylvannas are probably und...
Cooperative model knob-turning
by Gust — 2017-11-03T16:18:48.229Z

(Cross-posted from my medium channel)

When you are trying to understand something by yourself, a useful skill to check your grasp on the subject is to try out the moving parts of your mental model and see if you can simulate the resulting changes.

Suppose you want to learn how a rocket works. At the bare minimum, you should be able to calculate the speed of the rocket given the time past launch. But can you tell what happens if Earth gravity was stronger? Weaker? What if the atmosphere had no oxygen? What if we replaced the fuel with Diet Coke and Mentos?

To really understand something, it's not enough to be able to predict the future in a normal, expected, ceteris paribus scenario. You should also be able to predict what happens when several variables are changed is several ways, or, at least, point to which calculations need to be run to arrive at such a prediction.

Douglas Hofstadter and Daniel Dennett call that "turning the knobs". Imagine your model as a box with several knobs, where each knob controls one aspect of the modeled system. You don't have to be able to turn all the possible knobs to all possible values and still get a sensible, testable and correct answer, but the more, the better.

Doug and Dan apply this approach to thought experiments and intuition pumps, as a way to explore possible answers to philosophical questions. In my experience, this skill is also effective when applied to real world problems, notably when trying to understand something that is being explained by someone else.

In this case, you can run this knob-turning check cooperatively with the other person, which makes it way more powerful. If someone says “X+Y = Z” and “X+W = Z+A”, it’s not enough to mentally turn the knobs and calculate “X+Y+W = Z+A+B”. You should do that, then actually ask the explainer “Hey, let me see if I get what you mean: for example, X+Y+W would be Z+A+B”?

This cooperative model knob-turning has been useful to me in many walks of life, but the most common and mundane application is helping out people at work. In that context, I identify six effects which make it helpful:

1) Communication check: maybe you misunderstood and actually X+W = Z-A

This is useful overall, but very important if someone uses metaphor. Some metaphors are clearly vague and people will know that and avoid them in technical explanations. But some metaphors seem really cr...
Announcing the AI Alignment Prize

by cousin_it — 2017-11-03T15:47:00.092Z

Stronger than human artificial intelligence would be dangerous to humanity. It is vital any such intelligence’s goals are aligned with humanity's goals. Maximizing the chance that this happens is a difficult, important and under-studied problem.

To encourage more and better work on this important problem, we (Zvi Mowshowitz and Vladimir Slepnev) are announcing a $5000 prize for publicly posted work advancing understanding of AI alignment, funded by Paul Christiano.

This prize will be awarded based on entries gathered over the next two months. If the prize is successful, we will award further prizes in the future.

The prize is not backed by or affiliated with any organization.

Rules

Your entry must be published online for the first time between November 3 and December 31, 2017, and contain novel ideas about AI alignment. Entries have no minimum or maximum size. Important ideas can be short!

Your entry must be written by you, and submitted before 9pm Pacific Time on December 31, 2017. Submit your entries either as links in the comments to this post, or by email to apply@ai-alignment.com. We may provide feedback on early entries to allow improvement.

We will award $5000 to between one and five winners. The first place winner will get at least $2500. The second place winner will get at least $1000. Other winners will get at least $500.

Entries will be judged subjectively. Final judgment will be by Paul Christiano. Prizes will be awarded on or before January 15, 2018.

What kind of work are we looking for?

AI Alignment focuses on ways to ensure that future smarter than human intelligence will have goals aligned with the goals of humanity. Many approaches to AI Alignment deserve attention. This includes technical and philosophical topics, as well as strategic research about related social, economic or political issues. A non-exhaustive list of technical and other topics can be found here.

We are not interested in research dealing with the dangers of existing machine learning systems commonly called AI that do not have smarter than human intelligence. These concerns are also understudied, but are not the subject of this prize except in the context of future smarter than human intelligence. We are also not interested in general AI research. We care about AI alignment, which may or may not also advance the cause of general AI research.

(Addendum: the results of the prize and...
Announcing the AI Alignment Prize
by cousin_it — 2017-11-03T15:45:14.810Z

Stronger than human artificial intelligence would be dangerous to humanity. It is vital any such intelligence’s goals are aligned with humanity's goals. Maximizing the chance that this happens is a difficult, important and under-studied problem.

To encourage more and better work on this important problem, we (Zvi Mowshowitz and Vladimir Slepnev) are announcing a $5000 prize for publicly posted work advancing understanding of AI alignment, funded by Paul Christiano.

This prize will be awarded based on entries gathered over the next two months. If the prize is successful, we will award further prizes in the future.

This prize is not backed by or affiliated with any organization.

Rules

Your entry must be published online for the first time between November 3 and December 31, 2017, and contain novel ideas about AI alignment. Entries have no minimum or maximum size. Important ideas can be short!

Your entry must be written by you, and submitted before 9pm Pacific Time on December 31, 2017. Submit your entries either as URLs in the comments below, or by email to apply@ai-alignment.com. We may provide feedback on early entries to allow improvement.

We will award $5000 to between one and five winners. The first place winner will get at least $2500. The second place winner will get at least $1000. Other winners will get at least $500.

Entries will be judged subjectively. Final judgment will be by Paul Christiano. Prizes will be awarded on or before January 15, 2018.

What kind of work are we looking for?

AI Alignment focuses on ways to ensure that future smarter than human intelligence will have goals aligned with the goals of humanity. Many approaches to AI Alignment deserve attention. This includes technical and philosophical topics, as well as strategic research about related social, economic or political issues. A non-exhaustive list of technical and other topics can be found here.

We are not interested in research dealing with the dangers of existing machine learning systems commonly called AI that do not have smarter than human intelligence. These concerns are also understudied, but are not the subject of this prize except in the context of future smarter than human intelligence. We are also not interested in general AI research. We care about AI Alignment, which may or may not also advance the cause of general AI research.
Preferences over non-rewards
by Stuart_Armstrong — 2017-11-03T15:28:02.504Z

In this penultimate post on "learning human values" series, I just want to address some human values/preferences/rewards that don't fit neatly into the (p, R) model where p in the planning algorithm and R the actual reward.

Preferences over preferences and knowledge

Most people have preferences over their own preferences - and that of others. For example, consider someone who has an incorrect religious faith. They might believe something like:

"I want to always continue believing. I flinch away from certain sceptical arguments, but I'm sure my deity would protect me from doubt if I ever decided to look into them".

Hope this doesn't sound completely implausible for someone. Here they have beliefs, preferences over their future beliefs, and beliefs over their future beliefs. This doesn't seem to be able to be easily captured in the (p, R) framework. We can also see that asking them equivalent questions "Do you want to doubt your deity?" and "Do you want to learn the truth?" will get very different answers.

But it's not just theism, an example which is too easy to pick on. I have preferences over knowledge, for instance, as do most people. I would prefer that people had accurate information, for instance. I would also prefer that, when choosing between possible formalisations of preferences, people went with the less destructive and less self-destructive options. These are not overwhelmingly strong preferences, but they certainly exist.

Aliefs

Consider the following scenario: someone believes that roller-coasters are perfectly safe, but enjoys riding them for the feeling of danger they give them. It's clear that the challenge here is not reconciling the belief of safety with the alief of danger (which is simple: roller-coasters are safe), but to somehow transform the feeling of danger into another form that keeps the initial enjoyment.

Tribalism and signalling

The theism argument might suggest that tribalism will be a major problem, as various groups pressure adherents to conform to certain beliefs and preferences.

But actually that need not be such a problem. It's clear that there is a strong desire to remain part of that group (or, sometimes, just of a group). Once that desire is identified, all the rest become instrumental - the human will either do the actions that are needed to remain part of...
Normative assumptions: answers, emotions, and narratives
by Stuart_Armstrong — 2017-11-03T15:27:28.949Z

Agents can be modelled as pairs (p, R), where R is a reward, and p is a planner that takes R and more or less rationally outputs the policy p(R).

Normative assumptions are assumptions that can distinguish between different pairs (p, R) and (p', R'), despite those pairs generating the same policy p(R) = p'(R'), and hence being indistinguishable by observation. We've already looked at the normative assumption "stated regret is accurate"; this post will look at more general normative assumptions, and why you'd want to use them to define human (ir)rationality and reward.

Talking it all out

The previous post used "stated reward". This suggests an extension: why restrict to certain human utterances like regret, and why not just use human utterances in general? If we want to know about human values and human rationality, why not ask... humans?

But humans, and I'm sorry if this shocks you, sometimes lie or mislead or tell less than the full truth. We're subject to biases and inconsistencies, and hence our opinions are not a reliable indicator of our values.

Can we not just detect biases and lies, and train a learning agent to ignore or discount them? For example, we could use labelled databases of lies or partial truths, and...

The problem is that a "labelled database of lies and partial truths" is just asking humans again, at a meta level. If we can be misleading at the object level, how can we trust the meta-level assessment ("I am not racist"; "I am telling the truth in the previous statement")? If we use different people to do the speaking and the labelling, then we're just using the biases and utterance of some people as assessments of the biases and utterances of others.

Especially when people&#x27;s values are so under-defined, and biases are both rampant and un-obvious, and we expect meta-level statements to be even more noisy that object level ones.

Let P be the procedure ="take a lot of human statements about values, selected according to some criteria, and a lot of human meta-statements about values and object level statements, do some sort of machine learning on them with some sort of regularisation". In the language of this post, is P something that you would be comfortable to see as the definition of human values?

As definitions go, it certainly seems li...
Problems as dragons and papercuts
by Elo — 2017-11-03T01:42:01.492Z

Original post: http://bearlamp.com.au/problems-as-dragons-and-papercuts/

When I started trying to become the kind of person that can give advice, I went looking for dragons.
I figured if I didn't know the answers that meant the answers were hard, they were big monsters with hidden weak spots that you have to find. "Problem solving is hard", I thought.

Problem solving is not something everyone is good at because problems are hard, beasts of a thing. Right?

For all my searching for problems, I keep coming back to that just not being accurate. Problems are all easy, dumb, simple things. Winning at life is not about taking on the right dragon and finding it's weak spots.

Problem solving is about getting the basics down and dealing with every single, "when I was little I imprinted on not liking chocolate and now I have been an anti-chocolate campaigner for so long for reasons that I have no idea about and now it's time to change that".

It seems like the more I look for dragons and beasts the less I find. And the more problems seem like paper cuts. But it's paper cuts all the way down. Paper cuts that caused you to argue with your best friend in sixth grade, paper cuts that caused you to sneak midnight snacks while everyone was not looking, and eat yourself fat and be mad at yourself. Paper cuts.

I feel like a superhero all dressed up and prepared to fight crime but all the criminals are petty thieves and opportunists that got caught on a bad day. Nothing coordinated, nothing super-villain, and no dragons.

When I was in high school (male with long hair) I used to wear my hair in a pony tail. For about 4 years. Every time I would wake up or my hair would dry I would put my hair in a pony tail. I just did. That's what I would do. One day. One day a girl (who I had not spoken to ever) came up to me and asked me why I did it. To which I did not have an answer. From that day forward I realised I was doing a thing I did not need to do. It's been over 10 years since then and I have that one conversation to thank for changing the way I do that one thing. I never told her.

That one thing. That one thing that is irrelevant, and only really meaningful to you because someone said this one thing, this one time. but from the outside it feels like, "so what". That's what problems are like, and that's w...
Problems as dragons and papercuts
by Elo — 2017-11-03T01:41:53.922Z

Original post: http://bearlamp.com.au/problems-as-dragons-and-papercuts/

When I started trying to become the kind of person that can give advice, I went looking for dragons.

I figured if I didn't know the answers that meant the answers were hard, they were big monsters with hidden weak spots that you have to find. "Problem solving is hard", I thought.

Problem solving is not something everyone is good at because problems are hard, beasts of a thing. Right?

For all my searching for problems, I keep coming back to that just not being accurate. Problems are all easy, dumb, simple things. Winning at life is not about taking on the right dragon and finding it's weak spots.

Problem solving is about getting the basics down and dealing with every single, "when I was little I imprinted on not liking chocolate and now I have been an anti-chocolate campaigner for so long for reasons that I have no idea about and now it's time to change that".

It seems like the more I look for dragons and beasts the less I find. And the more problems seem like paper cuts. But it's paper cuts all the way down. Paper cuts that caused you to argue with your best friend in sixth grade, paper cuts that caused you to sneak midnight snacks while everyone was not looking, and eat yourself fat and be mad at yourself. Paper cuts.

I feel like a superhero all dressed up and prepared to fight crime but all the criminals are petty thieves and opportunists that got caught on a bad day. Nothing coordinated, nothing super-villain, and no dragons.

When I was in high school (male with long hair) I used to wear my hair in a pony tail. For about 4 years. Every time I would wake up or my hair would dry I would put my hair in a pony tail. I just did. That's what I would do. One day. One day a girl (who I had not spoken to ever) came up to me and asked me why I did it. To which I did not have an answer. From that day forward I realised I was doing a thing I did not need to do. It's been over 10 years since then and I have that one conversation to thank for changing the way I do that one thing. I never told her.

That one thing. That one thing that is irrelevant, and only really meaningful to you because someone said this one thing, this one time. but from the outside it feels like, "so what". That's what problems are like...