trentmkelly/LessWrong-43k huggingface dataset:
Acceptance and Commitment Therapy (ACT) 101
by  — 2022-09-25T07:25:39.851Z

I'm interested in (1) hearing from anyone with experience of ACT, (2) if anyone has tried both ACT and other types of CBT and a comparison (especially if you prefer other types of CBT), and (3) evidence for/against ACT.

ACT = Acceptance and Commitment Therapy (pronounced as the word ‘act’ rather than the letters)

CBT = Cognitive Behavioural Therapy

Summary

I have found Acceptance and Commitment Therapy (ACT) much more useful as a framework than other types of CBT.
Traditional CBT focuses on helping you identify and change negative thoughts, whereas ACT focuses on accepting them. It holds that fighting against your emotions usually just leads to being stuck in them.
Other types of CBT often ask “is this thought true?” to encourage behaviour change, whereas ACT uses values to encourage behaviour change (explained better in the full text). ACT could be a good fit for people who are especially values-driven.
ACT has a strong focus on values and mindfulness. Other key ideas:

Psychological flexibility: being in contact with the present moment, fully aware of emotions, and thoughts, welcoming them, including the undesired ones, and moving in a pattern of behaviour in the service of chosen values;
Encouraging gentle curiosity towards thoughts, feelings, and sensations, instead of trying to change them;
The normal thinking process of a healthy human mind will naturally lead to psychological suffering. We have not evolved to be happy, and we are not deficient for experiencing difficult thoughts and feelings;
The goal isn’t to chase happiness or otherwise try and control our internal state.

The six principles of ACT:

Learning the skill of defusing your thoughts and feelings, so they have much less influence over you;
Making room for unpleasant feelings instead of trying to push them away (expansion);
Connecting with whatever you’re doing or experiencing in the present moment;
Becoming familiar with the "observing self," the part of you that experiences, sees, touches, and doesn't judge or take responsibility;
Clarifying and connecting with your values;
Taking action motivated by your values.

This leads to a formula of: Mindfulness + Values + Committed Action = Psychological Flexibility
If you’d like to learn more, I recommend reading the book

The Happiness Trap

, or this

book summary

of it, or watching this

Tedx t

...
Bathroom Construction Cost Comparison
by jefftk — 2022-09-25T02:30:01.436Z

When we

bought our house in
2015 it had one bathroom for our 4br unit. In 2016 I

added a bathroom
upstairs and then in

2019 I
gut-renovated the existing one downstairs. I was thinking back over
these, and I was curious: how did my costs compare on the two
projects?

In both cases I acted as my own general contractor, hiring people for
the plumbing and electrical but otherwise doing the work myself
(with friends and family helping). First, the costs:

Upstairs (2016)
Downstairs (2019)

Plumber
$6,100
$5,826

Electrician
$1,267
$2,651

Fixtures
$823
$1,750

Materials
$861
$1,733

Engineer
n/a
$1,550

Plasterer
$1,000
n/a

Roofer
$700
n/a

Window
n/a
$428

Permits
$247
$103

Other
$658
$381

Total
$11,656
$14,422

Upstairs (2016)

Downstairs (2019)

Even though the costs only differ by ~25% there were a lot of
differences between the projects:

Upstairs the framing was in fine shape, downstairs it was in
terrible shape (a load bearing wall had gone missing...) and I
needed to hire a structural engineer and do serious framing work.

Upstairs I need a new roof vent, downstairs we could hook into
the existing one.

Upstairs the plumber ran a new drain down to the basement,
upstairs they could use the existing one. Except the existing one
needed to be moved to make room for the framing work, so as part of
the project the removed our original cast iron stack and replaced it
with a PVC one.

Upstairs I hired someone to do the drywall finishing;
downstairs I did it myself (and you can tell...)

Downstairs we added a window, and I hired someone for the
exterior work.

Both floors were sheet vinyl inside, but the downstairs work
also included a hardwood floor section outside.

Upstairs we went with a relatively cheap modular shower;
downstairs we did a tub and a reasonably nice surround (partly tile,
which Julia did, and partly modular).

I also haven't included the cost to clean up the mercury we found under the floor during
the first project.

Upstairs is about 50sqft, downstairs 100sqft. This is a case
where per-sqft pricing isn't going to be very useful, though, because
most of the costs weren't proportional to size.

One thing I'm curious about is how much we saved by doing much of the
work ourselves. Looking at estimates I've seen for other work, I
think we might have paid $20k for ...
Prioritizing the Arts in response to AI automation
by Casey — 2022-09-25T02:25:30.728Z

In modern society, many find meaning and fulfillment from their work and careers. I, for one, certainly get enjoyment from a productive day's work.

As a software engineer, I've benefited greatly from GPT-3. I estimate that I'm 5-10 times more productive on a large range of tasks. Beyond predicting lines of code, I actually use GPT-3 as a pseudo-search engine for things I haven't committed to memory. For example, I'll write a comment saying "add entry to database", and GPT-3 will effectively 'look-up' the solution, so I don't have to switch tabs and search it myself. I'm also learning like never before. By prompting GPT-3 via a code comment, I get instant, tailored solutions to my specific problem in new languages or with new tools that I've never used before. This saves me hours of reading general purpose tutorials and debugging to get the working code that I need.

I genuinely feel superhuman, and this boost in productivity lets me focus on more creative aspects of the work (e.g. designing the solution to a problem). In short, I've never found coding so satisfying. Unfortunately, I suspect this is a temporary 'sweet-spot' that won't last forever. Given how powerful the technology already is, with a few months or years of progress I might soon feel like I'm not really contributing to the work at all.

High-school students are using GPT-3 to write essays, and no doubt it's already in use within academia.

As technology automates human labor, history tells us that we'll simply create new jobs in industries and careers not yet imaginable. How could 19th century agriculturalists have foreseen careers in web design? In the case of artificial general intelligence, however, this repeating pattern could be broken. What happens when AI also performs those new jobs better than us?

Will we use all this free time for leisure and enjoyment, or will we struggle to find meaning and fulfillment outside of work? This is not necessarily a new question, for it is exactly the challenge of those who retire (and remain in good health). It is, however, something that we'll need to ask on a larger scale than ever before.

My proposed solution is to promote education and skills in the arts. This will open up creative outlets and hobbies for individuals, which may be essential to maintaining fulfillment and satisfaction in the long-term. Alongside this, one can imagine a reinvigorated pr...
UI/UX From the Dark Ages
by Shmi — 2022-09-25T01:53:48.099Z

(Inspired by a spirited discussion on #lesswrong)

You may not realize it, but our existing UI/UX paradigms are mainly from the 1970s, when human-oriented computing was still in dark ages. Menus, forms, check boxes, search bars, file systems, you name it. They are fine tools, polished by decades of doing the best we could with limited computing power we had, but they are still very much dated. Various attempts to introduce better UX have fallen flat due to limitations of algorithms, memory and compute. Bold attempts like Microsoft Bob and Clippy failed because they made user experience worse, not better.

Things are different now. Natural language processing in limited domains is good enough or nearly good enough to provide an audio- and typed DWIM interface without forcing the user to go through the levels of menus (usually poorly designed by the developers). This is not to replace the menus or the check boxes, but to add another way to do something. Here are some things you might say or type in an ever-present "do box" (not just a "search box"), some of which already sort of work on some gadgets:

"call mom on whatsapp"
"play that song I used to listen to a lot last year"
"turn on the dark theme"
"show me a list of academic articles on ..."
"play the soup nazi Seinfeld episode on the big TV"
"send me an email when someone replies to my comment or post"
"connect wireless headphones I just turned on"
"connect to the public wifi nearby"
"mark me as being on vacation from now till the end of the month"
"open diary entry from ... or the nearest one with discussion of topic X"
"print a black and white copy of this document I am working on"
"insert a link to the wiki entry on UI/UX in this post"

Google Assistant, Siri and ilk can already recognize and interpret many of those, and execute some if asked just right, but it is still an afterthought most of the time, compared to the traditional way to do things. My point is that the technology is good enough now to make a natural language interface a convenient way to do things that require digging through menus and settings, and searching for solutions online. But the UI/UX mindset is still stuck in the old days, and it is basically hit-and-miss.

This is a bit ironic, given that this UI/UX is front and center in sci-fi movies and shows, where, in addition to pressing some weird symbols on a colorful star trek touch pa...
Papers to start getting into NLP-focused alignment research
by Feraidoon — 2022-09-24T23:53:34.010Z

I have recently started working towards a research-focused MSc in AI under the supervision of Dr. Pilehvar and Dr. Soleymani at Sharif University of Technology. (CV, LinkedIn)

Since we essentially get no funding here in Iran, I have ample freedom in choosing what research topics to pursue. What are some interesting papers that are alignment-adjacent in the NLP/transformer space that I can read? I have taken a cursory look at the previously aggregated resources, but the papers there pattern-matched in my brain with non-concrete abstractions that speak in hypotheses (i.e., "philosophy"). I am inclined towards more mainstream/technical works that I can apply to the models we already have. I like capability research, if that matters.

The fields which remind me of alignment:

interpretability

AI ethics

privacy

fairness and biases

out-of-distribution generalization

robustness to adversarial attacks

P.S.: Recent events in Iran might have created novel opportunities for effective altruism. Please take a moment to review the situation if you don't already know the elephant in the room.

P.P.S: I assume I can't apply for any grants because I am an Iranian and thus under sanctions. If you know otherwise, please let me know.

Related:

TAI Safety Bibliography

AI safety starter pack - EA Forum

Resources I send to AI researchers about AI safety - LessWrong

2021 AI Alignment Literature Review and Charity Comparison - LessWrong 2.0 viewer

AI Alignment Research Overview (Oct 2019) by Jacob Steinhardt

AI Alignment Curriculum --- AGI Safety Fundamentals

colah's blog

Information-Theoretic Probing with Minimum Description Length
Whose Fault?
by Markovia — 2022-09-24T23:53:23.795Z

There is an old story that I had read in one of the Upanishads (I can't recall which one exactly), and it describes a situation that goes something like this:

A blind man is walking towards a deep well. There is a guy sitting on a bench nearby and watching him from a distance.

The blind man unaware of the upcoming well, eventually falls into it.

The Upanishad asks the reader: Whose fault is that?

Is it the blind's man fault or the man sitting the bench watching everything and yet doing nothing?

In a simplistic setup such as this one, it is easy to point out that the fault is the man sitting on the bench. His inaction led to a painful event that could have been easily avoided.

The scenario becomes interesting when we try to simulate the exercise in our day-to-day life.

Let me illustrate by taking a hypothetical instance:

There is a reasonably large pothole is in the road in front of your house. You have noticed the pothole and have taken a mental note to ask the concerned authorities to fix it when you have time.

Now, one day, you hear the sound of a bike crash.

Maybe the biker didn't see the pothole, or maybe he was riding irresponsibly, but the bike got into a crash due to the large pothole, and the biker got seriously injured.

Now, let me ask you the question: Whose fault is that?

Is it the the biker?
Is it the concerned government official responsible for the maintenance of the road?
Or is it yours? You, who in the pursuit to maximize your time for saving 10k children in Bangladesh, couldn't find an hour of your time to call up and perform basic civic duties.

It's a fun exercise to take any parable with its simplistic setup and apply it to our complex world setting. Isn't it?

One of the standard maxims of effective altruism is working on the world's most pressing issues that not many people are working on.

And sometimes, that just happens to be right in front of your doorstep.
Brain-over-body biases, and the embodied value problem in AI alignment
by geoffreymiller — 2022-09-24T22:24:40.414Z

Note: This essay was published here on EA Forum on Sept 21, 2022. The description of the brain-over-body biases in the EA subculture may or may not apply to the Rationalist subculture in LessWrong. This essay builds upon this essay on the heterogeneity of human value types.

Overview

Most AI alignment research focuses on aligning AI systems with the human brain’s stated or revealed preferences. However, human bodies include dozens of organs, hundreds of cell types, and thousands of adaptations that can be viewed as having evolved, implicit, biological values, preferences, and priorities. Evolutionary biology and evolutionary medicine routinely analyze our bodies’ biological goals, fitness interests, and homeostatic mechanisms in terms of how they promote survival and reproduction. However the Effective Altruism movement includes some ‘brain-over-body biases’ that often make our brains’ values more salient than our bodies’ values. This can lead to some distortions, blind spots, and failure modes in thinking about AI alignment. In this essay I’ll explore how AI alignment might benefit from thinking more explicitly and carefully about how to model our embodied values.

Context: A bottom-up approach to the diversity of human values worth aligning with

This essay is one in a series that tries to develop an approach to AI alignment that’s more empirically grounded in psychology, medicine, and other behavioral and biological sciences. Typical AI alignment research takes a rather top-down, abstract, domain-general approach to modeling the human values that AI systems are supposed to align with. This often combines consequentialist moral philosophy as a normative framework, machine learning as a technical framework, and rational choice theory as a descriptive framework. In this top-down approach, we don’t really have to worry about the origins, nature, mechanisms, or adaptive functions of any specific values.

My approach is more bottom-up, concrete, and domain-specific. I think we can’t solve the problem of aligning AI systems with human values unless we have a very fine-grained, nitty-gritty, psychologically realistic description of the whole range and depth of human values we’re trying to align with. Even if the top-down approach seems to work, and we think we’ve solved the general problem of AI alignment for any possible human values, we can’t be ...
Opt out from the Funni
by Coafos — 2022-09-24T22:07:38.360Z

Abstract

There are situations, where inaction would lead to an interesting situation, which could go badly if you make a wrong decision. AKA The Funni.

However, sometimes you can take a preemptive action which would lead to a boring situation. You should consider this option more times because it might be better. Hence this post.

Epistemic vibes: this post was made by the opt-out gang.
Disclaimer: I bought "no" on the manifold.

Intro

Imagine the following: a trolly is hurtling towards a fork. You can pull a lever to change paths. If you pull the lever, the trolley will change to an empty track.

But the default track contains the classical 1-5 trolley, where you have to make a high-stakes morally-grey decision in an adrenalin-fueled split-second if you don't pull the first lever.

You know it is morally good to pull the first lever. With cold blood, the choice is completely clear. But that would be booooring, so what if

On Petrov

When your screen shows that five missiles are approaching, and the system is waiting for your answer, it's already late.

And it's not late because you have to follow up on your C. U. T. E. decision theory to make deterrence work. It's not late because you can be a renegade and don't let the world burn.

It's late because there is an option to burn the world.

"idealistic agent"

So you're saying that it would not be a problem for you, because, as far as you know, you will make the right decisions at the right time. And I think it's possible you are right.

However, it won't be you who makes this decision. It will be future you. And future you is a complex agent, they can be hungry or sleepy. They'll have system 1, which can override the right decision. They'll have an inclination to do funni.

That's why you have to protect yourself against these. The you here is plural; it's a very universal human trait. Just remember that in John 8:7 Jesus said:

Let any one of you who's a rational agent be the first to throw a nuke at her.

Summary

What I said, that you should find an option to opt out of a future conflict, only works if you are not currently in that conflict. If the world is moving toward bad state, then you should actively act against it.

Like, if you're reading this, and there is a big red button to do bad, don't do it. But if this red button will only appear in a day or two, then you should probably find a way to disable it.

The good world should be relat...
AI coöperation is more possible than you think
by 423175 — 2022-09-24T21:26:39.977Z

90% of the content of this post is to endorse, in the strongest terms, Schelling's Lecture [transcript], and to note its clear and direct implications for AI coöperation.

When you read arguments about our inability to stop AGI, they sound like arguments about inability to stop nuclear war.

Even Von Neumann believed war was inevitable for game-theoretic reasons—the first to strike suffered less, and the probability of a strike increased to 1 as time went on. How could war not happen—and soon?[1]

AI is expensive

Nuclear weapons are like AI: they are both expensive and this limits the number of actors that can build them. The actors—states, large companies—usually need buy-in, implicit or explicit, and are beholden to shareholders, voters, regulators. Even in autocratic countries, public opinion matters. And even autocratic countries can exhibit a large degree of coöperation with foreign countries (cf. Russian grain exports).

What is the Schelling Point?

Directly applying Schelling's logic, the way to avoid nuclear escalation is to have a bright line, something that is queriable about a model in the same way you can ask the question, "is this military nuclear technology?". What is the line in AI? I don't have the answer here.

There's an obvious candidate. Big. All modern models that have made astonishing progress are big. There are fundamental theorems about the exponential computational difficulty of even specific AI tasks, like playing optimal Go. A highly non-expert observer without direct access to a model can ask, "how big is it?" As long as the answer is truthful, it gives him an idea about how "dangerous" the system is in a way that is hard to work around. It might just not be possible to build dangerous AI systems under a certain scale—or it might be possible only via large systems.

If you feel the urge to comment, it would make me very happy if you proposed other Schelling Points.

Public Opinion

Public opinion was the second driver of Schelling's argument. Good news on that front. How does the average person feel about AI? Bad.

We've got a skewed view, a lot more positive than the average person, and more positive than we think, for much the same reasons that we tend to have more positive views about science/medicine/technology—well explained in Ivermectin: Much More than You Wanted to Know.

It's hard to get numbers, but Pew is a start. Would it surprise you...
"Cotton Gin" AI Risk
by 423175 — 2022-09-24T21:26:39.849Z

Most concerns about AI tend to boil down to:

Loss of control to AI systems - What if AI were smarter than us and took over the world?
Concentration of power - What if AI gave too much power to someone bad?

I'm surprised I haven't heard consideration of a third, more basic risk.

Will this technology be good?

Suppose you're in the Southern United States in 1793 and you believe that an important moral question—perhaps the most important moral question—is labor ethics of how cotton is processed. I suspect I don't need to go into detail about why you might think this.

Proceeding directly from this belief, an obviously good thing is, what if a machine could process cotton instead of people? Then at least the people who processed cotton wouldn't have to anymore.[1]

Imagine you work hard and, through grit and luck, it works!

What is your confidence interval of how much better this makes life?

I hope your interval included negative numbers. For some reason, I never hear negative numbers for how much better life would be if AI could do lots of jobs for us.

This is in fact exactly what happened. Eli Whitney tried to reduce enslaved labor by creating a replacement machine, but it worked backward.[2]

Isn't this "centralization of power"?

No,

The gains from the gin were no more centralized than previous production surplus
The problem wasn't its effect on processing. It was the indirect effect on cotton growing. And that didn't change at all in centralization.
It would hold true regardless of centralization. The problem wasn't centralization, it was more cotton growing.

What can AI do that is bad?

I don't have clear answers. But the cotton gin should be enough of a cautionary tale about economics and unintended consequences.

A start is "tricking people". The central motive of all economic activity is to modify human behavior, usually involving a step where they give you money. Training a net costs money. How will you make that money back? The net will help you change people's behavior to give you their money. Not every way to change someone's behavior is good.

Another angle is "social change". If there's an invention that turns dirty water into clean water cheaper, it can change the math of economic activity and that can bubble up to have indirect social changes. AI is more direct. Its main successes have been text and image: abstract goods whose sole purpose is to feed directly into p...