trentmkelly/LessWrong-43k huggingface dataset:
Tesla Model 3 Review
by jefftk — 2023-01-17T01:10:01.582Z

This weekend I was in San Luis Obispo for

a gig, about halfway between
SF and LA. It's possible to fly into

SBP,
but since I was

traveling with
two of my kids it was a lot cheaper to fly into SFO and drive down,
and only slightly slower.

I'm signed up with Hertz's reward program ("Gold") and
one of the benefits is that you pick
out your own car. When I got to SFO, there were several Tesla
Model 3s in the "Gold" area. This was somewhat surprising—I had
only paid for a small sedan ("B") and the Teslas are fancy
("E7")—but it seemed like it would be interesting to try one out
and I liked the idea of not paying for gas. I got us loaded up but
when I got to the exit the attendant didn't believe I'd gotten the car
from the designated area, and said it would be a $50/day upgrade. I
went back to the area, identified an apparently identical Model 3, and
asked if I could have that one. They said yes, I moved kids and
luggage over, and we were off.

I forgot to take a picture of the car—what sort of review is
this?—but here's a picture of my kids enjoying the best seats on
the SFO people mover.

This was my first time driving an electric car and the first thing I
noticed was lifting your foot off the accelerator is very
different. In a gas car you coast, slowing down a little from engine
braking, but apparently in EVs you get regenerative braking. There's
a sense in which this doesn't matter, and is just a question of where
to put the "coast" point—at no pedal vs pushing down a
little—but it doesn't immediately seem better to me.

The first evening was a short drive to San Jose. Getting out of the
car, it was not obvious how to turn it off. Reading online later I
learned that all you do is walk away, which is nice and automatic.
But you'd only know if someone told you or you looked it up, and late
at night after a cross country flight with two tired kids while poking
at unfamiliar menu options on the dashboard tablet I was pretty
frustrated with their minimally discoverable approach.

The next morning I was looking for somewhere adjacent to a charging
location to get breakfast along my route. This seems like something
the built-in navigation should help with; charge + activity seems like
a common kind of goal. Unfortunately, it would only let me search for
one thing at a time. Google Maps on my phone was better, letting me
search for '...
Should AI writers be prohibited in education?
by Eleni Angelou — 2023-01-17T00:42:56.999Z

Crossposted from the EA Forum: https://forum.effectivealtruism.org/posts/yNitwYkHP6DtkkSrG/should-ai-writers-be-prohibited-in-education

Note: this is an attempt to engage with and interpret legislation on the usage of AI. I don't have a strong opinion on this yet and expect it to be controversial which is why I preferred the Question Mode.

In the AI Act, i.e., the EU's regulatory framework for the usage of AI-related technologies it is mentioned that

The following artificial intelligence practices shall be prohibited:
the placing on the market, putting into service or use of an AI system that
exploits any of the vulnerabilities of a specific group of persons due to their
age, physical or mental disability, in order to materially distort the behaviour of
a person pertaining to that group in a manner that causes or is likely to cause
that person or another person physical or psychological harm.

Title II, Article 5, p. 43 (English Version).

I'll set up one interpretation of this statement in debate form:

Question: should AI writers be prohibited in education?

Claim: we can stretch this statement to apply to the usage of AI writing products employed by underage students for their assignments. This technology exploits students' inability to make a fully-informed and thoughtful decision as to what would be beneficial for their intellectual development and education. Therefore, the practice should be prohibited.

Counterclaim: the AI system is not exploiting anyone's vulnerability as the notion of vulnerability should not be considered to entail one's proneness to dishonesty or cheating behaviors. Therefore, AI writers should not be prohibited and students should be held accountable for cheating when using AI writing models to compose their assignments.

Feel free to continue the debate in the comments section.
What can thought-experiments do?
by Cleo Nardo — 2023-01-17T00:35:17.074Z

Introduction

What's the difference between actually being in a situation and just thinking about the situation? In other words, what's the difference between a real-life ethical dilemma and a hypothetical ethical dilemma?

There are many differences.

Some differences are phenomenological. A real-life dilemma feels very different from a hypothetical dilemma.
Some differences are decision-theoretic. For example, the action-space of the real-life dilemma isn't isomorphic to the action-space of the hypothetical dilemma.
Some differences are cognitive. There are particular cognitive processes/algorithms that can be used to solve real-life dilemmas that can't be used to solve hypothetical dilemmas. And vice-versa.
Some differences are social. The social norms governing real-life dilemmas differ from those governing hypothetical dilemmas.
E.t.c, e.t.c.

In this post, I'll discuss two decision-theoretic differences, and I'll reach this conclusion:

For almost every real-life dilemma, there will not exist a hypothetical dilemma which has the same decision-theoretic properties as the real-life dilemma.

In subsequent posts, I might discuss other differences, and I expect to reach these conclusions:

Many people underestimate the difference between hypothetical dilemmas and real-life dilemmas.
Often people should replace thinking about hypothetical dilemmas with thinking about corresponding real-life dilemmas (especially for ethics, decision theory, and LessWrong).

What counts as a decision-theoretic difference?

A good hypothetical dilemma should capture all the decision-theoretic properties of the real-life dilemma. Here's what I mean:

Suppose Alice is faced with a real-life dilemma — she sees a child drowning in a pond, but saving the child would ruin her expensive shoes. So Alice has two options: save the child, or leave the child.

And suppose Bob is faced with the corresponding hypothetical dilemma: "you see a child drowning, but saving the child would ruin your expensive shoes." Bob has two options: hypothetically save the child, or hypothetically leave the child.

This is a faithful hypothetical dilemma if and only if Bob's decision is decision-theoretically equivalent to Alice's. In formal terms, there must exist an order-preserving isomorphism between Alice's options and Bob's options.

But this is rarely the case. I'll' explain two ways that Bob's decision differs from Alice's.

1. Bob'

...
Experiment Idea: RL Agents Evading Learned Shutdownability
by Leon Lang — 2023-01-16T22:46:03.403Z
Link: https://docs.google.com/document/d/1ZvI2nEWYE4C_NfoR1jBG-LzlBwqI-mlqDIDfVlfIqdU/edit#heading=h.sqnn8usa4l7k

Preface

Produced as part of the

SERI ML Alignment Theory Scholars Program

- Winter 2022 Cohort. Thanks to

Erik Jenner

who explained to me the basic intuition for why an advanced RL agent may evade the discussed corrigibility measure. I also thank

Alex Turner

,

Magdalena Wache

, and Walter Laurito for detailed feedback on the proposal and

Quintin Pope

and

Lisa Thiergart

for helpful feedback in the last December SERI-MATS shard theory group meeting.

This text was part of my deliverable for the

shard theory

stream of SERI-MATS. In it, I present an idea for an experiment that tests the convergent drive of modern model-based RL agents to evade shutdownability. If successful, I expect the project could serve as a means to communicate the problem of corrigibility to the machine learning community. As such, I also consider this project idea a submission of the

Shutdown Problem Contest

.

I do not personally want to work on the project since doing experiments does not seem like my comparative advantage. Thus, with posting this project, I mainly seek collaborators and feedback. More on that in the conclusion.

Introduction

At some point in the future, we will train very advanced AI, possibly by some version of model-based reinforcement learning. Since it is hard to correctly

specify the reward function

or

steer the inner learning dynamics of the agent

, it may be desirable to make sure that the agent is

corrigible

, including shutdownability:

“(1) A corrigible reasoner must at least tolerate and preferably assist the programmers in their attempts to alter or turn off the system.”

Next to a literal shutdown button, one could also try to use the inner functions of the agent to effectively get the ability to shut it down. The idea would be to design a certain type of input such that, as a reaction to that input, a computation in the agent itself will cause it to perform a null action that doesn’t do anything — which effectively equates to a shutdown. Scott Aaronson proposed this idea

in a recent talk

(timestamp: 57:10) in the form of a planted cryptographic backdoor, an idea he currently works on during his

sabbatical at OpenAI

.

For this proposal, I consider a variation of that shutdown approach: instead of directly “planting” the shutdown behavior, I consider the possibility to train the b...
Consequentialists: One-Way Pattern Traps
by David Udell — 2023-01-16T20:48:56.967Z

Generated during MATS 2.1.

A distillation of my understanding of Eliezer-consequentialism.

Thanks to Jeremy Gillen, Ben Goodman, Paul Colognese, Daniel Kokotajlo, Scott Viteri, Peter Barnett, Garrett Baker, and Olivia Jimenez for discussion and/or feedback; to Eliezer Yudkowsky for briefly chatting about relevant bits in planecrash; to Quintin Pope for causally significant conversation;[1] and to many others that I've bounced my thoughts on this topic off of.

Introduction

What is Eliezer-consequentialism? In a nutshell, I think it's the way that some physical structures monotonically accumulate patterns in the world. Some of these patterns afford influence over other patterns, and some physical structures monotonically accumulate patterns-that-matter in particular -- resources. We call such a resource accumulator a consequentialist -- or, equivalently, an "agent," an "intelligence," etc.

A consequentialist understood in this way is (1) a coherent profile of reflexes (a set of behavioral reflexes that together monotonically take in resources) plus (2) an inventory (some place where accumulated resources can be stored with better than background-chance reliability.)

Note that an Eliezer-consequentialist is not necessarily a consequentialist in the normative ethics sense of the term. By consequentialists we'll just mean agents, including wholly amoral agents. I'll freely use the terms 'consequentialism' and 'consequentialist' henceforth with this meaning, without fretting any more about this confusion.

Path to Impact

I noticed hanging around the MATS London office that even full-time alignment researchers disagree quite a bit about what consequentialism involves. I'm betting here that my Eliezer-model is good enough that I've understood his ideas on the topic better than many others have, and can concisely communicate this better understanding.

Since most of the possible positive impact of this effort lives in the fat tail of outcomes where it makes a lot of Eliezerisms click for a lot of alignment workers, I'll make this an effortpost.

The Ideas to be Clarified

I've noticed that Eliezer seems to think the von Neumann-Morgenstern (VNM) theorem is obviously far reaching in a way that few others do.

Understand the concept of VNM rationality, which I recommend learning from the Wikipedia article... Von Neumann and Morgenstern showed that any agent obeying a few simple co

...
Book Review: Worlds of Flow
by remember — 2023-01-16T20:17:16.022Z

This work was written at Conjecture.

“Worlds of Flow,” a history of 19th and early 20th-century hydrodynamics by Oliver Darrigol, concludes:

What distinguishes the history of hydrodynamics from that of other physical theories is not so much the tremendous effect of challenges from phenomenal worlds, but rather it is the slowness with which these challenges were successfully met. Nearly two centuries elapsed between the first formulation of the fundamental equations of the theory and the deductions of laws of fluid resistance in the most important case of large Reynolds numbers…The reasons for this extraordinary delay are easily identified a posteriori. They are the infinite number of degrees of freedom and the nonlinear character of the fundamental equations, both of which present formidable obstacles to obtaining solutions in concrete cases. Moreover, instability often deprives the few known exact solutions of any physical relevance…

These difficulties have barred progress along purely mathematical lines. They have also made physical intuition a poor guide, and a source of numerous paradoxes. Hydrodynamicists therefore sought inspiration in concrete phenomena. Engagement with and challenges from the real worlds of flow were essential to the development of the above-mentioned strategies. The challenged theorists strove to find new solutions and to develop new methods of approximation. Experience indicated some general properties of the motion, such as the existence of boundary layers, the random character of turbulence, the sudden character of the Reynolds transition, or the formation of trailing vortices…Altogether, there were many ways in which practical concerns oriented theorists in the conceptual maze of fluid dynamics. The evolution from a paper theory to an engineering tool thus depended on transgressions of the limits between academic hydrodynamics and applied hydrodynamics.

This quote captures one of the most significant lessons in the book: the study of concrete phenomena was critical in overcoming many of the difficulties in hydrodynamics. Roughly two upstream problems required interacting with concrete phenomena to solve. The first is summarized nicely by the quote above: theorizing and abstract thinking alone was not enough to solve the problems posed by hydrodynamics. The second is a subtler point: early mathematical and theoretical tools wer...
For the Record: DL ∩ ASI = ∅
by  — 2023-01-16T19:04:10.907Z

Disclaimer: This post isn't intended to convince or bring anyone closer to a certain position on AI. It is merely - as the title suggests - for the record.

I would like to publicly record my prediction about the prospects of artificial superintelligence, consisting of a weak and a strong thesis:

Weak thesis: Current deep learning paradigms will not be sufficient to create an artificial superintelligence.

You could call this the Anti-"scaling-maximalist"-thesis, except that it goes quite a bit further by including possible future deep leaning architectures. Of course, "deep learning" is doing a lot of work here, but as a rule of thumb, I would consider a new architecture fits within the DL paradigm if it involves a very large number (at least in the millions) of randomly initialized parameters that are organized into largely uniform layers and are updated via a simple algorithm like backpropagation.

I intentionally use the word "superintelligence" here because "AGI" or "human-level intelligence" have become rather loaded terms, the definitions of which are frequently a point of contention. I take superintelligence to mean an entity so obviously powerful and impressive in its accomplishments that all debates around its superhuman nature should be settled instantly. Feats like building a Dyson Sphere, launching intergalactic colony ships at 0.9c, designing and deploying nanobots that eat the whole biosphere etc. Stuff like passing the Turing Test or Level 5 self-driving decidedly do not qualify (not that I think these challenges will be easy; but I want to make the demarcation blatantly clear).

(the downside is that we may never live to witness such an ASI in case it turns out to be UnFriendly, but by then earning some reputation points on the internet will be the least of my concerns)

Strong thesis: If and when the first ASI is built, it will not use deep learning as one of its components.

For instance, if the ASI uses a few CNN-layers to pre-process visual inputs, or some autoencoder system to distill data into latent variables, that's already enough to refute the strong thesis. On the other hand, merely running on hardware that was design-assisted by DL-systems does not disqualify the ASI from being DL-free.

For future reference, here is some context this prediction was made in:

It is the beginning of 2023, 1.5 months after the release of chat...
What determines female romantic "market value"?
by anon_girl — 2023-01-16T18:45:36.436Z

There had been multiple conversations on this website about what makes men attractive to women, how can men improve along those axes, et cetera (example). However, AFAICT there were few discussions of what makes women attractive to men. (It can't be just about looks, right? Right??) The men reading this website are probably not representative of the overall population, but this bias is positively correlated with the kind of men I'm interested in, so as far as I'm concerned it's not a problem. Among other things, I'm interested to understand how age factors into the equation (I'm middle-aged).
Status conscious
by avantika.mehra — 2023-01-16T17:44:18.758Z

There is something off about the sky. Strange colours streak the horizon at sunset – just subtly enough that you wouldn’t notice unless you looked — and the stars that roam the night sky are doing so off cadence. A certain rhythm seems to have jolted. But it’s possible I am hallucinating; that the apparently transforming elements are nothing more than the imminent effects of War on a simple mind.

I used to look at the stars, 86 billion sparkling orbs, to feel awe, magic. In a radically inconsistent world they are the only things I know to be true. But today they loom large and sinister, and I begin to wonder which one of them the assailants call home. It is impossible not to think of them everyday; of the alien souls that found themselves among us, and continued to cripple our kind. We realised, almost too late, that their intentions were nefarious — but since then, we’ve fought long, and we’ve fought hard.

And now, we’ve won the war; we’re healing.

*** At a higher scale of time and space, separated by a few layers of biological boundary ***

Leia’s head pounded. Beads of sweat dotted her face as she rocked back and forth, as if trying to expel the sickness from her body. Unable to produce material change with either intense focus or Vedantic breathwork, she lay quiet, resigned, and stared at the single sunflower perched on her bedside. The seeds in its center swirled in spirals, as if trying to escape from the flower’s center; she wondered what it would take for them to escape from their cyclical, bounded universe.

“Knock knock!” Leia was jolted to reality as Doctor Q. Rius’s smiling face popped around the door. “May I come in?”

She nodded weakly and Q entered. “Good news — it is slowly receding from the brain.”

She sighed, “Slowly.”

“This virus is unlike any we have seen before — we’re learning more about it every day.”

“I understand.”

Q turned to leave, but Leia said, “If it’s alright — a personal question?”

“Yes?”

“You’re here without PPE… you’re infected with the virus as well?”

Wistfully, he nodded. “I caught it yesterday. There’s no onset of symptoms yet, so I’m here, working.”

She said, “I’m sorry,” and then, “Are you able to talk for a bit? I’ve been struggling to process this sickness.”

“Of course,” said Q, and sat down on the wooden chair next to Leia’s bed. “How can I help?”

She began: “I’m always so sick… I feel like there’s a hundred wars being fough...
Confusing the ideal for the necessary
by adamShimi — 2023-01-16T17:29:06.932Z
Link: https://epistemologicalvigilance.substack.com/p/confusing-the-ideal-for-the-necessary

I had many meetings that day, and a lot of managing issues to attend, so I found myself thinking “I just can’t get any research done today”.

It was not the first time I had thought that thought; but it might have been the first time I applied my main epistemologist’s tool to it: I asked “Why?” For I did have time to work, not that much, yes, splintered, yes, but enough to make progress.

So why was I discarding the very possibility of making progress and working on my research?

Because I had internalized a false requirement: that I needed large chunks of time with no distractions to do research. That it was a precondition to me doing anything worth my time, and so investing little pockets of time here and there was a mistake.

Of course, long sessions of deep work are reliably more productive than 15 minute sprints peppered through a day of meeting. It’s a reliable and reproducible finding, and I’ve experienced it again and again in my own life.

Yet the point here is different. Instead of simply recognizing my lack of ideal condition, and deciding whether it was still worth it for me to do research despite the discrepancy, I automatically discarded the possibility of doing research. I turned ideal conditions into necessary conditions.

And it’s even worse than that. Because I could not even consider doing research despite distractions, I never exercised this specific attention muscle. I never trained myself to go back quickly and smoothly to my train of thought after an interruption. Which means that when I had to make progress despite the constraints and distractions (for example when I had both an important research deadline and documentation/posts to write), my research suffered far more than it needed to because I was not trained to get the best out of the little time I had.

Which naturally leads to the more disturbing question: how many instances of this kind of thinking am I not noticing? How much am I costing myself by subscribing to necessary conditions that aren’t really necessary, just ideal?
Tyler Cowen AMA on the Progress Forum
by jasoncrawford — 2023-01-16T17:23:16.990Z
Link: https://progressforum.org/posts/3aNLznQiLuyTKMhpH/tyler-cowen-ama

The inimitable Tyler Cowen—chairman of the Mercatus Center at GMU and (co-)author of the blog Marginal Revolution, the book The Great Stagnation, and the 2019 article in The Atlantic that coined the term “progress studies”—is doing an AMA (Ask Me Anything) on the Progress Forum.

Get your questions in now, and upvote the ones you want to see answered. He’ll start answering tomorrow (Tuesday, Jan 17).

After you’re done, check out our previous AMA with Patrick McKenzie.