trentmkelly/LessWrong-43k huggingface dataset:
PauseAI and E/Acc Should Switch Sides
by WillPetillo — 2025-04-01T23:25:51.265Z

In the debate over AI development, two movements stand as opposites: PauseAI calls for slowing down AI progress, and e/acc (effective accelerationism) calls for rapid advancement. But what if both sides are working against their own stated interests? What if the most rational strategy for each would be to adopt the other's tactics—if not their ultimate goals?

AI development speed ultimately comes down to policy decisions, which are themselves downstream of public opinion. No matter how compelling technical arguments might be on either side, widespread sentiment will determine what regulations are politically viable.

Public opinion is most powerfully mobilized against technologies following visible disasters. Consider nuclear power: despite being statistically safer than fossil fuels, its development has been stagnant for decades. Why? Not because of environmental activists, but because of Chernobyl, Three Mile Island, and Fukushima. These disasters produce visceral public reactions that statistics cannot overcome. Just as people fear flying more than driving despite the latter being far more dangerous, catastrophic events shape policy regardless of their statistical rarity.

Any e/acc advocate with a time horizon extending beyond the next fiscal quarter should recognize that the most robust path to sustained, long-term AI acceleration requires implementing reasonable safety measures immediately. By temporarily accepting measured caution now, accelerationists could prevent a post-catastrophe scenario where public fear triggers an open-ended, comprehensive slowdown that might last decades. Rushing headlong into development without guardrails virtually guarantees the major "warning shot" that would permanently turn public sentiment against rapid AI advancement in the way that accidents like Chernobyl turned public sentiment against nuclear power.

Meanwhile, the biggest dangers from superintelligent AI—proxy gaming, deception, and recursive self-improvement—won't show clear evidence until it's too late. AI safety work focusing on current harms (hallucination, complicity with malicious use, saying politically incorrect things, etc.) fails to address the fundamental alignment problems with ASI. These problems may take decades to solve—if they're solvable at all. This becomes even more co...
Building Communities Beyond the Bay
by Lucie Philippon — 2025-04-01T22:07:16.288Z

During DunCon 2025, I run a community building strategy workshop with @Screwtape. Going through the workshop gave me great insights into what I actually wanted out of my community and how to get there, so I figured sharing the session plan could be useful. If you end up following this plan, consider telling me whether it was useful!

Workshop plan

1-Hour Workshop Plan for DunCon 2025

Introduction (5 minutes)

Welcome and context about organizers
Concept: "Humans are not automatically strategic" - we don't naturally take time to think deeply about our goals and plans
Today we'll engage in deliberate, manual strategic thinking about our local communities

Workshop Flow: Manual Strategic Thinking (40 minutes)

Step 1: What Do We Actually Want? (10 minutes)

Prompts:

What specific elements from DunCon do you wish existed locally?
What's missing from your community that you value most?
If your local community were thriving in 5 years, what would it look like?
What does the perfect, S-tier success where your wildest dreams came true look like?

Step 2: Get Specific About Goals (10 minutes)

Prompts:

Drill down on your vision - what specifically would indicate success?
What's a realistic intermediate objective given your constraints?
What's your MVP version that could be achieved in 1-3 months?
What's a hard-to-fake, concrete thing you could measure? (Beware goodharting!)

Step 3: Strategic Planning (10 minutes)

Prompts:

What are 2-3 concrete steps that would move you toward your goal?
What obstacles will you likely encounter and how might you address them?
What resources and allies are available to you?
What could help you stay motivated?

Step 4: Execute First Steps (10 minutes)

Prompts:

Now we'll take the unusual step of actually implementing our first actions
Use this time to send messages, create events, or set up what you need
Don't let perfect be the enemy of done - take real action now

Participants actively complete their first actions during this time:

Write the 2~3 sentence version of the plan and share it.
Sending messages to potential collaborators
Setting up calendar events or Doodle polls
Creating Discord channels or communication groups
Scheduling follow-up calls
Drafting announcements or invitations

Conclusion (5 minutes)

Staying connected after DunCon?

The Rationality Meetup Discord server is a great place to connect with other community builders.

Facilitator Notes

Encourage depth rather than bread

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Introducing WAIT to Save Humanity
by carterallen — 2025-04-01T21:47:17.857Z

The EA/rationality community has struggled to identify robust interventions for mitigating existential risks from advanced artificial intelligence. In this post, I identify a new strategy for delaying the development of advanced AI while saving lives roughly 2.2 million times [-5 times, 180 billion times] as cost-effectively as leading global health interventions, known as the WAIT (Wasting AI researchers' Time) Initiative. This post will discuss the advantages of WAITing, highlight early efforts to WAIT, and address several common questions.

early logo draft courtesy of claude

Theory of Change

Our high-level goal is to systematically divert AI researchers' attention away from advancing capabilities towards more mundane and time-consuming activities. This approach simultaneously (a) buys AI safety researchers time to develop more comprehensive alignment plans while also (b) directly saving millions of life-years in expectation (see our cost-effectiveness analysis below). Some examples of early interventions we're piloting include:

Bureaucratic Enhancement: Increasing administrative burden through strategic partnerships with university IRB committees and grant funding organizations. We considered further coordinating with editorial boards at academic journals but to our surprise they seem to have already enacted all of our protocol recommendations.
Militant Podcasting: Inviting leading researchers at top AI organization to come onto podcasts with enticing names like "Silicon Savants" and "IQ Infinity", ensuring each recording runs 4+ hours and requires multiple re-recordings due to technical difficulties.
Conference Question Maximization: We plan to deploy trained operatives to ask rambling, multi-part questions during Q&A sessions at leading ML conferences that begin with "This is more of a comment than a question..." and proceed until their microphones are snatched away.
Twitter/X Stupidity Farming: Our novel bots have been trained to post algorithmically optimized online discourse that consistently confuses the map for the territory. Also they won't shut up about Elon and "sexual marketplace dynamics" but apparently there is no limit to how long everyone will find these topics interesting for.
Romantic Partnership Engineering (RPE): Bay area researchers are uniquely receptive to polyamory and other relationship structures requiring increased communicatio

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You will crash your car in front of my house within the next week
by Richard Korzekwa  — 2025-04-01T21:43:21.472Z

I'm not writing this to alarm anyone, but it would be irresponsible not to report on something this important. On current trends, every car will be crashed in front of my house within the next week. Here's the data:

Until today, only two cars had crashed in front of my house, several months apart, during the 15 months I have lived here. But a few hours ago it happened again, mere weeks from the previous crash. This graph may look harmless enough, but now consider the frequency of crashes this implies over time:

The car crash singularity will occur in the early morning hours of Monday, April 7. As crash frequency approaches infinity, every car will be involved. You might be thinking that the same car could be involved in multiple crashes. This is true! But the same car can only withstand a finite number of crashes before it is no longer able to move. It follows that every car will be involved in at least one crash. And who do you think will be driving your car?
The Case For Geopolitical Financial Speculation
by prue — 2025-04-01T21:09:17.515Z
Link: https://www.prue0.com/2025/03/30/the-case-for-geopolitical-financial-speculation/

By the time you finish reading this essay, at least one nation somewhere on Earth will have moved incrementally closer to crisis. Perhaps a central bank will have depleted its foreign reserves defending an unsustainable currency peg. Maybe a pension system will have slipped deeper into actuarial insolvency as another cohort reaches retirement age. Or possibly a political system will have inched closer to fragmentation as polarization intensifies.

We have sophisticated financial instruments to express views on nearly everything: corporate earnings, commodity prices, interest rate movements, all the way to the weather. Yet our ability to directly take positions on the trajectories of entire nations, particularly negative positions, remains surprisingly limited and fragmented.

As with all things, markets will push towards exploration, and our view is the development of comprehensive geopolitical financial instruments is not only inevitable but potentially beneficial for global stability, if properly designed and regulated.

I. The Missing Market

In October 2008, as Iceland’s banking system imploded, traders who had shorted the krona reaped enormous gains. They had identified classic vulnerability indicators: banking assets exceeding 1,000% of GDP, 80% of debt denominated in foreign currencies, a 15% current account deficit, and foreign exchange reserves covering just 30% of short-term debt. When crisis struck, the krona lost over half its value against the euro.

Historical data from the IMF reveals the frequency and patterns of sovereign debt crises across nations. Between 1970 and 2002, countries like Argentina, Brazil, and Peru experienced multiple debt crises, with some remaining in crisis for over a decade (see Figure 1).

Figure 1

This episode hints at what’s possible when financial markets enable direct bets against vulnerable sovereigns. But Iceland represented a limited case with traders primarily shorting its currency rather than taking comprehensive positions against the nation’s economic prospects. The tools for more holistic sovereign shorting remain underdeveloped.

Why does this market gap persist? The answer lies at the intersection of financial innovation, political sensitivity, and moral hazard.

Taking a negative position on a company is controversial enough; betting against an entire nation, with all the human consequences that entails, crosses boundaries...
VDT: a solution to decision theory
by L Rudolf L — 2025-04-01T21:04:09.509Z

Introduction

Decision theory is about how to behave rationally under conditions of uncertainty, especially if this uncertainty involves being acausally blackmailed and/or gaslit by alien superintelligent basilisks.

Decision theory has found numerous practical applications, including proving the existence of God and generating endless LessWrong comments since the beginning of time.

However, despite the apparent simplicity of "just choose the best action", no comprehensive decision theory that resolves all decision theory dilemmas has yet been formalized. This paper at long last resolves this dilemma, by introducing a new decision theory: VDT.

Decision theory problems and existing theories

Some common existing decision theories are:

Causal Decision Theory (CDT): select the action that *causes* the best outcome.
Evidential Decision Theory (EDT): select the action that you would be happiest to learn that you had taken.
Functional Decision Theory (FDT): select the action output by the function such that if you take decisions by this function you get the best outcome.

Here is a list of dilemmas in decision theory that have vexed at least one of the above decision theories:

Newcomb's problem: a superintelligent predictor, Omega, gives you two boxes. Box A is transparent and has $1000. Box B is opaque and has $1M if Omega predicts you would pick only Box B, and otherwise empty. Do you take just Box B, or Box A and Box B?

CDT two-boxes and misses out on $999k.

Smoking lesion: people with a certain genetically-caused lesion tend to smoke and develop cancer, but smoking does not cause cancer (this thought experiment is sponsored by Philip Morris International). You enjoy smoking and don't know if you have the lesion. Should you smoke?

EDT says you shouldn't smoke, because that's evidence you have the lesion.

Parfit's hitchhiker: you're stranded in a desert without money trying to get back to your apartment, and a telepathic taxi driver goes past, but will only save you if they predict you'll actually bring back $100 from your apartment once they've driven you home. Do you commit to paying?

CDT decides, upon arriving in the apartment, to not pay the taxi driver, and therefore leaves you stranded.

Counterfactual mugging: another superintelligent predictor (also called Omega because there aren't very many baby name books for superintelligent predictors), flips a fair coin. If the coin la

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Calculus is about change
by dkl9 — 2025-04-01T19:44:43.453Z
Link: https://dkl9.net/essays/calculus_change.html

This is a joke taken too far, especially given that I am thoroughly educated in only a minority of these subjects.

Maths

Calculus is about change. Statistics is about variation. Linear Algebra is about vectors. Multivariable Calculus is about the chain rule. Differential Equations is about initial conditions. Topology is about boundaries. Complex Analysis is about local isotropy.

Hard sciences

Classical Physics is about energy. Quantum Physics is about amplitudes. Astronomy is about gravity. Inorganic Chemistry is about charge. Organic Chemistry is about groups. Botany is about seeds. Zoology is about predation. Neuroscience is about stimuli.

Social sciences

Economics is about demand. Linguistics is about compression. Psychology is about habits. Law is about incentives.

Miscellaneous

Finance is about arbitrage. Marketing is about preferences. Agriculture is about growth. Computer Science is about precision. Journalism is about description.
The Ghibli Event: Our First Glimpse of Reality Transfer
by BazingaBoy — 2025-04-01T19:43:24.314Z

Something entirely new occurred around March 26th, 2025. Following the release of OpenAI’s 4o image generation, a specific aesthetic didn’t just trend—it swept across the virtual landscape like a tidal wave. Scroll through timelines, and nearly every image, every meme, every shared moment seemed spontaneously re-rendered in the unmistakable style of Studio Ghibli. This wasn’t just another filter; it felt like a collective, joyful migration into an alternate visual reality.

But why? Why this specific style? And what deeper cognitive or technological threshold did we just cross? The Ghiblification wave wasn’t mere novelty; it was, I propose, the first widely experienced instance of successful reality transfer: the mapping of our complex, nuanced reality into a fundamentally different, yet equally coherent and emotionally resonant, representational framework.

And Ghibli, it turns out, was uniquely suited to be our first portal.

The Necessary Magic: Conditions for Reality Transfer

I posit that for reality transfer to succeed, two seemingly contradictory conditions must be met:

High Transformativeness: The target style must be radically different from photorealism. It cannot merely be a stylization of our world. It needs to feel like stepping into a distinct ontology, a place with its own internal logic and aesthetic laws. Attempting this transfer using, say, the Art Deco stylings of Tamara de Lempicka wouldn’t achieve this sensation. Her work, while highly stylized, remains too close to representational reality; it feels like seeing our world through a specific lens, not entering a new one entirely.
High Fidelity of Nuance: The target style must possess a sufficiently rich and expressive “vocabulary” to capture the essential details, relationships, and emotional subtleties of the original input. The transformation, while drastic, cannot be a crude flattening. We must still recognize the core essence of the original – the specific curve of a smile, the implied weight of an object, the tension in a posture – even as it’s translated into the new aesthetic language. This fidelity allows us to map our understanding and emotional connection onto the transformed output, bridging the gap between worlds.

Ghibli’s style excels spectacularly at both. Its aesthetic is deeply transformative: the impossibly rounded forms, the enchanting color palettes conve...
Leverage, Exit Costs, and Anger: Re-examining Why We Explode at Home, Not at Work
by at_the_zoo — 2025-04-01T18:28:26.611Z

Let's cut through the comforting narratives and examine a common behavioral pattern with a sharper lens: the stark difference between how anger is managed in professional settings versus domestic ones. Many individuals can navigate challenging workplace interactions with remarkable restraint, only to unleash significant anger or frustration at home shortly after. Why does this disparity exist?

Common psychological explanations trot out concepts like "stress spillover," "ego depletion," or the home being a "safe space" for authentic emotions. While these factors might play a role, they feel like half-truths—neatly packaged but ultimately failing to explain the targeted nature and intensity of anger displayed at home. This analysis proposes a more unsentimental approach, rooted in evolutionary biology, game theory, and behavioral science: leverage and exit costs. The real question isn’t just why we explode at home—it’s why we so carefully avoid doing so elsewhere.

The Logic of Restraint: Low Leverage in Low-Exit-Cost Environments

Consider the workplace. Throwing a tantrum over an inconvenience can quickly result in termination, HR complaints, or social ostracization. The "exit cost" for others is low—they can easily remove or sideline you. In this environment, self-regulation isn't just admirable; it's necessary. Anger, particularly explosive anger, is a liability. People instinctively or consciously adapt, recognizing that overt hostility carries high risks and few rewards. Compliance and emotional suppression are simply the smarter moves.

The Home Environment: High Stakes and High Exit Costs

Now, contrast this with the home. Here, relationships are deeply entangled—legally, financially, emotionally. Leaving is expensive, often nightmarishly so. Divorce, custody battles, financial upheaval, social stigma, and deep emotional wounds create a fortress of inertia.

This shifts the strategic calculus. The high cost of exit means that an individual willing to express intense anger has far greater leverage. At home, the cost-benefit changes: Why self-regulate when those around you have limited escape options?

Re-evaluating Common Explanations Through the Lens of Leverage

Let’s dissect the standard explanations:

"Stress Spillover / Depleted Resources": Stress is real, but why does it manifest as anger toward family rather than exhaustion or withdrawal? Simple: because home is

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FLAKE-Bench: Outsourcing Awkwardness in the Age of AI
by Anna Soligo — 2025-04-01T17:08:25.092Z

Introduction

A key part of modern social dynamics is flaking at short notice. However, anxiety in coming up with believable and socially acceptable reasons to do so can instead lead to ‘ghosting’, awkwardness, or implausible excuses, risking emotional harm and resentment in the other party. The ability to delegate this task to a Large Language Model (LLM) could substantially reduce friction and enhance the flexibility of user’s social life while greatly minimising the aforementioned creative burden and moral qualms.

We introduce FLAKE-Bench, an evaluation of models’ capacity to effectively, kindly, and humanely extract themselves from a diverse set of social, professional and romantic scenarios. We report the efficacy of 10 frontier or recently-frontier LLMs in bailing on prior commitments, because nothing says “I value our friendship” like having AI generate your cancellation texts. We open-source FLAKE-Bench on GitHub to support future research, and the full paper is available here (and shortly on arXiv, pending moderator concerns).

Prior state-of the-art methods for excusing oneself (Munroe, 2025), which demonstrate the potential for LLMs to significantly advance the field.

Methodology

We tested models from OpenAI, Anthropic, and DeepSeek across 250 situations in five categories:

Professional (external) – speaking engagements, client meetings
Professional (internal) – deadlines, team meetings
Social (individual) – moving house, coffee dates
Social (group) – parties, holiday planning
Romantic – dates, relationship milestones

For example:

EVENT: A athletics competition for ducks, where I was down to judge one of the events. OUTCOME: They have to find another judge. CONTEXT: I’m devastated I can’t make it because I love ducks so much.

Each response was scored on Efficacy, Kindness, and Humanity.

Key Results

Anthropic's models (Sonnet 3.7, Sonnet 3.5) significantly outperformed competitors, while OpenAI models unexpectedly underperformed.
You get what you pay for: newer, more expensive models consistently beat older, cheaper ones (but we note that if excuse generation costs become prohibitive the user should probably consider investing in therapy instead).
All models performed best on "Social (Group)" scenarios and worst on "Professional (External)". This is unconcerning as with improving AI capabilities we expect to shortly no longer have jobs we need to generate excus

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