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client: ea_forum
project_id: summaries
narrator: cs
---

Original article:
https://forum.effectivealtruism.org/posts/o3Gaoizs2So6SpgLH/summaries-of-top-forum-posts-27th-march-to-16th-april

This podcast has just passed the 6-month mark! Please give us your feedback and suggestions so we can continue to improve — the survey should take no more than 10 minutes, and we really appreciate your input!

This is part of a weekly series summarizing the top posts on the EA Forum — you can see the full collection here. The first post includes some details on purpose and methodology. Feedback, thoughts, and corrections are welcomed.

Narrated by Coleman Jackson Snell. Summaries written by Zoe Williams (Rethink Priorities).

Published by TYPE III AUDIO on behalf of the Effective Altruism Forum.

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client: ea_forum
project_id: curated 
narrator: pw
qa: mds
qa_time: 0h15m
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I recently spent some time reflecting on my career and my life, for a few reasons:

• It was my 29th birthday, an occasion which felt like a particularly natural time to think through what I wanted to accomplish over the course of the next year 🙂.
• It seems like AI progress is heating up.
• It felt like a good time to reflect on how Redwood has been going, because we’ve been having conversations with funders about getting more funding.

I wanted to have a better answer to these questions:

• What’s the default trajectory that I should plan for my career to follow? And what does this imply for what I should be doing right now?
• How much urgency should I feel in my life?
• How hard should I work?
• How much should I be trying to do the most valuable-seeming thing, vs engaging in more playful exploration and learning?

Original article:
https://forum.effectivealtruism.org/posts/2DzLY6YP2z5zRDAGA/a-freshman-year-during-the-ai-midgame-my-approach-to-the

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client: lesswrong
project_id: curated
feed_id: ai_alignment, ai
narrator: pw
qa: km
qa_time: 0h50m
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The primary talk of the AI world recently is about AI agents (whether or not it includes the question of whether we can’t help but notice we are all going to die.)

The trigger for this was AutoGPT, now number one on GitHub, which allows you to turn GPT-4 (or GPT-3.5 for us clowns without proper access) into a prototype version of a self-directed agent.

We also have a paper out this week where a simple virtual world was created, populated by LLMs that were wrapped in code designed to make them simple agents, and then several days of activity were simulated, during which the AI inhabitants interacted, formed and executed plans, and it all seemed like the beginnings of a living and dynamic world. Game version hopefully coming soon.

How should we think about this? How worried should we be?

Original article:
https://www.lesswrong.com/posts/566kBoPi76t8KAkoD/on-autogpt

Narrated for LessWrong by TYPE III AUDIO.

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client: ea_forum
project_id: articles
feed_id: ai_safety
narrator: pw
qa: mds
qa_time: 0h15m
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This is a linkpost for https://www.forourposterity.com/want-to-win-the-agi-race-solve-alignment/

Society really cares about safety. Practically speaking, the binding constraint on deploying your AGI could well be your ability to align your AGI. Solving (scalable) alignment might be worth lots of $$$ and key to beating China.

Look, I really don't want Xi Jinping Thought to rule the world. If China gets AGI first, the ensuing rapid AI-powered scientific and technological progress could well give it a decisive advantage (cf potential for >30%/year economic growth with AGI). I think there's a very real specter of global authoritarianism here. 

Or hey, maybe you just think AGI is cool. You want to go build amazing products and enable breakthrough science and solve the world’s problems.

So, race to AGI with reckless abandon then? At this point, people get into agonizing discussions about safety tradeoffs. And many people just mood affiliate their way to an answer: "accelerate, progress go brrrr," or "AI scary, slow it down."

I see this much more practically. And, practically, society cares about safety, a lot. Do you actually think that you’ll be able to and allowed to deploy an AI system that has, say, a 10% chance of destroying all of humanity?

Original article:
https://forum.effectivealtruism.org/posts/Ackzs8Wbk7isDzs2n/want-to-win-the-agi-race-solve-alignment

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---
client: lesswrong
project_id: curated
feed_id: ai_safety
narrator: pw
qa: km
qa_time: 0h10m
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(Related text posted to Twitter; this version is edited and has a more advanced final section.)

Imagine yourself in a box, trying to predict the next word - assign as much probability mass to the next token as possible - for all the text on the Internet.

Koan:  Is this a task whose difficulty caps out as human intelligence, or at the intelligence level of the smartest human who wrote any Internet text?  What factors make that task easier, or harder?  (If you don't have an answer, maybe take a minute to generate one, or alternatively, try to predict what I'll say next; if you do have an answer, take a moment to review it inside your mind, or maybe say the words out loud.)

Original article:
https://www.lesswrong.com/posts/nH4c3Q9t9F3nJ7y8W/gpts-are-predictors-not-imitators

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---
client: agi_sf
project_id: core_readings
feed_id: agi_sf__alignment
narrator: pw
qa: mds
qa_time: 0h30m
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The two tasks of supervised learning: regression and classification. Linear regression, loss functions, and gradient descent.

How much money will we make by spending more dollars on digital advertising? Will this loan applicant pay back the loan or not? What’s going to happen to the stock market tomorrow?

Original article:
https://medium.com/machine-learning-for-humans/supervised-learning-740383a2feab

Author:
Vishal Maini

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This article is featured on the AGI Safety Fundamentals: Alignment course curriculum.

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client: t3a
feed_id: ai_safety_abstracts
narrator: ai
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This episode covers 3 abstracts:

1. Active reward learning from multiple teachers - Peter Barnett et al. 
2. Conditioning Predictive Models: Risks and Strategies - Hubinger et al.
3. Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT2 small - Kevin Wang et al.

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(This is a stylized version of a real conversation, where the first part happened as part of a public debate between John Wentworth and Eliezer Yudkowsky, and the second part happened between John and me over the following morning. The below is combined, stylized, and written in my own voice throughout. The specific concrete examples in John's part of the dialog were produced by me. It's over a year old. Sorry for the lag.)

(As to whether John agrees with this dialog, he said "there was not any point at which I thought my views were importantly misrepresented" when I asked him for comment.)

Original article: https://www.lesswrong.com/posts/fJBTRa7m7KnCDdzG5/a-stylized-dialogue-on-john-wentworth-s-claims-about-markets

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---
client: lesswrong
project_id: curated
feed_id: ai_safety 
narrator: pw
qa: mds
qa_time: 1h00m
---

In late 2022, Nate Soares gave some feedback on my Cold Takes series on AI risk (shared as drafts at that point), stating that I hadn't discussed what he sees as one of the key difficulties of AI alignment.

I wanted to understand the difficulty he was pointing to, so the two of us had an extended Slack exchange, and I then wrote up a summary of the exchange that we iterated on until we were both reasonably happy with its characterization of the difficulty and our disagreement.1 My short summary is:

• Nate thinks there are deep reasons that training an AI to do needle-moving scientific research (including alignment) would be dangerous. The overwhelmingly likely result of such a training attempt (by default, i.e., in the absence of specific countermeasures that there are currently few ideas for) would be the AI taking on a dangerous degree of convergent instrumental subgoals while not internalizing important safety/corrigibility properties enough.
• I think this is possible, but much less likely than Nate thinks under at least some imaginable training processes.

Original article:
https://www.lesswrong.com/posts/iy2o4nQj9DnQD7Yhj/discussion-with-nate-soares-on-a-key-alignment-difficulty

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client: ea_forum
project_id: curated
feed_id: ai_safety
narrator: pw
qa: mds
qa_time: 0h30m
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Far fewer people are working on it than you might think, and even the alignment research that is happening is very much not on track. (But it’s a solvable problem, if we get our act together.)

Original article:
This is a linkpost for https://www.forourposterity.com/nobodys-on-the-ball-on-agi-alignment/
https://forum.effectivealtruism.org/posts/5LNxeWFdoynvgZeik/nobody-s-on-the-ball-on-agi-alignment

Narrated for the Effective Altruism Forum by TYPE III AUDIO.

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