📜

Motivations, Natural Selection, and Curriculum Engineering

📅 2021
policy development
🔵 Rare
#adaptation executors #ai #corrigibility #evolution #general intelligence #mesa-optimization #seri mats

📖 Description

*Epistemic status: I am professionally familiar with contemporary machine learning theory and practice, and have a long-standing amateur interest in natural history. But (despite being a long-term lurker on LW and AF) I feel very uncertain about the nature and status of goals and motivations! This post is an attempt, heavily inspired by Richard Ngo's* [Shaping Safer Goals sequence](https://www.lesswrong.com/s/boLPsyNwd6teK5key), *to lay out a few ways of thinking about goals and motivations in natural and artificial systems, to point to a class of possible prosaic development paths to AGI where general capabilities emerge from extensive open-ended training, and finally observe some desiderata and gaps in our understanding regarding alignment conditional on this situation.*

📊 Game Impacts

Variable Change Condition
Research +10 Always
Vibey Doom +5 Always
Ethics Risk -5 Always

💭 Reactions

🔬 Safety Researcher Reaction: ⚠️ Placeholder - Needs Real Quote
"Important work advancing our understanding of AI safety"
📰 Media Reaction: ⚠️ Placeholder - Needs Real Quote
"Discussed in AI safety community"
💡 Found a Real Quote? Suggest it here

🔗 Sources

🏷️ Event Metadata

Think this event's metadata could be improved? Suggest changes to category, rarity, tags, game impacts, or p(doom) effects.

🤝 Found an Issue?

This event data is sourced from the pdoom-data repository. If you notice errors or want to suggest improvements:

GitHub Issue (Preferred) 📧 Email (No GitHub)
← Back to All Events