📜

Arguments against myopic training

📅 2020
policy development
⚪ Common
#ai #myopia

📖 Description

*Note that this post has been edited to clarify the difference between explicitly assigning a reward to an action based on its later consequences, versus implicitly reinforcing an action by assigning high reward during later timesteps when its consequences are observed. I'd previously conflated these in a confusing way; thanks to Rohin for highlighting this issue.*

📊 Game Impacts

Variable Change Condition
Research +10 Always
Vibey Doom +2 Always
Ethics Risk -5 Always

💭 Reactions

🔬 Safety Researcher Reaction: ⚠️ Placeholder - Needs Real Quote
"Interesting perspective on safety challenges"
📰 Media Reaction: ⚠️ Placeholder - Needs Real Quote
"Discussed in AI safety community"
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🔗 Sources

🏷️ Event Metadata

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📁 Category Policy Development → Suggest different category
⭐ Rarity ⚪ Common → Suggest different rarity
🏷️ Tags (2) ai, myopia → Suggest tag changes
📊 Game Impacts (3) 3 variable changes → Suggest impact changes
☢️ p(Doom) Impact No direct impact → Suggest p(doom) change
📝 General Metadata Year, description, reactions → Comprehensive review

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