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LessWrong에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 LessWrong 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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“Self-Other Overlap: A Neglected Approach to AI Alignment” by Marc Carauleanu, Mike Vaiana, Judd Rosenblatt, Diogo de Lucena
Manage episode 432958306 series 3364760
LessWrong에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 LessWrong 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Figure 1. Image generated by DALL-3 to represent the concept of self-other overlapMany thanks to Bogdan Ionut-Cirstea, Steve Byrnes, Gunnar Zarnacke, Jack Foxabbott and Seong Hah Cho for critical comments and feedback on earlier and ongoing versions of this work.
Summary
In this post, we introduce self-other overlap training: optimizing for similar internal representations when the model reasons about itself and others while preserving performance. There is a large body of evidence suggesting that neural self-other overlap is connected to pro-sociality in humans and we argue that there are more fundamental reasons to believe this prior is relevant for AI Alignment. We argue that self-other overlap is a scalable and general alignment technique that requires little interpretability and has low capabilities externalities. We also share an early experiment of how fine-tuning a deceptive policy with self-other overlap reduces deceptive behavior in a simple RL environment. On top of that [...]
The original text contained 1 footnote which was omitted from this narration.
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First published:
July 30th, 2024
Source:
https://www.lesswrong.com/posts/hzt9gHpNwA2oHtwKX/self-other-overlap-a-neglected-approach-to-ai-alignment
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Narrated by TYPE III AUDIO.
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…
continue reading
Summary
In this post, we introduce self-other overlap training: optimizing for similar internal representations when the model reasons about itself and others while preserving performance. There is a large body of evidence suggesting that neural self-other overlap is connected to pro-sociality in humans and we argue that there are more fundamental reasons to believe this prior is relevant for AI Alignment. We argue that self-other overlap is a scalable and general alignment technique that requires little interpretability and has low capabilities externalities. We also share an early experiment of how fine-tuning a deceptive policy with self-other overlap reduces deceptive behavior in a simple RL environment. On top of that [...]
The original text contained 1 footnote which was omitted from this narration.
---
First published:
July 30th, 2024
Source:
https://www.lesswrong.com/posts/hzt9gHpNwA2oHtwKX/self-other-overlap-a-neglected-approach-to-ai-alignment
---
Narrated by TYPE III AUDIO.
---
332 에피소드
Manage episode 432958306 series 3364760
LessWrong에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 LessWrong 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Figure 1. Image generated by DALL-3 to represent the concept of self-other overlapMany thanks to Bogdan Ionut-Cirstea, Steve Byrnes, Gunnar Zarnacke, Jack Foxabbott and Seong Hah Cho for critical comments and feedback on earlier and ongoing versions of this work.
Summary
In this post, we introduce self-other overlap training: optimizing for similar internal representations when the model reasons about itself and others while preserving performance. There is a large body of evidence suggesting that neural self-other overlap is connected to pro-sociality in humans and we argue that there are more fundamental reasons to believe this prior is relevant for AI Alignment. We argue that self-other overlap is a scalable and general alignment technique that requires little interpretability and has low capabilities externalities. We also share an early experiment of how fine-tuning a deceptive policy with self-other overlap reduces deceptive behavior in a simple RL environment. On top of that [...]
The original text contained 1 footnote which was omitted from this narration.
---
First published:
July 30th, 2024
Source:
https://www.lesswrong.com/posts/hzt9gHpNwA2oHtwKX/self-other-overlap-a-neglected-approach-to-ai-alignment
---
Narrated by TYPE III AUDIO.
---
…
continue reading
Summary
In this post, we introduce self-other overlap training: optimizing for similar internal representations when the model reasons about itself and others while preserving performance. There is a large body of evidence suggesting that neural self-other overlap is connected to pro-sociality in humans and we argue that there are more fundamental reasons to believe this prior is relevant for AI Alignment. We argue that self-other overlap is a scalable and general alignment technique that requires little interpretability and has low capabilities externalities. We also share an early experiment of how fine-tuning a deceptive policy with self-other overlap reduces deceptive behavior in a simple RL environment. On top of that [...]
The original text contained 1 footnote which was omitted from this narration.
---
First published:
July 30th, 2024
Source:
https://www.lesswrong.com/posts/hzt9gHpNwA2oHtwKX/self-other-overlap-a-neglected-approach-to-ai-alignment
---
Narrated by TYPE III AUDIO.
---
332 에피소드
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