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Why focus on schemers in particular? (Sections 1.3-1.4 of "Scheming AIs")

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Manage episode 385590246 series 3402048
Content provided by Joe Carlsmith. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Joe Carlsmith or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
  continue reading

Chapters

1. Why focus on schemers in particular? (Sections 1.3-1.4 of "Scheming AIs") (00:00:00)

2. 1.3 Why focus on schemers in particular? (00:00:36)

3. 1.3.1 The type of misalignment I’m most worried about (00:01:14)

4. 1.3.2 Contrast with reward-on-the-episode seekers (00:04:27)

5. 1.3.2.1 Responsiveness to honest tests (00:04:46)

6. 1.3.2.2 Temporal scope and general “ambition” (00:07:54)

7. 1.3.2.3 Sandbagging and “early undermining” (00:11:17)

8. 1.3.3 Contrast with models that aren’t playing the training game (00:17:13)

9. 1.3.4 Non-schemers with schemer-like traits (00:23:13)

10. 1.3.5 Mixed models (00:25:20)

11. 1.4 Are theoretical arguments about this topic even useful? (00:28:35)

54 episodes

Artwork
iconShare
 
Manage episode 385590246 series 3402048
Content provided by Joe Carlsmith. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Joe Carlsmith or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
  continue reading

Chapters

1. Why focus on schemers in particular? (Sections 1.3-1.4 of "Scheming AIs") (00:00:00)

2. 1.3 Why focus on schemers in particular? (00:00:36)

3. 1.3.1 The type of misalignment I’m most worried about (00:01:14)

4. 1.3.2 Contrast with reward-on-the-episode seekers (00:04:27)

5. 1.3.2.1 Responsiveness to honest tests (00:04:46)

6. 1.3.2.2 Temporal scope and general “ambition” (00:07:54)

7. 1.3.2.3 Sandbagging and “early undermining” (00:11:17)

8. 1.3.3 Contrast with models that aren’t playing the training game (00:17:13)

9. 1.3.4 Non-schemers with schemer-like traits (00:23:13)

10. 1.3.5 Mixed models (00:25:20)

11. 1.4 Are theoretical arguments about this topic even useful? (00:28:35)

54 episodes

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