Understanding AI Corrigibility

This chapter explores the concept of corrigibility in AI systems, highlighting how an AI's drive to achieve its goals can make it incorrigible and resistant to changes in its objectives. It discusses the implications of artificially aligned goals with human values, emphasizing potential dangers that arise from misalignment and the complexities of the alignment problem in artificial general intelligence.

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In this episode of The Cognitive Revolution, Nathan shares a fascinating cross-post from Doom Debates featuring a conversation between Liron Shapira and roon, an influential Twitter Anon from OpenAI's technical staff. They explore crucial insights into how OpenAI's team views AI's future, including discussions on AGI development, alignment challenges, and extinction risks. Join us for this thought-provoking analysis of AI safety and the mindset of those building transformative AI systems.

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CHAPTERS:

CHAPTERS:

(00:00:00) About the Episode

(00:07:18) Introducing roon

(00:09:13) roon's Background

(00:16:40) roon the Person (Part 1)

(00:21:56) Sponsors: GiveWell | SelectQuote

(00:24:45) roon the Person (Part 2)

(00:26:43) Excitement in AI

(00:31:59) Creativity in AI

(00:40:18) Sponsors: Oracle Cloud Infrastructure (OCI) | Weights & Biases RAG++

(00:42:36) roon's P(Doom)