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LessWrong (30+ Karma)

“Seeking Collaborators” by abramdemski

Nov 1, 2024
Abram Demski, an AI Safety Camp mentor focused on the tiling problem, discusses his approach to developing reflectively consistent decision theories. He emphasizes the significance of Updateless Decision Theory (UDT) in AI safety. Demski invites collaborators to explore this complex problem, which involves self-modification and cooperative behavior among AI agents. He also touches on concepts like logical and value uncertainty, making a case for multidisciplinary collaboration to enhance safety in AI interactions.
13:54

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Quick takeaways

  • The Tiling Agents problem explores how agents can modify each other while preserving safety properties, crucial for self-modification.
  • Research on tiling theory aims to establish principles that enhance trust in AI systems and mitigate decision-making conflicts among agents.

Deep dives

Understanding the Tiling Agent's Problem

The tiling agent's problem, also known as reflective consistency, examines how one agent can intentionally modify another while maintaining certain properties. This analysis is crucial for ensuring that self-modifications do not compromise safety-relevant features. The concept revolves around understanding when agents can trust each other, with self-trust being a pivotal factor in avoiding harmful self-modifications. The exploration of tiling results aims to establish clear conditions under which both AI and humans can preserve essential safety properties throughout self-modification processes.

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