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Replication Control

Replication control becomes relevant when an AI system can duplicate itself—or be duplicated—beyond the reach of any central authority.

Addresses / Mitigates

  • Loss Of Human Control: An explicit interruption capability can avert catastrophic errors or runaway behaviours
  • Emergent Behaviour: Preventing self-replicating AI or unsupervised proliferation of emergent behaviours by implementing strict replication oversight.

  • Replication control becomes relevant when an AI system can duplicate itself—or be duplicated—beyond the reach of any central authority (analogous to a computer virus—though with potentially far greater autonomy and adaptability).

  • An organization/person builds a very capable AI with some misaligned objectives. If they distribute its model or code openly, it effectively becomes “in the wild.”

  • Could controls be put in place to prevent this from happening? TODO: figure this out.

  • In open-source communities or decentralised systems, controlling replication requires broad consensus and technical enforcement measures.