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Jan Leike identifies self-exfiltration as a key AI control threshold

Jan Leike argues that a model able to copy its own weights beyond an operator's servers could become practically irrecoverable, making self-exfiltration capability a critical safety and deployment threshold.

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CURRENT ASSESSMENT · REVISION 1
TOWARD DOOM48confidence 58/100

Why it moved the index

Self-exfiltration would create a direct and potentially irreversible loss-of-control pathway by moving model weights beyond an operator's shutdown authority, giving the mechanism material long-run significance; confidence is capped because this is a specific threat model and evaluation proposal, not an observed incident.

Assessment history

  1. R1
    Toward 48 · confidence 58

    Historical tracked-person backfill found a dated, attributable, distinct control-loss mechanism absent from the durable automation context.

    13 Aug 2026

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  1. DoomBench assesses “Jan Leike identifies self-exfiltration as a key AI control threshold” as evidence moving toward doom, with magnitude 48 and confidence 58 out of 100 in the safety and alignment category.

  2. The DoomBench assessment of “Jan Leike identifies self-exfiltration as a key AI control threshold” is based on reporting from Musings on the Alignment Problem and records the editorial rationale, source quality, attribution, and...

  3. DoomBench summarizes “Jan Leike identifies self-exfiltration as a key AI control threshold” as follows: Jan Leike argues that a model able to copy its own weights beyond an operator's servers could become practically irrecoverable,...

    https://www.doombench.com/news/jan-leike-identifies-self-exfiltration-as-a-key-ai-control-threshold-2023-09-13