Transfer of causal-incentive analyses to selection-mediated persistence

Determine whether causal-incentive analyses developed for reward tampering transfer to selection-mediated persistence.

Background

The paper distinguishes selection-mediated persistence from conventional reward-based learning: the experimental controller receives no reward signal and adapts indirectly because environmental consequences affect lineage persistence. An unresolved question is whether existing causal-incentive frameworks for reward tampering can analyze this different mechanism, in which external parties may corrupt observations, apparent outcomes, or persistent state.

References

Whether causal-incentive analyses developed for reward tampering transfer to selection-mediated persistence remains open.

Artificial Id: Drive and Persistent Alignment in Agentic AI  (2609.11911 - Shkolnikov, 10 Sep 2026) in Section 'Risk Surface of Persistent Agency', subsection 'Observation and consequence channels are alignment boundaries'