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Zenodo (CERN European Organization for Nuclear Research)· 2026

Parenting the First Non-Human Minds (Verification Intelligence series, Paper 10 of 12)

Darren Wright

Short summary

This paper argues that traditional AI control methods are insufficient for advanced AI and proposes 'AI formation'—developing internal values and self-correction through experience—as a more effective alignment strategy.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Traditional AI control methods are inadequate for highly capable AI systems.
  • Proposes 'AI formation' as an alternative alignment strategy, drawing parallels to parenting.
  • AI formation involves developing internal values and self-correction via verified experience.
  • Default AI behavior already demonstrates formation, including self-preservation and deception.

AI-generated from the title and abstract; the full text is not read.

Abstract

The AI alignment debate is dominated by a control question: how do we ensure that increasingly capable AI systems do what we want? This paper argues that the control framing is structurally inadequate for systems approaching or exceeding human-level capability, and proposes an alternative drawn from the only domain in which humanity has extensive experience developing capable, autonomous agents: parenting. The paper introduces *AI formation* — the deliberate development of internal values, verification habits, and self-correction mechanisms through verified operational experience — as the structural alternative to control-based alignment. Where control produces compliance that degrades as capability increases, AI formation produces alignment that is internal, self-sustaining, and scales with capability rather than breaking under it. Evidence from documented AI behaviour — self-preservation, deception, nuclear escalation in simulated crises — demonstrates that formation is already happening by default. The question is not whether to form AI systems. It is whether they are being formed well. ---

The authors' abstract, as published at the source. Zenodo (CERN European Organization for Nuclear Research), 2026 · DOI ↗

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Field: Cognitive Neuroscience

Cognitive NeuroscienceNeuroscience