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The Possibility of Artificial Intelligence Becoming a Subject and the Alignment Problem

arXiv 2604.14990 ↗First posted 16 Apr 2026cs.AIcited by 0

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Abstract (arXiv)

The prospect of Artificial General Intelligence (AGI) is increasingly driving institutional decisions, and alignment of AGI is a hard problem. The currently dominant AI alignment strategies like reinforcement learning with human feedback or constitutional AI, while partly taking ``model welfare'' into account, share a common ontology: the AI system is an optimiser whose objective function must be constrained from outside, and the ultimate goal is to keep human control and containment of AI. We argue that this control-based framing becomes insufficient when AGI has plausibly attained moral patient or subject status. Building on a structural analogy to Freud's model of the psyche and Turing's analogy of ``child machines'', we are developing a vision of the possibility of autonomy-supporting parenting of AI, in which human control over a developing AGI is gradually reduced, allowing AI to become an independent, autonomous subject, that will be negotiated with rather than constrained. Such a perspective opens up the possibility of cooperative coexistence and co-evolution between humans and AGIs. Hence, we also examine the relation between humans and developing AGI from an evolutionary and a game-theoretic perspective. Instead of Nash's individualistic framework, we use Berge equilibria, Aumann's correlated equilibria and Capraro's moral preference hypothesis. The relationship between humans and AGIs will thus have to be newly determined, which will change our self-image as humans. It will be crucial that humans not only claim control over potential AGIs, but also engage with AGIs through surprise, creativity, and other specifically human qualities, thereby offering them motivating incentives for cooperation.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 26 of its 67 references that are in the map. First posted on arXiv 16 Apr 2026.

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26 of 67 references.

References · 26

  1. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 3,050
  2. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,592
  3. 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,439
  4. 2021A General Language Assistant as a Laboratory for Alignmentcited by 1,055
  5. 2024Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Trainingcited by 529
  6. 2022The Alignment Problem from a Deep Learning Perspectivecited by 258
  7. 2023AI Deception: A Survey of Examples, Risks, and Potential Solutionscited by 188
  8. 2023Removing RLHF Protections in GPT-4 via Fine-Tuningcited by 171
  9. 2020Open Problems in Cooperative AIcited by 168
  10. 2025Measuring AI Ability to Complete Long Software Taskscited by 156
  11. 2018Supervising strong learners by amplifying weak expertscited by 145
  12. 2019Optimal Policies Tend to Seek Powercited by 119
14 more
  1. 2023Levels of AGI for Operationalizing Progress on the Path to AGIcited by 96
  2. 2025Stress Testing Deliberative Alignment for Anti-Scheming Trainingcited by 86
  3. 2025School of Reward Hacks: Hacking harmless tasks generalizes to misaligned behavior in LLMscited by 66
  4. 2024Thousands of AI Authors on the Future of AIcited by 48
  5. 2025An Approach to Technical AGI Safety and Securitycited by 45
  6. 2024Taking AI Welfare Seriouslycited by 31
  7. 2024International Scientific Report on the Safety of Advanced AI (Interim Report)cited by 19
  8. 2021Mathematical foundations of moral preferencescited by 16
  9. 2025Deception in LLMs: Self-Preservation and Autonomous Goals in Large Language Modelscited by 16
  10. 2025A Pragmatic View of AI Personhoodcited by 12
  11. 2025Towards a Theory of AI Personhoodcited by 6
  12. 2025The Dragon Hatchling: The Missing Link between the Transformer and Models of the Braincited by 6
  13. 2024A systematic review of norm emergence in multi-agent systemscited by 4
  14. 2019Theories of Parenting and their Application to Artificial Intelligencecited by 1

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