mlsanityData to 7 Oct 2026

Gradual Disempowerment: Systemic Existential Risks from Incremental AI Development

arXiv 2501.16946 ↗First posted 28 Jan 2025cs.CYcited by 42

Not on the map. Why?

Abstract (arXiv)

This paper examines the systemic risks posed by incremental advancements in artificial intelligence, developing the concept of `gradual disempowerment', in contrast to the abrupt takeover scenarios commonly discussed in AI safety. We analyze how even incremental improvements in AI capabilities can undermine human influence over large-scale systems that society depends on, including the economy, culture, and nation-states. As AI increasingly replaces human labor and cognition in these domains, it can weaken both explicit human control mechanisms (like voting and consumer choice) and the implicit alignments with human interests that often arise from societal systems' reliance on human participation to function. Furthermore, to the extent that these systems incentivise outcomes that do not line up with human preferences, AIs may optimize for those outcomes more aggressively. These effects may be mutually reinforcing across different domains: economic power shapes cultural narratives and political decisions, while cultural shifts alter economic and political behavior. We argue that this dynamic could lead to an effectively irreversible loss of human influence over crucial societal systems, precipitating an existential catastrophe through the permanent disempowerment of humanity. This suggests the need for both technical research and governance approaches that specifically address the risk of incremental erosion of human influence across interconnected societal systems.

Key facts. Cited by 42 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Jan 2025.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 22; 2026: 20.

42 papers.

Sort:

By area:

  1. 2025Levels of Autonomy for AI Agentscited by 45
  2. 2025Among Us: A Sandbox for Measuring and Detecting Agentic Deceptioncited by 24
  3. 2025Virtual Agent Economiescited by 17
  4. 2025A Pragmatic View of AI Personhoodcited by 12
  5. 2025AI Safety Should Prioritize the Future of Workcited by 11
  6. 2025HumanAgencyBench: Scalable Evaluation of Human Agency Support in AI Assistantscited by 10
  7. 2026AI Assistance Reduces Persistence and Hurts Independent Performancecited by 7
  8. 2025AI Awarenesscited by 6
  9. 2025Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Valuecited by 6
  10. 2026How to Count AIs: Individuation and Liability for AI Agentscited by 5
  11. 2026Self-Improvement of Large Language Models: A Technical Overview and Future Outlookcited by 5
  12. 2025Misalignment or misuse? The AGI alignment tradeoffcited by 4
30 more
  1. 2025Embodied AI: Emerging Risks and Opportunities for Policy Actioncited by 3
  2. 2025Human-AI Complementarity: A Goal for Amplified Oversightcited by 3
  3. 2026Overseeing Agents Without Constant Oversight: Challenges and Opportunitiescited by 3
  4. 2026Architecting Trust in Artificial Epistemic Agentscited by 3
  5. 2025The Economics of p(doom): Scenarios of Existential Risk and Economic Growth in the Age of Transformative AIcited by 2
  6. 2025Military AI Cyber Agents (MAICAs) Constitute a Global Threat to Critical Infrastructurecited by 2
  7. 2025Distributed and Decentralised Training: Technical Governance Challenges in a Shifting AI Landscapecited by 2
  8. 2025Against racing to AGI: Cooperation, deterrence, and catastrophic riskscited by 2
  9. 2025Reproducibility: The New Frontier in AI Governancecited by 2
  10. 2026The Homogenization Problem in LLMs: Towards Meaningful Diversity in AI Safetycited by 1
  11. 2026Solipsistic Superintelligence is Unlikely to be Cooperativecited by 1
  12. 2026A dataset of rated conceptual argumentscited by 1
  13. 2025Mitigating Societal Cognitive Overload in the Age of AI: Challenges and Directionscited by 0
  14. 2025A Taxonomy of Omnicidal Futures Involving Artificial Intelligencecited by 0
  15. 2025Dimensional Characterization and Pathway Modeling for Catastrophic AI Riskscited by 0
  16. 2025Corrigibility Transformation: Constructing Goals That Accept Updatescited by 0
  17. 2025When Assisting One Disempowers Anothercited by 0
  18. 2025Dark Speculation: Combining Qualitative and Quantitative Understanding in Frontier AI Risk Analysiscited by 0
  19. 2026From Diagnosis to Inoculation: Building Cognitive Resistance to AI Disempowermentcited by 0
  20. 2026Questionnaire Responses Do not Capture the Safety of AI Agentscited by 0
  21. 2026Mecha-nudges for Machinescited by 0
  22. 2026AI Loss of Control Incident Management: Response & Resiliencecited by 0
  23. 2026Generative Models Erode Human Temporal Learning Through Market Selectioncited by 0
  24. 2026Memetic Capture: A Pluralistic Policy Framework for Governing AI-Driven Cultural Disempowermentcited by 0
  25. 2026AI Researchers Must Help Lead Arms Control to Mitigate Military AI Riskscited by 0
  26. 2026AI Coaching for Accelerating Human Skill Development with Reinforcement Learningcited by 0
  27. 2026The Closing Window: How Governments Could Lose Their Ability to Restrain Advanced AIcited by 0
  28. 2026AI Evaluation Should Work With Humanscited by 0
  29. 2026Growth Without Us: Machine Consumers, Corporate Circularity, and the Decoupling of GDP from Humanity after AGIcited by 0
  30. 2026Math for AI safety: an invitation for mathematicianscited by 0