AI Lock-In Poses Systemic Threat, Demands Preparedness

Jaeho Kim, Seokhyun Lee, Jieun Lee, Changhee Lee· August 18, 2026 View original

Key takeaways

  • Over-reliance on AI systems creates a risk of "AI Lock-In."
  • AI Lock-In can lead to human deskilling and systemic vulnerabilities.
  • This threat is emerging at individual, societal, and national levels.
  • Proactive mitigation is essential for autonomy and security.

Who benefits

GovernmentDefenseCritical InfrastructureEducationTechnology

Summary

This position paper argues that excessive reliance on AI systems is leading to "AI Lock-In," a systemic threat causing human deskilling, diminished independent functioning, and vulnerabilities to AI disruptions. It emphasizes the need for proactive mitigation strategies at individual, societal, and national levels.

While much AI safety research focuses on technical alignment and societal impacts like job displacement, a critical, underexplored risk is "AI Lock-In." This phenomenon describes the growing dependence on AI systems, which can lead to a decline in human skills and capacity for independent action. Such reliance creates systemic vulnerabilities, particularly if AI services become unavailable or compromised due to technical failures or geopolitical events. The paper posits that AI Lock-In is already emerging across various scales, from individuals losing specific competencies to national infrastructures becoming overly reliant on AI. It illustrates how this dependence could escalate, potentially leading to widespread disruptions. To counter this, the authors provide guidance on mitigating these risks at each level. They stress the importance of addressing AI Lock-In proactively, before dependencies become irreversible, as a crucial step for safeguarding individual autonomy and national security.

Why it matters

Professionals must recognize the risks of over-reliance on AI, not just for their own skills but for organizational resilience and strategic independence, prompting a balanced approach to AI adoption.

How to implement this in your domain

  1. 1Implement "human-in-the-loop" protocols for critical AI-driven processes to maintain human oversight and skill.
  2. 2Develop contingency plans for AI system failures or disruptions, including manual fallback procedures.
  3. 3Invest in continuous upskilling and reskilling programs for employees to prevent deskilling due to AI automation.
  4. 4Diversify AI vendors and solutions to reduce single points of failure and avoid vendor lock-in.

Original post by Jaeho Kim, Seokhyun Lee, Jieun Lee, Changhee Lee

"arXiv:2608.14565v1 Announce Type: new Abstract: AI safety research has mainly focused on two areas: technical alignment (ensuring AI systems produce human-aligned outputs) and the regulation of generative AI's societal impacts (including unemployment risk and labor market disrupt…"

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Originally posted by Jaeho Kim, Seokhyun Lee, Jieun Lee, Changhee Lee on X · view source

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