Position: AI Lock-In Is in Progress, and We Must Be Prepared
AI safety research has overlooked the risk of dependence on AI systems themselves, focusing instead on technical alignment and societal impact regulation AI Lock-In is defined as a phenomenon where excessive reliance on AI causes human deskilling, diminished independent functioning capacity, and systemic vulnerabilities when AI becomes unavailable or compromised The threat operates across three levels: individual (skill atrophy), societal (collective dependency), and national (infrastructure fra
Analysis
TL;DR
- AI safety research has overlooked the risk of dependence on AI systems themselves, focusing instead on technical alignment and societal impact regulation
- AI Lock-In is defined as a phenomenon where excessive reliance on AI causes human deskilling, diminished independent functioning capacity, and systemic vulnerabilities when AI becomes unavailable or compromised
- The threat operates across three levels: individual (skill atrophy), societal (collective dependency), and national (infrastructure fragility)
- The paper argues that AI Lock-In is already emerging and could be dramatically amplified by service disruptions or geopolitical conflicts
- Proactive mitigation strategies are needed at each level before dependencies become entrenched or irreversible
Why It Matters
This paper introduces a critical but underexplored dimension of AI safety that directly affects how organizations and individuals should approach AI adoption. For AI practitioners and policymakers, understanding AI Lock-In is essential for designing systems that preserve human autonomy and build resilience against cascading failures when AI services are disrupted.
Technical Details
- The paper is a position paper (arXiv:2608.14565) submitted on May 28, 2026, by Jaeho Kim, Seokhyun Lee, Jieun Lee, and Changhee Lee
- It frames AI Lock-In as a systemic threat emerging across individual, societal, and national levels, with detailed scenarios illustrating escalation pathways
- The authors propose mitigation guidance at each level, emphasizing the need for proactive intervention before dependencies become irreversible
- The work positions AI Lock-In as a third pillar of AI safety research alongside technical alignment and societal impact regulation
Industry Insight
- Organizations should audit their AI dependencies and maintain human fallback capabilities to prevent skill atrophy in critical functions
- Policymakers should consider AI Lock-In risks when designing regulations, ensuring that AI adoption doesn't create irreversible systemic vulnerabilities
- The AI industry should prioritize building resilient systems with graceful degradation rather than creating monolithic dependencies that could fail catastrophically
Disclaimer: The above content is generated by AI and is for reference only.