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Position paper: AI safety research is missing 'AI Lock-In'

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AI safety research has mainly worked on two fronts: technical alignment, making AI systems produce outputs that match human intent, and regulating the societal impact of generative AI, including unemployment and labor market disruption. A new position paper argues a third dimension has been left underexplored: the risk that comes from depending on AI systems themselves. The authors name this AI Lock-In, the phenomenon in which excessive reliance on AI leads to human deskilling, shrinks people's capacity to function independently, and creates systemic vulnerability if the AI systems in question become unavailable or compromised. They argue this is not a hypothetical future problem: AI Lock-In is already emerging at three levels, individual, societal, and national, and they warn it could be sharply amplified by AI service disruptions or geopolitical conflict. Working through detailed scenarios, the paper traces how the risk emerges and escalates across those levels, from an individual losing a skill through disuse up to national-scale infrastructure failure if AI systems a country depends on go down. For each level, the authors offer guidance on how the risk can be mitigated and prepared for. Their conclusion is that AI Lock-In needs to be addressed proactively, before the dependencies it creates become entrenched or irreversible, because doing so is necessary to preserve both individual autonomy and national security.

Key facts

  • The paper argues AI safety research has covered technical alignment and the societal impact of generative AI, but has underexplored a third risk: dependence on AI systems themselves.
  • It names this risk AI Lock-In: excessive reliance on AI causing human deskilling, reduced capacity for independent function, and systemic vulnerability when AI becomes unavailable or compromised.
  • AI Lock-In is described as already emerging at three levels, individual, societal, and national, with the risk of being sharply amplified by AI service disruptions or geopolitical conflict.
  • The paper works through detailed scenarios tracing the risk from individual skill atrophy up to national-scale infrastructure failure, with mitigation guidance offered at each level.
  • The authors' conclusion: address AI Lock-In before the dependencies it creates become entrenched or irreversible, calling this essential for individual autonomy and national security.

Why it matters

Most AI safety debate has centered on making models behave (alignment) and on cushioning the economic fallout of automation (job loss, labor disruption). This paper points at a gap between those two: what happens as people, organizations, and countries come to structurally depend on AI systems working. That dependency is treated here as a distinct, systemic safety issue in its own right, not a side effect of the other two.

Who it affects

The paper frames AI Lock-In as cutting across three levels. At the individual level, it is skill atrophy, people losing the capacity to do a task themselves after routinely offloading it to AI. At the societal level, it is institutions and systems built around the assumption that AI tools stay available. At the national level, it is infrastructure and services that become fragile if the AI they run on is disrupted, whether by an outage or by geopolitical conflict.

How to use it

As a position paper, its practical output is a framework rather than a product: it lays out scenarios showing how lock-in escalates at each level and pairs them with mitigation guidance meant for AI safety researchers and policymakers to act on, aimed at catching the dependency before it becomes entrenched or irreversible.

How solid is it

This is an argument-based position paper, not an empirical study: the abstract presents no data, statistics, or named authors, and describes scenarios and mitigation guidance without detailing them. Its strength lies in naming and structuring a risk category, not in quantifying it.

Risks and caveats

The abstract does not specify who wrote the paper, what the detailed scenarios actually contain, or what the mitigation guidance recommends beyond referring to it in general terms. Readers looking for concrete numbers, case studies, or step-by-step mitigation would need the full paper, which lies beyond what is available here.

“AI Lock-In is a systemic threat that is already emerging at individual, societal, and national levels, one that could be dramatically amplified by AI service disruptions or geopolitical conflicts.”

— from the paper's abstract