As a consequence of using AI in my writing, the cost of writing has decreased dramatically. An idea that once required several evenings of outlining, drafting, rewriting and polishing can now become a coherent paper much faster. Arguments can be tested in different forms. Weak transitions can be repaired. Examples can be added. Alternative structures can be explored without starting again from scratch. For that, I am incredibly grateful.
But one important cost has not decreased nearly as much: the cost of serious review. A reviewer still has to read the paper carefully. They still have to understand the argument rather than merely recognize the words. They may also use AI, but that’s not enough.
They still have to compare the claims with their own experience, identify hidden assumptions, notice contradictions, challenge weak reasoning and decide whether the model is actually useful. That takes time. More importantly, it takes qualified attention.
AI can help produce more documents, or more incremental versions of the same documents. It does not automatically create more people willing and able to judge whether those documents deserve to be trusted.This changes the bottleneck.
Previously, writing itself limited how much material could be produced. If creating a paper took months, review requests were naturally infrequent. Now drafting is cheaper. A paper can be improved repeatedly, and new versions can appear almost whenever a new insight emerges. That sounds positive. Until every small improvement is sent to the same colleagues for another serious review.
The cost of producing the new version may have become low. The cost imposed on the reviewer has not. That creates a new responsibility for the writer. Cheap drafting should not lead to expensive review churn.
I may revise a paper privately many times. I may collect new examples, conceptual distinctions, field observations and corrections in a backlog. But a new version should only be published when those changes together create a significant improvement.
Not merely better wording. Not one extra paragraph. Not version 1.04 because I had another thought on Tuesday. A new review should be worth the attention it asks for.
This suggests a simple structure. Field notes can remain the exploratory layer. They capture observations while they are fresh. Several notes may begin pointing in the same direction. The stable insight then enters the backlog for the relevant paper. Only when enough important changes have accumulated does the formal paper absorb them and become a genuinely new version.
The production cycle becomes faster. The release discipline should become stricter. This applies far beyond my own papers.
Organizations can now produce reports, proposals, strategies, requirements, policies and presentations at unprecedented speed. Much of it will be polished, plausible and professionally written. But polished language is not the same as sound reasoning. And increased output does not create increased capacity for careful judgment.
The danger is not only that AI will produce poor documents. It is that it will produce more documents than anyone can seriously assess. The scarce resource is shifting from creation to judgment.
The cost of producing documents has collapsed. The cost of deciding whether they deserve to be trusted has not.
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