Epistemic inflation.
AI has made information almost free to dump, while leaving everyone else to pay the cost of deciding what is worth keeping.
That is digital fly-tipping.
The problem is not simply that AI produces bad information. Much of it is useful, coherent and convincing.
The problem is that the cost of generating plausible information has collapsed, while the cost of verifying it has not.
So the economics have become badly distorted.
A human once had to spend time researching, writing, checking and publishing something. Now a machine can generate thousands of plausible articles, reviews, explanations, code snippets or reports almost instantly.
The information enters the shared digital environment cheaply.
The verification cost arrives later.
Someone still has to determine whether it is accurate, relevant, duplicated, misleading, outdated or subtly wrong.
That cost is pushed downstream onto readers, engineers, researchers, businesses, search engines and eventually other AI systems.
This is where AI's deeper weakness matters.
AI can generate what looks right; it cannot guarantee what is right.
Worse, it can take a carefully bounded idea and expand it into something broader and more certain simply because that makes a better continuation.
That is epistemic inflation.
A modest claim becomes a confident conclusion.
A possibility becomes a prediction.
A concern becomes a crisis.
And once that inflated information is published, indexed, copied and eventually consumed by other machines, it starts to become part of the digital landscape.
The danger is therefore not simply "AI slop".
It is the increasing difficulty of distinguishing information that has merely been generated from information that has earned the right to become knowledge.
Physical fly-tipping works because dumping is cheaper than responsible disposal.
Digital fly-tipping works because generation is cheaper than verification.
And until that economic imbalance changes, the internet risks becoming extraordinarily good at producing information while becoming progressively worse at telling us what is worth keeping.
AuthOrigin
Preserving the difference between knowing, believing, inferring and acting.
The problems explored in this essay — plausible answers replacing genuine knowledge, inferences treated as facts, decisions made without traceable authority — are not separate issues. They share a common cause: the epistemic state of information is lost in transit.
AuthOrigin preserves the knowledge-to-consequence chain. Every piece of information carries its epistemic state — not just what it says, but what it is:
Before knowledge is reused: what is it? Before it is trusted: where did it come from? Before it is acted upon: who has authority? Before the outcome is forgotten: what happened?
"AuthOrigin doesn't need to know what the problem is. It needs to preserve the evidence from which the problem can be demonstrated — and the conditions under which a solution can be trusted."
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