The Frame Problem
Representing change requires deciding what stays relevant and what can be ignored.
The Mechanism: The frame problem arose in artificial intelligence and philosophy: how can a system represent which facts change after an action and which remain unchanged? It highlights a challenge in formalizing context and relevance.
The Philosophical Pivot: Human beings often know what not to notice without being able to state a rule for every case. Common sense depends on background expectations that are difficult to encode completely.
The Horizon: Automated systems must decide what information is relevant to a task, and errors can arise when context is missing. This is a research challenge, not a proof that computation or AI is impossible.
People also frame situations selectively, often without noticing. The problem of relevance belongs to human judgment as well as artificial reasoning.
Every model draws a boundary around what it will treat as important.
A system's intelligence is shaped as much by what it ignores as by what it computes.
What am I treating as irrelevant simply because my current frame makes it difficult to see?