Optimization is a force of nature: it flows to the minimum of the objective it was given, and your wishes are not in that objective. Aim a wish at the descending ball — it slides right past, landing where the math says. Encode the wish into the objective and only then does the world move. That gap is the whole of alignment.
The dynamics are literal gradient descent on a fixed bowl f(x)=‖x−m‖²: each step x ← x − η·∇f drives x to the minimum m regardless of the wish, because the wish is not a term in f — a hope is not a force. The readout shows the outcome invariant to wish angle/force while ENCODED is off. Toggle ENCODE and the objective becomes f(x)=‖x−(m+wish)‖²; the minimum moves and the ball follows. Outcome-changes-iff-encoded is the checkable fact.
'Doesn't care / force of nature' is a figure: optimization is indifferent to preferences you did not write into the objective — it is not a physical force and not malice. The real, un-poetic lesson is value alignment: if you want it in the outcome, it has to be in the objective; wishing at the process does nothing. The bowl is a toy landscape, not a model of any specific system.