WEBVTT

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A description that works for what we see now may still fail to predict what happens

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after an action.

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If hidden conditions have different consequences, treating them as the same can hide a

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difference that matters.

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Watch which distinctions are needed to predict change, and which details can safely be

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left out.

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Start a fresh run.

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The observer receives zero: the lamp is off.

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That reading fits either hidden configuration u or hidden configuration v.

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We do not get a cutaway showing which one is actual.

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The letters name hidden configurations; zero and one name lamp outputs.

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Zero means off and one means on.

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We want to predict the lamp after a button called PULSE.

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Does the current reading tell us enough?

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The rules are supplied with this teaching model.

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If the device started in u, PULSE would take it to w.

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The lamp is one in w.

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If it started in v, PULSE would leave it in v.

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The lamp there is zero.

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These are calculations from the known rule.

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We have not pressed the button on the actual device.

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Before comparing the results, predict the answer.

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Given only the received zero, must the lamp be on after PULSE, must it be off, or is the result still undetermined?

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The two possible runs start with the same lamp output, zero.

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Starting in u gives w and then output one.

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Starting in v gives v and then output zero.

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So the result is still undetermined.

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The current reading has not selected one of those starting configurations.

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No predicted output has become a new received reading.

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Now build prediction groups for all four configurations in the model.

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Configurations can share a group only when the group supports the same future lamp predictions for the available buttons.

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We must give u and v different groups: PULSE is a concrete reason to separate them.

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These boxes are a description of possibilities.

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Splitting a box does not create a new physical configuration.

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Compare the other two configurations, w and z.

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Both have output one.

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They are not candidates for our earlier zero reading; we are comparing model cases to finish the prediction groups.

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PULSE leaves w at w and z at z.

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Their lamps stay on.

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Press PULSE again and the same thing happens.

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Any number of PULSE presses keeps both outputs one.

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There is one other available button: RESET.

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Its known rule sends every configuration to u.

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Starting in w or starting in z, the first RESET therefore brings both cases to that same state u.

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Every finite sequence either has no RESET, or has a first RESET.

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Without RESET, we just checked the repeated PULSE case.

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With RESET, both cases reach u together; the same later buttons then give the same states and outputs.

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That is why w and z can stay together.

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The full model has four configurations.

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For lamp predictions using PULSE and RESET, three groups suffice: u, v, and w-or-z.

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Members of each group are predictively equivalent: they make the same specified future predictions.

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The combined w-or-z group reports one.

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PULSE keeps it in that group; RESET takes it to the u group.

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From u, PULSE actually goes to w.

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Its group destination is called w-or-z because that label groups w with z; it does not mean the button might send u to z.

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The other rows are shown too, so we can update the group without choosing a member inside it.

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But the group cannot answer every question.

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If the task were to report the exact configuration name, w or z would matter.

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Our grouping preserves this lamp-prediction task, not all possible information.

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Return to the fresh run.

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The only received reading is still zero.

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All the button presses we traced were hypothetical model cases.

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The actual device has not been operated.

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We now know why u and v need separate prediction groups.

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Does the observer know which of those groups its device occupies?

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No. Both u and v still fit the evidence.

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A table can show which difference matters without giving us an experiment that obtains it.

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Later episodes ask what observations and actions are actually available.

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u and v look the same now but must be separated for future lamp predictions.

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w and z are different configurations that can stay together for this specified task.

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A useful description preserves the distinctions the task needs.

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We have not assigned probabilities or measured the cost of finding out.

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Episode four asks how uncertainty and usefulness differ.
