Basis Lab

Watching a Model After Launch

When the Right Answer Moves

Last timeWhen the Inputs Move

The inputs moving is visible and usually harmless; the relationship between input and answer moving is invisible without labels and is what silently ruins a model.

Two different things can move

Last lesson watched the inputs. This lesson is about the distinction that

makes that watching useful, and it is the central idea of the course.

Two things can change between training and today. Which cases arrive can

change: more young customers, larger amounts, a new region. Or, for exactly

the same case, the right answer can change: the customer who would have repaid

two years ago now defaults, with identical inputs, because interest rates

moved.

The first leaves the model relationship intact. It is being asked about a

different mixture, and if it saw cases like these in training it will be fine.

The second makes the relationship wrong, and no amount of the same inputs

helps.

FIG 1The two movements, side by side
visible in the inputsvisible in the scoresthe learned relationshiptypical cause
the mixture of cases cha1111
the answer for a given c0002
both at once1103
Coded 1 for yes and 0 for no. The causes are coded: 1 is a new audience, a campaign or a new region, 2 is a change in the world such as prices, rules or behaviour, 3 is a large external event that does both. The second row is the whole problem of this lesson, and its first two columns being zero is what makes it so hard: there is nothing to see.

Why the second one is worse

Picture a fraud model. The inputs are amounts, times, device types, merchant

categories, and their distributions are exactly what they were last month. The

score distribution is unchanged. Volumes are normal, response times are

normal, nothing has errored.

Meanwhile a new fraud technique has appeared that the model was never trained

on, and transactions that it scores at 0.1 are the ones worth worrying about.

Every signal on the panel is green. The model is wrong on the cases that

matter and will remain wrong until the disputes arrive, which is six to twelve

weeks.

FIG 2What the panel sees, and what is actually happening
0.800.840.880.910.950.06.513.019.526.0weeks since launch
accuracy, known only much latereverything visible on the dashboard
The flat wobbling line is what the team watches, and it does exactly what it always did. The falling line is the truth, available only when the labels mature, which for this kind of decision is two to three months. By the time the lower line is known to have fallen, five months of decisions have been made on it, and the only way to have known earlier was to have been labelling a small sample all along.

There is a partial exception worth knowing. If the relationship moves in a way

that also changes the balance of answers, for instance if genuine fraud

becomes much more common, then the score distribution shifts and the panel

does say something. That is luck rather than coverage, and the cases where the

model is quietly wrong on a constant share of traffic produce nothing at all.

The lesson stops here

4 more paragraphs to go

You have read the opening. The rest of the argument, the problems that check whether it landed, and the lines worth keeping at the end all come with a plan.

The first lesson of every course in the library reads the whole way through, free, so you can see exactly what the rest of them are.

See the planThe contents

This is the reading half

Starting the course gives you your own copy of it. Every idea on every page has problems standing under it, marked with a reason rather than a tick, and any sentence you do not believe can be opened and argued with. None of that can happen on a page nobody owns.

The contents

The rest of this course

  1. 01What You Can Measure Without Labels
  2. 02When the Inputs Moveopening only
  3. 03When the Right Answer Movesyou are here
  4. 04Labels That Arrive Weeks Lateropening only
  5. 05The Model Changing Its Own Inputsopening only
  6. 06What Deserves an Alarmopening only
  7. 07Deciding to Retrainopening only
  8. 08The Failures That Make No Noiseopening only

Read alongside