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It’s obviously intended to make a particular point — and one that’s politically supportive to her. The baseline isn’t zero, but this is clearly an example where a zero baseline would be silly: zero is not a relevant value of the vaccination rate.

The 95% top line is also not arbitrary: it’s the government target for vaccination, chosen because it’s thought to be high enough for herd immunity even to measles.

They’re most interested in trends over time (increasing) and perhaps in seasonal variation (more in summer).

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And if they’re talking about people who are So, how does this differ from, say, the IRD using statistical models to target people with higher probability of having committed tax fraud for auditing? The first is that the IRD is interested in auditing people who done but might do in the future. It has to make decisions about who to let into the country in the first place, and who to give extensions of visas, or grant residency. These decisions will have serious impacts on the lives of would-be immigrants — ranging from those who have an application for residency denied to those who don’t even bother applying because there’s no hope. There are at least three issues with the model: the ‘‘ issue is ‘racial profiling’.

Since Immigration NZ does make these sorts of decisions, do we want them to do it based on a statistical model? As a society, we’ve decided that some information just should not be used to make certain types of decisions — regardless of whether it’s genuinely predictive.

And some, like the Lightpath, that get used all the time.

Note: while it’s great that Auckland Transport publishes these data, the data would be easier to reuse if the names they used for each counter were consistent over time (eg: “Tamaki Dr” vs “Tamaki Drive”, or “Nelson Street Lightpath Counter Cyclists” vs “Nelson Street Lightpath Cyclists”) This graph comes from the Twitter account of Jill Hennessy, Victoria’s Minister for Health.

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There are some paths that are clearly used primarily by commuters, with more than twice the average traffic on a weekday vs weekend.

There are also some that are mostly used at the weekend, such as Matakana, Upper Harbour, and Mangere Bridge.

How much unnecessary government expenditure does it predict they will require? Are there relevant groups of people for whom the model is importantly less accurate — people from particular countries, people with or without family in NZ, etc — so that the costs of automated decision making aren’t justified by benefits.

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