Have you ever thought why the flight attendants bother giving safety instructions? Do you listen to them?
Flight attendants are stuck. They can’t go off script.
Probably a long time ago, there were tests on how to deliver those safety instructions to passengers.
The current way was tested not with busy passengers needing to get somewhere, but people recruited for the purpose. It probably fared better than anything else.
Yet, when applied in real life, it sucks. We don’t listen to what they say.
I see the same mistake made in data science: people test their model with real data, but not in production.
I used to tell my classes a story of a big online retailer developing a much better version of their recommender — “customers who bought this, also bought that” type of thing.
With the new recommender, fewer clicks were necessary to understand the set of items the customer wanted to buy.
Before rolling out, they A/B tested it — luckily.
To their surprise, people exposed to the new version, were closing their browser more quickly without buying!
Some of them were logged in, so they decided to investigate.
It turns out, customers were creeped out by the eerie accuracy of the new recommender. They left the website, afraid of what else the retailer would find out about them.
The retailer went back to the old version.
It doesn’t matter how enthusiast data scientists are about the model.
Without testing in production, it counts for nothing.
Why, statistically speaking, cryptocurrencies are for losers.
”The problem here is that the amount of actual money you can get out of a cryptocurrency equals the amount of actual money that has been put in, minus the actual costs of mining. So the big picture is that although there may be winners, in aggregate the system loses money.”
If you follow Dutch news, you probably heard of a big scandal with the tax office.
It boils down to discrimination and racism towards citizens with a double nationality The consequences of the discrimination were often catastrophic. The previous Dutch government resigned on it.
The scandal reminded me of a manager at a financial institution.
The manager (year 2015, before GDPR) was interviewing for the department I was in.
One of the questions I asked was about integrity. Could they recall a situation in which they did the right thing, regardless of outside pressure.
“Oh yes, a couple of months ago, somebody from the mortgage department came in, asking if we could associate countries with last names.”
“I said we could, but why? His answer was: people from certain countries default more often on their mortgage. The company could benefit greatly from such a model.”
“Well, in that case go f* yourself”
(They didn’t use the f* word, it’s a poetic license).
That no allowed thousands of people to buy a place to live.
That no saved the company from the public shame the Dutch tax office is going through right now — and probably millions in claims!
Companies can do great things with data. They can also do awful things with it.
The difference between the two is drawing a line and saying no.
I was doing some math with my son and I wanted to highlight the power of compound (the greatest force in the universe, according to fellow physicist Albert Einstein!).
He then asked me where can you get a 10% interest rate.
