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Comment by gruez | Hacker News Reader

>That's quite an assumption to make. The very famous example of data tracking and creepy correlations is the story about the supermarket sending baby ads to a household based on nothing more than their purchasing habits.

While a fun anecdote, it really shouldn't be taken seriously as something that actually happened.

https://medium.com/@colin.fraser/target-didnt-figure-out-a-t...

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Did you actually read that Medium post? It's idle FUD and speculation that the author of the original 2012 Forbes article lied about the Target incident, without anything to substantiate that claim. It's also evidently written by someone working in data science at Meta, who would naturally have incentive to deny the reality of their industry.

Most of the Medium comments are calling them out on this:

>Title: "Target didn’t figure out a teenager was pregnant before her father did, and that one article that said they did was silly and bad." A clear assertion. A solid claim. One of the first paragraphs: "I won’t belabor this since we can’t actually know, but the anecdote about the father calling the store and talking to the manager is probably just not true. " So, a person who contradicts himself right in the beginning uses articles that are being hyperbolic as proof that the articles got it all wrong. Smells a bit like double standards, no? And the point of the conversation is less about accuracy of the findings and more about such models being in place. I mean, Facebook did this, right? https://www.snopes.com/fact-check/facebook-categorize-users-... And I'm not sure but there was this little company, very obscure, not sure anyone heard of it. Cambridge Analytica? Again, very obscure.

The target one always seemed like bullshit to me. They don’t have any magic algorithms. There were likely some hard tells that she was pregnant. As in something like a doctor’s office told them.

Or they just sent the same mailer to anyone with a female name popular in the last 40 years.

After all, at any given time, like 11% of women are either pregnant, will soon become or have recently been pregnant.

As someone who recently had a kid, I guarantee you’ll get flooded with very targeted baby stuff quickly. Not just fliers, but literal product samples.

I assume insurance or something sells the data.

I worked in computer infra stuff at Target at the time.

For one, they were incredibly paranoid about customer data privacy at the time, because of the famous incident of an unknown entity siphoning off data from some of their in store payment terminals for an unknown length of time. They instituted barriers and strict need to know basis access to everything touching customer history.

The amount of internal systems and departments that would have had to cooperate in order to start trying to sell a customer pregnancy related products because another arm of the company detected an individual customer was pregnant just boggles my mind, it could not and would happen at Target.

>Did you actually read that Medium post? It's idle FUD and speculation that the author of the original 2012 Forbes article lied about the Target incident, without anything to substantiate that claim. It's also evidently written by someone working in data science at Meta, who would naturally have incentive to deny the reality of their industry.

Did you? From the article:

>[...]The Forbes writer who rehashes the anecdote even describes it as “so good that it sounds made up.” Indeed.

>But this is an easy criticism and beside the point, so for the remainder of this article, let’s suppose that the anecdote is true.

The bulk of the objections in the article are that a single instance of Target correctly predicting a pregnancy isn't enough evidence to conclude they have some sort of a galaxy-brained AI that can predict pregnancies before the mothers even know. It's far more plausible it randomly guessed someone was pregnant, and got lucky.

The comment you quoted has the same issue. It gets way too hung up on the first part, ignores everything else the author wrote, and then tries to move the goalposts to "the conversation is [...] more about such models being in place". That's a huge cope. It's fairly obvious how concerned we should be about such models is proportional to how accurate they are, and the author is trying to harness that with the Target anecdote. Nobody would care if the story was "24 year old man got sent ads for Zyn, without telling Target that he smoked".

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