TL;DR it's statistical turtles all the way down
-
-
This may seem navel-gazey, but it’s getting at another of McLuhan’s points. We don't recognize new media when we first encounter it. We only see the old media format inside the new media container, so the new format alters the way we think without us even realizing it's happening
1 reply 0 retweets 1 likeShow this thread -
As new media formats extend our senses, we also fail to recognize how much of ourselves we pour into them. We don't realize they're extensions of us, and we become infatuated with them, much like Narcissus fell in love with his own reflection.
1 reply 0 retweets 0 likesShow this thread -
It’s easy to see this happening to various degrees to social media users who get invested in their on-site personas, but like I said, I’m more interested in talking about how this applies to data work.
1 reply 0 retweets 0 likesShow this thread -
I recommend thinking about metrics as a form of media, a new technology that extends and alters the senses of a business. They work as mental prosthetics for decision makers, helping them quickly understand things about a company that they otherwise would struggle to summarize.
1 reply 1 retweet 1 likeShow this thread -
They also abstract the company's performance from the realities of the end users that the company makes decisions on behalf of. People become OBSESSED with metrics, so eager to move them that they forget their product is being used by people with particular goals in mind.
1 reply 0 retweets 1 likeShow this thread -
Katie Bauer! Retweeted Luke Wroblewski
Whatever the original purpose of the product was, it's quickly deprioritized in favor of getting users to do stuff that will cause the trend line of a metric (probably revenue or DAU) to go up and to the right. That's how you get stuff like this.https://twitter.com/LukeW/status/1327349136702672897 …
Katie Bauer! added,
1 reply 0 retweets 0 likesShow this thread -
McLuhan doesn't really seem to be describing this progression of media and ensuing fragmentation as a problem per se, more as an inevitable process. But even though he's not explicitly negative, it does leave me feeling a little ambivalent about my profession
1 reply 0 retweets 0 likesShow this thread -
A data scientist's job is to quantify things, after all, and quantification enables segmentation and fragmentation. Perhaps my solace should be in the fact that in order for things to be segmented, they first have to be understood as continuous.
1 reply 0 retweets 1 likeShow this thread -
Data scientists and the metrics they make can be a unifying force. Consistent measurement allows everyone to be on the same page and move in the same direction. Creating metric is creating a tool to direct a company's focus.
1 reply 0 retweets 3 likesShow this thread
Directing focus at the right things (or as close to right as possible) might be the most difficult and important part of a DS's job. It's worth taking seriously.
-
-
Replying to @imightbemary
V. true, but depends to some extent on everyone having a min ability to think rationally and in an unbiased manner. A powerful tool, but often gets overshadowed by politics or [benign] prejudices.
0 replies 0 retweets 0 likesThanks. Twitter will use this to make your timeline better. UndoUndo
-
-
-
Thanks. Twitter will use this to make your timeline better. UndoUndo
-
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.


Can't move without em