Any metric is useful until it becomes a target.
In this case “revenue per employee” leads to :
- “who is below average”
- “oh, it’s R&D/legal/HR/…, bye bye”
- “wait, how do we make payroll?”
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Plus people/departments figure out ways to game the stat. even if it’s destructive.
A: “I handled the most number of calls this week! My stat is up!”
B: “Huh? You just answered, said ‘Fuck you bye!’ and hung up.”
A: “Who cares? Most number of calls!”
Or measuring programmers by lines of code.
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Lines of code is nearly my favourite example - the one where the programmers and QA teamed together to make very obvious bugs that were super easy to fix.
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These petty feuds should help with advertising revenue, we are watching a true genius at work /s
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Yes we are.
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In the meanwhile when he went after NPR…
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Just over 4% of people who visited the Twitter Blue sales website last month subscribed to the service, according to web traffic data viewed by Bloomberg.
It reports that 116,000 people signed up for Twitter Blue in March – a monthly subscription of $8 – compared to 2.6 million who visited its sales page, based on estimates from Similarweb, which analyzes internet traffic.
Even timeshares salespeople were like this after reading that
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Isn’t 4% conversion actually pretty good?
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We should retitle this thread - “not even with your dick!”
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From the cited Reuters article:
The sharing of sensitive videos illustrates one of the less-noted features of artificial intelligence systems: They often require armies of human beings to help train machines to learn automated tasks such as driving.
Since about 2016, Tesla has employed hundreds of people in Africa and later the United States to label images to help its cars learn how to recognize pedestrians, street signs, construction vehicles, garage doors and other objects encountered on the road or at customers’ houses. To accomplish that, data labelers were given access to thousands of videos or images recorded by car cameras that they would view and identify objects.
Tesla increasingly has been automating the process, and shut down a data-labeling hub last year in San Mateo, California. But it continues to employ hundreds of data labelers in Buffalo, New York. In February, Tesla said the staff there had grown 54% over the previous six months to 675.
Two ex-employees said they weren’t bothered by the sharing of images, saying that customers had given their consent or that people long ago had given up any reasonable expectation of keeping personal data private. Three others, however, said they were troubled by it.
That was out of twelve anonymized respondents.
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Not if it means that you are only making 12 million a year off of it, I assume
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… of course in most programming languages one could just put one word on each line 
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Or everything on one really long line.
