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Every company with algorithmic recommendations will run experiments to try to improve it according to various metrics. This is the well known knowledge in the i
by im3w1l 4y ago
Every company with algorithmic recommendations will run experiments to try to improve it according to various metrics. This is the well known knowledge in the industry, not a conspiracy theory.
Trying to improve peoples chance of getting a job as opposed to something lame like "engagement" is laudable. The key question is how big the difference between the groups. If the difference is marginal, then I think the knowledge justifies it. This will lead to more people getting jobs in the future, so the total utility increases. But if it was night and day, and they really fucked some people over, then it was unethical.
- awb 4y ago> The key question is how big the difference between the groups. 2x increase in job opportunities. > They found that relatively weak social ties on LinkedIn proved twice as effective in securing employment as stronger social ties.
- deleted 4y ago[deleted]
- im3w1l 4y ago> A year after connecting on LinkedIn, people who had received more recommendations for moderately weak-tie contacts were twice as likely to land jobs at the companies where those acquaintances worked compared with other users who had received more recommendations for strong-tie connections. That's one piece of the puzzle but not the whole thing. It's not the same as saying they got 2x more job opportunities. People can add friends outside of the recommendations for instance. Or they may be added by the other person. I tried to quickly skim the paper just now but I was unable to find the details.
- awb 4y agoTrue, but wouldn’t both cohorts be expected to add connections manually in roughly the same amounts?