2026-10-03 04:36 UTC
We see a similar thing with LinkedIn AI content. Influencer A writes a post about AI. It has a probability C of being accurate. Influencer B reads that post with a probability P of spotting any errors or untruths before they write their own post propagating and compounding those errors.
The odds of reading anything accurate about "AI" on LinkedIn that has propagated through its Small World network are low.
I call this my theory of Social Transmission Accumulated Accuracy Risk.
Replies (1)
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@jasongorman@mstdn.business 2026-10-03 04:37
An example: Influencer A posts something about how agents can reliably regenerate complex software from the original specs in minutes. (That is extremely improbable.) Influencer B reads A's post and extrapolates that entire product designs can be tried out multiple times a day without anybody writing a line of code, and posts "Software engineering is dead!" Influencer C reads B's post and concludes "Don't bother learning to code, kids!" and advises everyone to train as plumbers And so on.