Open Source Teams at Google Hit Hard by Layoffs: Was It the Algorithm?
quietus writes:
During the pandemic, Big Tech was booming and hiring new employees as fast as they could. With all that hubbub behind us, and an uncertain economic outlook, those Giants of the Internet are cautiously trimming some of that fat in preparation for leaner times.
That, at least, is the argument for the recent wave of lay-offs at Facebook (Meta), Twitter, Amazon, Stripe, SalesForce, Lyft, DoorDash and Carvana. It seems, though, that the recent layoffs at Google might have been a little different.
Instead of culling the recent hires, the trusted hands at open source teams, and those teams themselves, are being hit especially hard argues an opinion piece at El Reg.Chris DiBona, founder of Google's Open Source Program Office, Jeremy Allison, co-creator of Samba and Google engineer, Cat Allman, former Program Manager for Developer EcoSystems, and Dave Lester, Head of Google's open source security initiatives, are the main names being mentioned.
El Reg's observation might be a coincidence, however; and the way the layoffs are being executed kinda points to that. No exit interviews, but just people's access badges disabled, and firings by e-mail: at least one engineer got the message in the middle of his production shift. Which gave rise to an interesting speculation by former Google engineer Mike Knell:
Best theory I have is that an outside company was hired and given a "clean room" export from the HR systems to work with.
Stripped of identifying information and any demographic data that could incur a *direct* disciminatory bias in the results. They were then told to write code to determine which rows to cut from the dataset based on the output of some weighted formula designed to determine the "fireability" of that employee while maximising the savings achieved by the exercise. They then took the output of that algorithm, stack ranked the results (because Google just LOVES to stack rank things, especially people) and returned the top 12,000 employee IDs.
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