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IMTrick t1_j91r52o wrote

From where I'm sitting, this is a really weird take. I get that it's upsetting to see the culture of an online space destroyed; that's the reason I rarely visit Twitter any more. It is, indeed, a festering shithole these days.

The idea that regulation would somehow have prevented that, though, is dubious. It's just as likely that regulation would have prevented the culture the writer enjoyed from ever appearing in the first place.

The problem here isn't a lack of regulations; it's a simple matter of one guy being in charge of a popular platform and enacting his own agenda on it (in addition to that one guy having a cult following that includes a disproportionate number of toxic assholes). It's unfortunate that Musk's priority with Twitter seems to mainly be to piss off as many people as possible for clicks (a tactic familiar to anyone who's followed other media for any length time), but how could you possibly regulate that in a way that wouldn't stifle innovation elsewhere?

I just don't see how any attempt to use regulations to enforce user behavior at a government would be anything but a dismal failure. It'd be subject to the priorities of whoever's in charge at the time, and it seems to me that this is one of those cases (and as a flaming liberal it pains me to say this out loud) where free market forces would do far good more in the long term than any legislation would. If Twitter continues to be a shithole, people will continue to create alternatives, and users will continue to flee.

This all just sounds like it's treating Twitter as a platform that's too big to fail, so it must be "fixed" rather than to let it go the way of countless social media media platforms before it for which there were better alternatives. We don't need to force Twitter to be better; we just need to let someone else do it.

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TeaKingMac t1_j9492li wrote

If you read the second half of the article, it's not really about Twitter, it's about oversight of algorithms generally.

Author is basically arguing for government creating an external "machine learning ethics" oversight committee and/or open sourcing everyone's algorithms to public entities for bias checking.

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