You're just guessing as much as anyone. Almost every generation in history has had doomers predicting the fall of their corner of civilization from some new thing. From religion schisms, printing presses, radio, TV, advertisements, the internet, etc. You can look at some of the earliest writings by English priests in the 1500s predicting social decay and destruction of society which would sound exactly like social media posts in 2025 about AI. We should at a minimum under the problem space before restricting it, especially given the nature of policy being extremely slow to change (see: copyright).
I'd urge you to read a book like Black Swan, or study up on statistics.
Doomers have been wrong about completely different doom scenarios in the past (+), but it says nothing about to this new scenario. If you're doing statistics in your head about it, you're wrong. We can't use scenarios from the past to make predictions about completely novel scenarios like thinking computers.
(+) although they were very close to being right about nuclear doom, and may well be right about climate change doom.
I'd like for you to expand your point on understanding statistics better. I think I have a very good understanding of statistics, but I don't see how it relates to your point.
Your point is fundamentally philosophical, which is you can't use the past to predict the future. But that's actually a fairly reductive point in this context.
GP's point is that simply making an argument about why everything will fail is not sufficient to have it be true. So we need to see something significantly more compelling than a bunch of arguments about why it's going to be really bad to really believe it, since we always get arguments about why things are really, really bad.
> which is you can't use the past to predict the future
Of course you can use the past to predict (well, estimate) the future. How fast does wheat grow? Collect a hundred years of statistics of wheat growth and weather patterns, and you can estimate how fast it will grow this year with a high level of accuracy, unless a "black swan" event occurs which wasn't in the past data.
Note carefully what we're doing here: we're applying probability on statistical data of wheat growth from the past to estimate wheat growth in the future.
There's no past data about the effects of AI on society, so there's no way to make statements about whether it will be safe in the future. However, people use the statistics that other, completely unrelated, things in the past didn't cause "doom" (societal collapse) to predict that AI won't cause doom. But statistics and probability doesn't work this way, using historical data about one thing to predict the future of another thing is a fallacy. Even if in our minds they are related (doom/societal collapse caused by a new technology), mathematically, they are not related.
> we always get arguments about why things are really, really bad.
When we're dealing with a completely new, powerful thing that we have no past data on, we absolutely should consider the worst, and of course, the median, and best case scenarios, and we should prepare for all of these. It's nonsensical to shout down the people preparing for the worst and working to make sure it doesn't happen, or to label them as doomers, just because society has survived other unrelated bad things in the past.
Ah, I see your point is not philosophical. It's that we don't have historical data about the effect of AI. I understand your point now. I tend to be quite a bit more liberal and allow things to play out because I think many systems are too complex to predict. But I don't think that's a point that we'll settle here.
