> To be fair, addiction is the problem of the users 

You're not wrong that it's an addiction but there's a big difference between a person being addicted to something and a society being addicted. The response should be different because the situation is different

  > You are ignoring

But if you're unwilling to have a nuanced take then there's no discussion to be had. You're just going to be yelling at me, someone who hates Zuckerberg. You're yelling at the wrong person

  > I prefer systems with a lot of people who get helped sufficiently to avoid hitting rock bottom in the first place.

  Scenario:
  There are 100 people starving

  Rankings of preferred situations:
  1) We feel it is morally just to feed everyone AND everyone gets fed
  2) Morals aside, everyone gets fed
  3) We feel it is morally just to feed everyone AND __N__ people get fed (N<100)
  4) Morals aside, N people get fed (N<100)
  5) We feel it is morally just to feed everyone BUT nobody gets fed
  6) Fuck the poor

We can rank these, right? We can even get more nuanced about the ranking (we can define N!) and argue about the weight of intent vs outcome, but I'm just proposing one ranking for the sake of making my point clear, not proposing one ranking as if it is the absolute objective ranking system and everyone that disagrees is dumb. The rankings are clearly subjective. But what's not subjective is that nuance exists. What is subjective is how we handle that nuance.

  > these undertakings are about promoting the benefactor

So I'm quite confused by your comment because it doesn't seem we disagree. Unless if you're saying that #2 in my list is equivalent to #6 (or anything that isn't #1 is equivalent). But I don't think that's what you're saying.

  > This has already been the case for at least my whole lifetime.

So I see EA as a popular one of those stories. One that people can reinforce. Makes the world simpler than it actually is: climb the ladder, make money at whatever cost, there's no harm that you can do that can't be offset by giving it all away at the end. It is a vast over simplification and is inconsistent logic. If they used their own logic then they'd recognize helping people now also results in compounding effects. You fix the problems now, while they are small and manageable, rather than kicking the can down the road. Maintenance is a lot easier and cheaper than repair. But it also requires us to be nuanced and reflect on ourselves [0]

[0] there seems to be a great irony that those leading these big AI companies are not themselves able to deeply reflect on their own actions, yet ask the AI to. How can you design something that you aren't intimately familiar with?

  > it's not out of principle.

I'd certainly rather things be done out of principle, but depending on what question you're concerned with that might not matter. There's also a clear hierarchy, but motivations are distinct from effect. The inverse of this is that lots of harm has happened from people with the best of motivations. I'd wager most evil in the world is created by men who would see themselves as good.

With Zuckerberg I think it isn't too hard. Clearly this is a business move, not a moral one. The motivation is wrong, BUT the effect is good. I think more open source models is better for the world. Closed source is also a business move and limits innovation as well as prevents people from interrogating safety. But there's valid arguments on either end.

My point more is that we can be nuanced. We should be nuanced. The world isn't black and white. The people making these decisions are neither demons nor gods and shouldn't be treated as such. My biggest fear is that if we resort to criticizing no matter what then those in power will just learn to ignore us. If they can do no good and only do wrong then there's no reason for them to do good (besides morals, but let's not pretend that's enough, even if it should be)

There are many non-intuitive things, hence that pitfalls page I linked. You can't just deflect and say that the user is "holding it wrong". If it is difficult and unintuitive in how to "hold" it correctly, that's a design problem, not a user problem.

Despite bash being a terrible language, I still use it on a daily basis because it is useful. But don't conflate these things.

  > I think minority do

[0] https://mywiki.wooledge.org/BashPitfalls

Edit:

[1] Fuck it, here's the lazy search: https://github.com/search?q=%22Bash(find%20*)%22&type=code

  > USB-A has many variants
  > especially when they aren’t even labeled period

https://www.corsair.com/us/en/explorer/diy-builder/storage/u...

  > Reviewers know what venues they are reviewing for, and attentive ones will adapt their review based on the prestige of the venue.

I don't think it's constable that luck plays a big role. Do we need you do a third NeruIPS study to convince people?

The real problem is that we don't actually know if an idea is good or not until it's had more time to be explored and studied. A great example of this is diffusion models. There's 6 years between Sohl-Dickstein's paper and Jonathan Ho's. All because GANs got popular, so only a few people kept looking at diffusion until one person scaled it. There's hundreds of cases like that, including attention and resnets (I'll defend Schmidhuber's Highway Nets here). So much fruitful research gets cast away for no good reason.

A reviewer can't ever determine if research is good or impactful. It's impossible to do by just reading a paper. So that needs to be taken out of the equation. What a reviewer can do, though, is determine if a paper is bad or fraudulent. So IMO, we should publish anything that isn't fraudulent. Let time tell us the impact, because history tells us we're not very good at figuring that out ourselves

  > because there are just so many papers at leading AI conferences

A low acceptance rate is unhealthy, especially in conferences (1 round of review). Papers just get recycled to the next conference, which, as is easy to model, creates an exponential feedback loop. It doesn't explain all the papers submitted, but it sure can explain a lot. Too much rejection is like shooting yourself in the foot.

Not to mention that it's just easy to reject works. All works are flawed, especially works that are in less mature domains. I see plenty a paper get rejected for lack of money. "Not enough experiments" is an common critique that's used inappropriately (along with the highly subjective "not novel enough" one) because it's fine to always want more but no lab has infinite funding. It is used lazily. The question shouldn't be about if your favorite benchmark is used, it should be if there isn't enough evidence to support the hypothesis or not. A mature domain where thousands of people work in it, yeah, that needs stronger evidence. A niche domain where dozens of people work in? Not as many required. Rejecting them ultimately slows down the progress of science because you require any new idea to outperform mature ideas. Ironically killing novelty as no one is going to, or even could (publish or perish), spend all the time and money to mature a niche all on their own.

  > you’re handing the power to