I agree with RL agents being misaligned by default, even more so for the non-imitation-learned ones. I mean, even LLMs trained on human-generated data are misaligned by default, regardless of what definition of 'alignment' is being used. But even with misalignment by default, I'm just less convinced that their capabilities would grow fast enough to be able to cause an existential catastrophe in the near-term, if we use LLM capability improvement trends as a reference. 

Thanks for this post. This is generally how I feel as well, but my (exaggerated) model of the AI aligment community would immediately attack me by saying "if you don't find AI scary, you either don't understand the arguments on AI safety or you don't know how advanced AI has gotten". In my opinion, a few years ago we were concerned about recursively self improving AIs, and that seemed genuinely plausible and scary. But somehow, they didn't really happen (or haven't happened yet) despite people trying all sorts of ways to make it happen. And instead of a intelligence explosion, what we got was an extremely predictable improvement trend which was a function of only two things i.e. data + compute. This made me qualitatively update my p(doom) downwards, and I was genuinely surprised that many people went the other way instead, updating upwards as LLMs got better. 

I've gotten push-back from almost everyone I've spoken with about this

I had also expected this reaction, and I always thought I was the only one who thinks we have basically achieved AGI since ~GPT-3. But looking at the upvotes on this post I wonder if this is a much more common view. 

My first impression was also that axis lines are a matter of aesthetics. But then I browsed The Economist's visual styleguide and realized they also do something similar, i.e. omit the y-axis line (in fact, they omit the y-axis line on basically all their line / scatter plots, but almost always maintain the gridlines). 

Here's also an article they ran about their errors in data visualization, albeit probably fairly introductory for the median LW reader.

Strong upvoted. I was a participant of AISC8 in the team that went on to launch AI Standards Lab, which I think counterfactually would not be launched if not for AISC.

This seems to be another one of those instances where I wish there was a dual-voting system to posts. I would've liked to strong disagree with the contents of the post without discouraging well-intentioned people from posting here. 

I feel like a substantial amount of disagreement between alignment researchers are not object-level but semantic disagreements, and I remember seeing instances where person X writes a post about how he/she disagrees with a point that person Y made, with person Y responding about how that wasn't even the point at all. In many cases, it appears that simply saying what you don't mean could have solved a lot of the unnecessary misunderstandings.

I'm curious if there are specific parts to the usual arguments that you find logically inconsistent.