If you look into a bit more history on social justice/equality problems, you would see we have actually made many many progress (https://gcdd.org/images/Reports/us-social-movements-web-timeline.pdf), but not enough as the bar was so low. These also have made changes in our law. Before 1879, women cannot be lawyers (https://en.wikipedia.org/wiki/Timeline_of_women_lawyers_in_the_United_States). On war, I don't have too much knowledge myself, so I will refrain from commenting for now. It is also my belief that we should not stop at attempt, but attempt is the first step (necessary but not sufficient), and they have pushed to real changes as history shown, but it will have to take piles of piles of work, before a significant change. Just because something is very hard to do, does not mean we should stop, nor there will not be a way (just like ensuring there is humanity in the future.) For example, we should not give up on helping people during war nor try to reduce wars in the first place, and we should not give up on preventing women being raped. In my opinion, this is in a way ensuring there is future, as human may very well be destroyed by other humans, or by mistakes by ourselves. (That's also why in the AI safety case, governance is so important so that we consider the human piece.)

As you mentioned political party - it is interesting to see surveys happening here; a side track - I believe general equality problems such as "women can go to school", is not dependent on political party. And something like "police should not kill a black person randomly" should not be supported just by blacks, but also other races (I am not black). 

Thanks for the background otherwise. 

A recent thought on AI racing - it may not lead to more intelligent models necessarily especially at a time when low hanging fruits are taken and now more advanced breakthroughs need to come from longer term exploration and research. But this also does not necessarily mean that AI racing (particularly on LLMs in this context, but I think generally too) is not something to be worried about. It may waste a lot of compute/resources to achieve only marginally better models. Additionally the worst side effect of AI racing to me is the potential negligence on safety mitigations, and lack of safety focused mindset/culture.

If you meant for current LLMs, some of them could be misuse of current LLM by humans, or risks such as harmful content, harmful hallucination, privacy, memorization, bias, etc. For some other models such as ranking/multiple ranking, I have heard some other worries on deception as well (this is only what I recall of hearing, so it might be completely wrong).

This aligns similarly with my current view. Wanted to add a thought - current LLMs could still have unintended problems/misalignment like factuality or privacy or copyrights or harmful content, which still should be studied/mitigated, together with thinking about other more AGI like models (we don’t know what exactly yet, but could exist.) And a LLM (especially a fine tuned one), if doing increasingly well on generalization ability, should still be monitored. To be prepared for future, having a safety mindset/culture is important for all models.

I also wish to see more safety papers. I guess/from my experience that it might also be - really good quality research takes time, and the papers so far from them seems pretty good. Though I don’t know if they are actively withholding things on purpose which could also be true - any insider/sources for this guess?

I think this is conditioning on one problem with one goal, but I haven’t thought about the other good collectively (more of a discussion on consequentialism).

For best of personal ability, I think the purpose is to distinguish what one can do personally, and what one can do to engage collaboratively/collectively, but I need to think through that better it seems, so that is a good question.

My reason on the na is: have intention, no execution/enough execution, did good is more like an accident, which is the same with no intention, no execution, and did good.

When thinking about deontology and consequentialism in application, I was trying to rate morality of actions based on intention, execution, and outcome. (Some cells are "na" as they are not really logical in real world scenarios.)

In reality, to me, it seems executed "some" intention matters (though I am not sure how much) the most when doing something bad, and executed to the best ability matters the most when doing something good.

It also seems useful to me, when we try to learn about applications of philosophy from law. (I am not an expert though in neither philosophy nor law, except worked for lawyers in securities and finance law for a few years, so these may contain errors.)

(Mentioned some of these in our chat, but allow me to be repetitive)

On first: I don't think efforts to reduce rape or discrimination needs 100% abolition, but working towards that currently has huge return at this point of history. Education has snowball effect as well. Just because it is hard to achieve 100%, does not mean there should not be efforts, nor impossible at all. In fact, it is something that is rarely worked on alone; for example, one strategy might actually be to bring up education generally, or economic disparity, and during this process, teach people how to respect other people. 

On second: We likely need good value system to align AI on, otherwise, the only alignment AI would know is probably not to overpower the most powerful human. But that does not seem to be the successful outcome of "aligned AI". I think there are a few posts recently on this as well.

Third: I have seen many people having this confusion/mixed up: rape play/bdsm is consensual, and the definition of rape is non-consensual. Rape is purely about going against the person's will. If you view it as murder it might be more comparable, but in this case, it is historically one group on to another group due to biological features and power differences that people cannot easily change on, though also a lot of men to men. In my view, it is worse than murder because it is extreme suffering, and that suffering will carry through the victims' whole lives, and many may end with suicide anyways.

Otherwise, I am glad to see you thinking about these and open to discussion.

Reminded me of the complex systems chapter from a textbook (Center for AI Safety)

https://www.aisafetybook.com/textbook/complex-systems

Equity vs equality considerations (https://belonging.berkeley.edu/equity-vs-equality-whats-difference):

• What caused the differences in outcome? 
  • Historical factors: should definitely apply equity. Conditioning on history is important and corrective efforts are needed.
• Is the desired outcome a human "necessity"?
  • The definition of necessity may be tricky, or even differ by culture. Generally in the US, if it is something like healthcare, or access to education, should move towards/apply equity.