I see a lot of talk with digital people about making copies but wouldn't a dominant strategy (presuming more compute = more intelligence/ability to multitask) be to just add compute to any given actor? In general, why copy people when you can just make one actor, who you know to be relatively aligned, much more powerful? Seems likely, though not totally clear, that having one mind with 1000 compute units would be strictly better for seeking power than 100 minds with 10 compute units each.
For example, companies might compete with one another to have the smartest/most able CEO by giving them more compute. The marginal benefit of more intelligence might be really high such that Tim Cook being 1% more intelligent than Mark Zuckerberg could mean Apple becomes dominant. This would trigger an intense race for compute. The same should go for governments. At some point we should have a multipolar superintelligence scenario but with human minds.
That seems true for many cases (including some I described) but you could also have a contingent of forward-looking digital people who are optimizing hard for future bliss (a potentially much more appealing prospect than expansion or procreation). Seems unclear that they would necessarily be interested in this being widespread.
Could also be that digital people find that more compute = more bliss without any bounds. Then there is plenty of interest in the rat race with the end goal of monopolizing compute. I guess this could matter more if there were just one or a few relatively powerful digital people. Then you could have similar problems as you would with AGI alignment. E.g. infrastructure profusion in order to better reward hack. (very low confidence in these arguments)
One thing that seems interesting to consider for digital people is the possibility of reward hacking. While humans certainly have quite a complex reward function, once we have full understanding of the human mind (having very good understanding could be a prerequisite to digital people anyway) then we should be able to figure out how to game it.
A key idea here is that humans have built-in limiters to their pleasure. I.e. if we eat good food that feeling of pleasure must subside quickly or else we'll just sit around satisfied until we die of hunger. Digital people need not have limits to pleasure. They would have none of the obstacles that we have to experiencing constant pleasure (e.g. we only have so much serotonin, money, and stamina so we can't just be on heroin all the time). Drugs and video games are our rudimentary and imperfect attempts to reward hack ourselves. Clearly we already have this desire. By becoming digital we could actually do it all the time and there would be no downsides.
This would bring up some interesting dynamics. Would the first ems have the problem of quickly becoming useless to humans as they turn to wireheading instead of interacting with humans? Would pleasure-seekers just be kind of socially evolved away from and some reality fundamentalists would get to drive the future while many ems sit in bliss? Would reward-hacked digital humans care about one another? Would they want to expand? If digital people optimize for personal 'good feelings' probably that won't need to coincide with interacting with the real world except so as to maintain the compute substrate, right?
I did my masters' thesis evaluating Kremer's paper from the 90's which makes the case for the more people->more growth->more people feedback loop. It essentially supports Ben's post from awhile ago (https://forum.effectivealtruism.org/posts/CWFn9qAKsRibpCGq8/does-economic-history-point-toward-a-singularity) [fyi I did work with ben on this project] in arguing that, with radiocarbon data (which I hold is much better than the guesstimate data Kremer uses), the more people->more growth relationship doesn't seem to hold. In terms of population it seems growth was much less steady than previously assumed. There are basically a few jumps, lot's of stagnation (e.g. China's population seems to have stagnated for thousands of years after the Neolithic revolution), and no clear overall pattern in long-term growth until the past few hundred years.
There are tons of caveats to my results listed in the thesis and I haven't read your paper so I'm not sure how much it even matters but I hope this contributes something! I'll add one more caveat: The paper is not super well-done (hence my previous hesitancy to post). I was sick for much of my thesis-writing period and also working part-time so much of it was rushed through toward the end. If it seems useful I can dredge up my notes on what I think might be wrong with it and send you the data (I actually have decently clean replication files in R). If I remember correctly the main results all hold it's mostly just minor things which need fixing. I've been meaning to clean it up and post it properly but I'm not sure whether that's ever going to happen, hence my posting it now.
With all that in mind, here's the thesis! https://docs.google.com/document/d/1pVzrTikeoRRO3WvU5x01nOEyf_USPUg-FcrqTGwUVR8/edit#
Feel free to reach out if you'd like to have a chat about this!
Cool thanks for the feedback everyone! I haven't done much thinking about root cause vs symptoms but I agree that especially with mental health it does seem right that 'root cause' isn't really a useful term given the complexity.
I changed up that last recommendation a bunch to get rid of symptom/root cause dichotomy:
"[revised] Try a bunch of other things. There are a lot of medications and pills you can take which have relatively low downsides and which can potentially be game-changers. This includes things like antidepressants, various supplements, nootropics, or other medication. Again, it's probably worth thinking of these as abnormally good lottery tickets. Expect most to fail but eventually something might really work. [see comments section for more on how to think about treating symptoms vs root causes]"
Oh thanks! I'll update that
Oh yeah, I think you're right on that! I shouldn't have been so down on symptom-reducing treatment. It does seem clearly better to fix root causes but given they can be so hard to fix it can often be the case that the best solution is to treat symptoms (and in some cases, like mental health, that can help improve root cause as well). I'll change that language so it's more positive on those
Yeah, maybe I should change some text... but I guess I have assumption built in that when finding papers which seem relevant you'd be reading the abstract, getting a basic idea of what they're about, and then adjusting search terms.
The reason having a pile of papers is useful is because the value of papers is extremely uneven for any given question and by having a pile you get a better feel for the range of what people say about a topic before diving into one perspective. Wrt the first point I'd argue that in most cases there are one or two papers which would be perfect for getting an overview. Reading those might be 100x more valuable than reading something which is just kind of related (what you are likely to find on the first search). If that's true it's clearly worth spending a lot of time looking around for the perfect paper rather than jumping into the first one you find. Obviously this can be overdone but I expect most people err toward too little search. Note that you might also find the perfect paper by skimming through an imperfect one. I tend to see this as another way of searching as you can look for that without actually 'reading' the paper, just by skimming through their lit review or intro.
Yeah, this would be nice to have! It's a lot of text to digest as it is now and I guess most people won't see it here going forward
I don't work at Rethink Priorities but I couldn't resist jumping in with some thoughts as I've been doing a lot of thinking on some of these questions recently
Thinking vs. reading. I’ve been playing around with spending 15-60 min sketching out a quick model of what I think of something before starting in on the literature (by no means a consistent thing I do though). I find it can be quite nice and help me ask the right questions early on.
Self-consciousness. Idk if this fits exactly but when I started my research position I tried to have the mindset of, ‘I’ll be pretty bad at this for quite a while’. Then when I made mistakes I could just think, ‘right, as expected. Now let’s figure out how to not do that again’. Not sure how sustainable this is but it felt good to start! In general it seems good to have a mindset of research being nearly impossibly hard. Humans are just barely able to do this thing in a useful way and even at the highest levels academics still make mistakes (most papers have at least some flaws).
Optimal hours of work per day. I tend to work about 4-7 hours per day including meetings and everything. Including only mentally intensive tasks I probably get around 4-5 a day. Sometimes I’m able to get more if I fall into a good rhythm with something. Looking around at estimates (Rescuetime says just ~3 hours per day average of productive work) it seems clear I’m hitting a pretty solid average. I still can’t shake the feeling that everyone else is doing more work. Part of this is because people claim they do much more work. I assume this is mostly exaggeration though because hours worked is used as a signal of status and being a hard worker. But still, it's hard to shake the feeling.
Learning a new field. I just do a lot of literature review. I tend to search for the big papers and meta-analyses, skim lot’s of them and try to make a map of what the key questions are and what the answers proposed by different authors are for each question (noting citations for each answer). This helps to distill the field I think and serves as something relatively easy to reference. Generally there’s a lot of restructuring that needs to happen as you learn more about a topic area and see that some questions you used were ill-posed or some papers answer somewhat different questions. In short this gets messy, but it seems like a good way to start and sometimes it works quite well for me.
Hard problems. I have a maybe-controversial take that research (even in LT space) is motivated largely by signalling and status games. From this view the advice many gave about talking to people about it sounds good. Then you generate some excitement as you’re able to show someone else you’re smart enough to solve it, or they get excited to share what they know, etc. I think if you had a nice working group on any topic, no matter how boring, everyone would get super excited about it. In general, connecting the solution to a hard problem to social reward is probably going to work well as a motivator by this logic.
Emotional motivators. I’ve been thinking a lot recently about what I’m calling ‘incentive landscaping’. The basic idea is that your system 2 has a bunch of things it wants to do (e.g. have impact). Then you can shape your incentive landscape such that your system 1 is also motivated to do the highest impact things. Working for someone who shares your values is the easiest way to do this as then your employer and peers will reward you (either socially or with promotions) for doing things which are impact-oriented. This still won’t be perfectly optimized for impact but it gets you close. Then you can add in some extra motivators like a small group you meet with to talk about progress on some thing which seems badly motivated, or ask others to make your reward conditional on you completing something your system 2 thinks is important. Still early days for me on this though and I think it’s a really hard thing to get right.
Typing speed. At least when I'm doing reflections or broad thinking I often circumvent this by doing a lot of voice notes with Dragon. That way I can type at the speed of thought. It’s never perfect but ~97% of it is readable so it’s good enough. Then if you want to actually have good notes you go through and summarize your long jumble of semi-coherent thoughts into something decent sounding. This has the side of effect of some spaced repetition learning as well!
Tiredness, focus, etc. I’ve had lot’s of ongoing and serious problems with fatigue and have tried many interventions. Certainly caffeine (ideally with l-theanine) is a nice thing to have but tolerance is an issue. Right now what seems to work for me (no idea why) is a greens powder called Athletic Greens. I’m also trying pro/prebiotics which might be helping. Magnesium supplementation also might have helped. A medication I was taking was causing some problems as well and causing me to have some really intense fatigue on occasion (again, probably…). It’s super hard to isolate cause and effect in this area as there are so many potential causes. I’d say it’s worth dropping a lot of money on different supplements and interventions and seeing what helps. If you can consistently increase energy by 5-10% (something I think is definitely on the table for most people), that adds up really quickly in terms of the amount of work you can get done, happiness, etc. Ideally you’d do this by introducing one intervention at a time for 2-4 weeks each. I haven’t had patience for that and am currently just trying a few things at once, then I figure I can cut out one at a time and see what helped. Things I would loosely recommend trying (aside from exercise, sleep, etc): Prebiotics, good multivitamins, checking for food intolerances, checking if any pills you take are having adverse effects.I do also work through tiredness sometimes and find it helpful to do some light exercise (for me, games in VR) to get back some energy. That also works as a decent gauge for whether I'll be able to push past the tiredness. If playing 10 min of Beatsaber feels like a chore, I probably won't be able to work.How you rest might also be important. E.g. might need time with little input so your default mode network can do it’s thing. No idea how big of a deal this is but I’ve found going for more walks with just music (or silence) to maybe be helpful, especially in that I get more time for reflection. I’ve also been experimenting with measuring heart rate variability using an app called Welltory. That’s been kind of interesting in terms of raising some new questions though I’m still not sure how I feel about it/how accurate it is for measuring energy levels.