All of dwebb's Comments + Replies

On Health (point 8), this paper shows that patent pooling can be effective at improving access to drugs in LMICs:

https://www.sciencedirect.com/science/article/pii/S0167629622000868?via%3Dihub

I haven't seen anything along these lines, but it would certainly be interesting if there were theoretical reasons to think that prediction variance should increase exponentially.

Ultimately though I do think this is an empirical question - something I'm hoping to work on in the future. One new relevant piece of empirical work is Tetlock's long-run forecasting results that came out last year: https://onlinelibrary.wiley.com/doi/abs/10.1002/ffo2.157

I think this is a very good point, and it's helping shape my ideas on this topic, thank you!

I guess it's true that most/all candidates for longtermist interventions that I've seen are based on attractor states. At the same time, it's useful to think about whether we might be missing any potential longtermist interventions by focusing on these attractor state cases. One such example that plausibly might fit into this category is an intervention that broadly improves institutional decision-making. Perhaps here, interventions plausibly have a long run positiv... (read more)

I hadn't seen this post before, but to me it sounds like Beckstead's arguments are very much in line with the idea of attractor states, rather than deviating from it. A path-dependent trajectory change is roughly the same as moving from one attractor state to another, if I've understood correctly.

The argument he is making is that extinction / existential risks are not the only form of attractor state, which I agree with.

2
MichaelA
3y
Whoops, yeah, having just re-skimmed the post, I now think that your comment is a more accurate portrayal of Beckstead’s post than mine was. Here’s a key quote from that post:

Yes indeed, kudos to Dave Bernard - he pointed out this distinction to me as well.

And good spot - sorry for the confusing error! I've now edited this in the text.

Thanks so much for the very insightful commentary!  My thoughts are still evolving on these topics so I will digest some of your remarks and reply on each one.

Thanks for some thought provoking questions!

The posterior estimate of value trends towards zero because we assumed that the prior distribution of u_t has a mean of 0. Intuitively, absent any other evidence, we believe a priori that our actions will have a net effect of 0 on the world (at any time in the future). (For example, I might think that my action of drinking some water will have 0 effect on the future unless I see evidence to the contrary. There's a bit of discussion of why you might have this kind of "sceptical" prior in Holden Karnofsky's blog po... (read more)

You're right that the constant predicted benefits for each intervention is an important simplifying assumption. However, as you mention, it would be relatively easy to change the integrand to allow for different shapes of signalled benefits. For example, a signal that suggests increasing benefits as we increase the time horizon might increase the relative value of the longtermist intervention. 

It quickly becomes an empirical question what the predicted-benefit function looks like, and so it will depend on the exact intervention we are looking at, alon... (read more)

I agree! I think you're pointing towards a useful way of carving up this landscape. My framework is good for modelling "ordinary" actions that don't involve attractor states, where actions are more likely to wash out and longtermism becomes harder to defend (but may still win out over neartermist interventions under the right conditions). Then, Tarsney's framework is a useful way of thinking about attractor states, where the case for longtermism becomes stronger but is still not a given.

4
Jack Malde
3y
I'm unsure how many proposed longtermist interventions don't  rely on the concept of attractor states. For example, in Greaves and MacAskill's The Case for Strong Longtermism, they class mitigating (fairly extreme) climate change as an intervention that steers away from a "non-extinction" attractor state: Perhaps Nick Beckstead's work deviates from the concept of attractor states? I haven't looked at his work very closely so am not too sure. Do you feel that "ordinary" (non-attractor state) longtermist interventions are commonly put forward in the longtermist community? The only intervention in Greaves and MacAskill's paper that doesn't rely on an attractor state is "speeding up progress": I'd be interested to hear your thoughts on what you think the forecasting error function would be in this case. My (very immediate and perhaps incorrect) thought is that speeding up progress doesn't fall prey to a noisier signal over time. Instead I'm thinking it would be constant noisiness, although I'm struggling to articulate why. I guess it's something along the lines of "progress is predictable, and we're just bringing it forward in time which makes it no less predictable". Overall thanks for writing this post, I found it interesting!

Thanks for this Jack! Sounds like an interesting area to look into.

I am curious about the literature suggesting that lead paint causes negative health / psychological effects. After an admittedly cursory glance, many of the studies you cite seem to indicate an association between lead exposure and some negative outcome, but don't necessarily imply a causal link from lead exposure to these negative outcomes. This is important: if the correlation is actually due to some other factor (e.g. living in worse conditions more generally), then we may overesti... (read more)

Hi, thanks for the comment! Yes, most of the studies are longitudinal cohort studies. I think this is one of the best examples of a well-designed interventional study: https://www.aeaweb.org/articles?id=10.1257/app.20160056