Research manager at ICFG.eu, board member at Langsikt.no, doing policy research to mitigate risks from biotechnology and AI. Ex-SecureBio manager, ex-McKinsey Global Institute fellow and founder of the McKinsey Effective Altruism community. Follow me on Twitter at @jgraabak
Jakob
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Thank you for this post, this is excellent work! Are you aware of ongoing efforts for any of your proposed topics? I’m asking because I’d consider starting a project on some of the above.
Thank you, Miranda!
Visualizations of the significance—persistence—contingency framework
I agree that it is a decision to be made on a project-by-project basis, but you can still have some prior about what’s roughly the right thing to do in aggregate, and use that prior to assess if you’re clearly missing the mark. This may feel like an artificial or useless exercise, but in general it is how high-level strategy decisions are made. Perhaps we’re just talking around each other because we are on different abstraction levels—you’re perhaps imagining a grant maker asking “how should I achieve this outcome” while I’m imagining “what’s the right strategy for EA as a whole”?
Side note: In this case, 100% prizes would clearly be the wrong percentage. 0% prizes is likely too low, and the realistic range is maybe 1-20%, but I don’t know with higher precision than that. However the movement looks very different with 1% vs. 20%, and getting it right could matter quite a bit.
The flip side of this is that people with less existing “reputation stock” may see the potential status upside as the main compensation from a prize contest, and not the monetary benefit
I think the “get lots of input in a short time from a crowd with different semi-informed opinions” feature of prizes are hard to replace through other mechanisms. Some companies have built up extensive expert networks that they can call on-demand to do this, but that still doesn’t have quite the same agility. However, in those cases you may often want to compensate more than just the best entry (in line with the OP)
One interesting debate would be: what’s the optimal % of funding that should go to prizes? Which parameters would allow us to determine this? One can imagine that the % should be higher in communities that are struggling more to hire enough, or where research agendas are unclear so more coordination is needed, but should be lower in communities with people with low savings, or where the funders have capacity to diversify risks.
One additional consideration is that the coordination benefits from prizes (in raising the salience of memes or the status of the winners) comes at an attention cost, so a large number of prizes may cannibalize on our “common knowledge budget” (if there is a limit to how much common knowledge we can generate)
Thank you for writing this up—I’ve wanted to do the same for a while! I think the only thing I see missing is that prizes can raise the salience of some concept or nuance, and therefore serve as a coordination mechanism in more ways than you list (e.g., say that we want more assessments of long-term interventions using the framework from WWOTF of significance—durability—contingency, then a prize for those assessments would also help signal boost the framework)
Thank you Max, and good point! While we did try to use the state-of-the-art evidence in this piece I think I’ll defer to Will’s research team on that one—his take is probably closer to the current consensus among the relevant experts
Hi Toby, thanks for the good insight and also relevant links—and apologies for the extremely delayed response! I thought I had already responded to this.
Agree that such a map would be valuable, though 1) I’m not sure if the data is rich enough to create a general map that works across all policy areas (due to substantial confounding factors throughout history), and 2) there may also be conceptual challenges (e.g., the strength of each arrow may differ by policy domain). Still, I think this is an important crux for the value of policy work in smaller countries, so agree that developing a better understanding would be valuable!
You can see their rationale in their public model: https://docs.google.com/spreadsheets/d/1tytvmV_32H8XGGRJlUzRDTKTHrdevPIYmb_uc6aLeas/edit#gid=1362437801
It’s the sum of 1.7% “improving circumstances over time”, 0.9% “compounding non-monetary benefits” and 1.4% “temporal uncertainty”. They have 0.0% “pure time preference”
Is GiveWell underestimating the health value of lead eradication?
I think it is likely that increased attention will lead to increased funding, but the question is on what timescales, and by what magnitude. Relatively recent numbers showed that the clear majority of people, even among US college students, had not heard of EA, which means it’s very unlikely that the potential funder pool is already saturated https://forum.effectivealtruism.org/posts/qQMLGqe4z95i6kJPE/how-many-people-have-heard-of-effective-altruism
Good point! Indeed, the key funding sources for EA (tech billionaires) have notoriously volatile fortunes, though I’m not sure how tight the link is between their wealth in a given year, and the flow of money to EA.
Also, others seem to predict that the number of major funders will grow over the next years, which can increase both the average level of funding, and the stability https://forum.effectivealtruism.org/posts/Ze2Je5GCLBDj3nDzK/how-many-ea-billionaires-five-years-from-now
The 3rd wave of EA is coming—what does it mean for you?
Have you spoken to Jona Glade about it? He’s also working on setting up a consultancy. I’m also happy to chat about this.
Would this be another organization like Rethink Priorities, or is it different from what they are doing? (Note: I don’t think this space is crowded yet, so even if it is another organization doing the same things, it could still be very helpful!)
One potential niche could be betting markets around outcomes of political events (e.g., betting on outcome metrics such as GDP growth, expected lifespan, GINI coefficient, or carbon emissions; linked to events such as a national election, new regulatory proposals, or the passing of government budgets). Depending on legal restrictions, this market could even ask policy makers or political parties to place bets in these markets, to help the public assess which policy makers have the best epistemics, to hold policy makers accountable, and to incentivize policy makers to invest in better epistemics. (note: this also links to an idea presented in a different comment here -https://forum.effectivealtruism.org/posts/KigFfo4TN7jZTcqNH/the-future-fund-s-project-ideas-competition?commentId=zjvCCNuLEToCQyHdn)
Hi Adam! Thanks for the detailed reply. From a brief look at your model, it seems you’ve understood my reasoning in this post correctly. I had indeed overlooked that their numbers were already discounted.
However, since they use a 3% discount rate and you use a 4% discount rate, you would still need to adjust for the difference. If we still assume that the economic impacts hit throughout your entire career, from 15 to 60 years into the future (note: 15 years into the future is not the average, but the initial year of impacts!), then you get to around $0.7 of NPV for each $1 today—much better than the $0.28 in my analysis, but still less than the $1 without discounting. Using this number, the result would be very close to GiveWell’s 20% estimate. How curious!
Best,
Jakob