joshcmorrison's Quick takes

I run an advocacy nonprofit, 1Day Sooner. When good things happen that we have advocated for, it raises the obvious question, "were we the but-for cause?" 

A recent experience in our malaria advocacy work (W.H.O. prequalification of the R21 vaccine, a key advocacy target of ours) is exemplary. Prequalification was on the critical path for malaria vaccine deployment. Based on analysis of public sources and conversations with insiders, we came to the view that there was friction and possibly political pressure delaying prequalification from occurring as quickly as would be ideal. We decided to focus public pressure on a faster process (by calling for a prequalification timeline, asking Peter Singer to include the request in his op-ed on the subject, discussing the issue with relevant stakeholders, and asking journalists to inquire about it). We thought it would take at least till January and probably longer. Then a few days before Christmas, a journalist we were talking to sent us a W.H.O. press release -- that morning prequalification had been announced. Did it happen sooner because of us?

The short answer is we don't know. The reason I'm writing about it is that it highlights a type of causal uncertainty that I think is common (though not universal) in advocacy campaigns and should be relevant to EA thinking. 

In some campaigns, you find yourself on the inside of a decision-maker's process in a way that can give you some amount of certainty as to your role.^[1] For my kidney donor reimbursement campaign at Waitlist Zero (pre-1Day Sooner), I saw some text related to some Trump administration actions before they happened, had good transparency into the decision-making behind the Advancing American Kidney Health Initiative that my policy was a part of, and had decent confidence that my work was a but-for cause. 

But for others, like the W.H.O. prequalification above or the Biden Admnistration's announcement of Project NextGen, things are much fuzzier. Something you advocated for happens without your getting advance notice. You've made the case for it publicly and perhaps exercised some levers to pressure decision-makers. Did you influence the outcome? How can you know? 

I'm highlighting this experience because when it happened with NextGen I didn't really understand how to think about it, and now with prequalification I'm at least noticing the common pattern. (To be clear, I think the case for our causal influence on prequalification is stronger than for NextGen). 

I think it's of note for EA advocates because it raises the challenge of evaluating advocacy through a consequentialist framework. To me the strongest theoretical challenge to consequentialism is uncertainty and the unknowability of the future. The uncertainty of advocacy impact is a very practical example of this broader challenge. 

One thought about this I'd sent to a funder who asked about the NextGen campaign is the below:

So like ideally what you want as an advocacy group is to be inside-track on relevant decisions but maybe second-best is to be creating a narrative out of which the decision you are seeking manifests. That is to say we put on the performance of the need/desirability of a "Warp Speed 2" that the relevant decision-makers witnessed and participated in (even if it is unknowable whether it was causal or they were reactive to it) and this performative scaffold is sort of prima facie valuable for goals that are valuable (and the nature of advocacy/consequentialism is that oftentimes that's all that will be knowable even during a successful campaign). 

To be clear, the prequalification advocacy story was different than this performative scaffolding concept -- the most obvious way we may have been causally relevant is that the comms department of the relevant entities were likely getting journalistic inquiries about the issue from some major outlets, which very possibly scared the bejesus out of them and increased the desirability of hurrying up.

I raise these case studies because I hope they can provoke further thought, discussion, and insights from EAs involved in advocacy work.

1. ^{^}

   Even this is complicated because decision-makers often have an incentive to flatter you and for many issues, even if you're on the inside of the process you don't know if the process would have happened without you

I haven't had time to read all the discourse about Manifest (which I attended), but it does highlight a broader issue about EA that I think is poorly understood, which is that different EAs will necessarily have ideological convictions that are inconsistent with one another. 

That is, some people will feel their effective altruist convictions motivate them to work to build artificial intelligence at OpenAI or Anthropic; others will think those companies are destroying the world. Some will try to save lives by distributing medicines; others will think the people those medicines save eat enough tortured animals to generally make the world worse off. Some will think liberal communities should exclude people who champion the existence of racial differences in intelligence; others will think excluding people for their views is profoundly harmful and illiberal. 

I'd argue that the early history of effective altruism (i.e. the last 10-15 years) has generally been one of centralization around purist goals -- i.e. there're central institutions that effective altruism revolves around and specific causes and ideas that are the most correct form of effective altruism. I'm personally much more a proponent of liberal, member-first effective altruism than purist, cause-first EA. I'm not sure which of those options the Manifest example supports, but I do think it's indicative of the broader reality that for a number of issues, people on each side can believe the most effective altruist thing to do is to defeat the other. 

For a while I've been thinking about an idea I call Artificial Environment risk, but I haven't had the time to develop the concept in detail (or come up with a better name). The idea is roughly that the natural environment is relatively robust (since it's been around for a long time, and average species extinction rates and reasons are somewhat predictable), but as a higher proportion of humanity's environment is artificially created we voyage into an unknown without a track record of safety or stability. So the risk of dangerous phenomena increase dramatically -- as we go to a paradigm where we depend on an environment that has been roughly stable for millions of years to one for which exists evidence measured maybe in decades (or less!). Global warming and ozone degradation are obvious examples of this. But I also think that AI risk, biosecurity, nuclear war etc. fall under this (perhaps overly large) umbrella -- as humans gain more and more ability to manipulate our environment, we accumulate more and more opportunities for systemic destruction. 

Some risks, like global warming, are fairly observable and relatively straightforward epistemically. But then things like the attention environment and influence of social media are more complicated -- as tools for attracting attention become more and more powerful, it creates unforeseen (and hard-to-specify or verify) effects (e.g. perhaps education polarization, weakening of elite mediation of information, harm to public discourse) that may be quite influential (and may interact with or compound other effects) but will be hard to plan for, understand, or mitigate. 

One reason I find the idea worth trying to sketch out is, assuming technological development continues to progress, as humanity's control over our environment increases, risk will generally continue to rise, and fewer technologies will be realistically considered riskless. (So we will have more tradeoffs about things like whether to develop technologies that can end infectious disease but also enable better weapons). 

The idea of differential technological acceleration is aimed at this problem, but I am not sure how predictable offense/defense will be or how to effectively make political decisions about which fields and industries to nurture or cull. Part of the implication I draw from categorizing this broad set of risks together is that the space for new scientific and technological development will become more crowded -- with fewer value-neutral or obviously positive opportunities for growth over time. 

I think this may also tend to manifest in more of a clear division between what you might call left-EAs (progress-focused) and right-EAs (security-focused) (in some sense this corresponds to global health focused EAs vs. existential risk focused EAs currently, but the division is less clear). But that also  goes to a separate view I have that EAs will have to accept more internal ideological diversity over time and recognize that the goals of different effective altruists will conflict with one another (e.g. extending human lifespan may be bad for animal welfare; synthetic biology advances to cure infectious disease may increase risks to biohazards etc.). 

Very possible these ideas aren't original -- as I said they're very thinly sketched at the moment, but have been thinking about them for a while so figured I should write them out.