Luisa Rodriguez is research analyst at 80,000 Hours. Previously, she researched civilisational collapse at the Forethought Foundation for Global Priorities Research, and nuclear war at Rethink Priorities and as a visiting researcher at the Future of Humanity Institute. Before that, she conducted cost-effectiveness evaluations of nonprofit and government programs at ImpactMatters, Innovations for Poverty Action, and GiveWell (as a summer intern).
Luisa_Rodriguez
Karma: 2,053
So glad you’ve found ways to significantly improve your wellbeing!!
I switched from taking antidepressants in the morning to taking them at night.
Can I ask why you think this helped so much?
What a phenomenal post — thank you both for writing it! A bunch of the potential negative consequences of unhealthy impact obsession felt super familiar to me, and the ideas for things that might help are just so good. Going to discuss a bunch of them with my therapist :)
Good point! Added a few!
Thanks so much for sharing this. It’s really heartbreaking to hear that someone’s encounter with the community was so painful and costly. I can relate to EA making my life worse in some ways, though I’m fortunate to have found a way to keep EA in my life in a way that’s healthier now. I’m trying to do more to support people who struggle with similar experiences, in part by doing things like the interview in this post.
80k does have some articles on the site that we think could be helpful to people in a similar position to the person who wrote that response. We address issues like how you can have an impact in any job, why personal fit for your career is so important, and why we think it’s helpful to not treat impartial impact as the only goal in life (a bunch of related ideas here, here, and here). But I’d love to find ways to do more to make sure the people who need to hear those messages are actually exposed to them — it’s clearly the case that some people’s experiences in the EA community, and the pressure they feel to have an impact, can be really dispiriting (again, this has definitely been the case for me). I’ll continue to look for opportunities to talk about these things on the podcast, but if people have other ideas for how to support people with these kinds of experiences, I’d love to hear them (and I know my colleagues would as well).
Not an error, but a few clarifying questions:
“For how many hours have you roughly been productive during the past 7 days?” <<this is in total over the last 7 days?
Does “productive” mean.. doing productive work for my job?
Yea, good question. It’s basically because I started with NHS psychiatrists (who strongly prefer to prescribe SSRIs), and only later moved to a private psychiatrist (who recommended I start first with agomelatine because of the excellent side effect profile, given that side effects were my main complaint).
I tracked my mood and thought patterns in a few different ways:
I use Daylio to track my overall mood once a day and I have 2 years worth of data there.
I use the GAD9 and PHQ-7 to track my depression and anxiety scores once every week. I have 3 years worth of data from that.
I use perfectionism and low self esteem questionnaires to track those things once a month. Data for those for about 2 years
Perhaps you approached these tests as mostly about finding one that didn’t have acute side-effects, and also wasn’t obviously not working?
Yea, I basically did this ^^
It was just extremely obvious to me when something was working/wasn’t, and the fact that many antidepressants I was super optimistic about didn’t work makes me think I wasn’t getting huge placebo issues.
While self-reported data is obviously a bit tricky, my sense of whether something was/wasn’t working was backed up by the data I collected.
I use Daylio to track my overall mood once a day and I have 2 years worth of data there.
I use the GAD9 and PHQ-7 to track my depression and anxiety scores once every week. I have 3 years worth of data from that.
I use perfectionism and low self esteem questionnaires to track those things once a month. Data for those for about 2 years
Hi Dan, I’m Luisa — I’ve been helping EA-aligned organizations find candidates for their open roles as part of my work at 80,000 Hours. I think there’s a good chance one of the direct outreach emails you’ve seen at IDinsight came from me, so I thought it’d be good to share a bit more about what kinds of headhunting we’re doing, and how we’re thinking about it.
Briefly, 80,000 Hours is sometimes asked by hiring managers at EA-aligned orgs to recommend potential candidates for specific roles. Given we get to know lots of EA-aligned people through our programs, we think we’re pretty well-placed to help talented people find out about impactful roles they might be a good fit for (that they might not have been aware of otherwise).
This does sometimes include reaching out to people who already have jobs — sometimes at EA-aligned (and adjacent) organizations — to find out if they’re open to other roles, and if so, put some roles we think are especially impactful on their radar.
We hope that the fact that we don’t have the same financial incentives as normal headhunters (who are paid when they get placements) means we’re able to act as a neutral-ish third party trying to think about which roles are extra-worth putting on more people’s radars.
We recognize that there are potential downsides, like increasing costs to organizations that spend a year training a new hire, only to have that person leave for another org soon once they’ve skilled up. And we absolutely don’t endorse pushing people harder on switching jobs than they would endorse, or in any way misleading people.
We hope this means we’re able to help create a better-working talent pipeline for orgs doing high-impact work, while minimizing the costs to orgs doing great work (like IDinsight!)
Thanks so much for sharing this publicly — I just shared with 8 people :)
I really loved this post! Thanks for writing it, Julia!
This meant so much <3
I love the idea of adding a section on good things that imposter syndrome’s trying to protect :) I’d love your help writing it if you’re up for it! I’ll DM you :)
Do you have a citation for the 100-1000 figure?
Comes from here https://mason.gmu.edu/~rhanson/collapse.pdf and the papers it cites:
It seems that groups of about seventy people colonized both Polynesia and the New World (Murray-McIntosh, Scrimshaw, Hatfield, & Penny, 1998; Hey, 2005). So let us assume, as a reference point for analysis, that the survival of humanity requires that one hundred humans remain, relatively close to one another, after a disruption and its resulting social collapse. With a healthy enough environment, one hundred connected humans might successfully adopt a hunter-gatherer lifestyle. If they were in close enough contact, and had enough resources to help them through a transition period, they might maintain a sufficiently diverse gene pool, and slowly increase their capabilities until they could support farming. Once they could communicate to share innovations and grow at the rate that our farming ancestors grew, humanity should return to our population and productivity level within twenty thousand years. (Murray-McIntosh, Scrimshaw, Hatfield, & Penny, 1998; Hey, 2005)
Oh dear — yes it should! Edited, thanks for flagging!
Yea, I find this really difficult to think about. I think if I’d never joined Rethink, I’d have ended up continuing to work in the global poverty space (>70%). If I left Rethink now, I’d probably look for (longtermist-oriented) research and research-adjacent jobs at EA orgs and EA-aligned think tanks.
Hey Aaron, good question!
I’m currently in touch with folks at the Nuclear Threat Initiative and a few other similar think tanks, but I don’t think my work has meaningfully influenced their views/activities. My hope is that this will change as I continue building my relationships with them.
To date, I think the audience that has engaged most with (and gotten the most value out of) the nuclear risks series is funders in the EA space. For example, I understand that multiple EA funders/grantmakers have drawn on (and augmented) some of my nuclear risks models as part of some cause prioritization work they’ve done.
Note: I can’t discuss this, since it’s covered by an NDA, and I haven’t seen the report that OpenPhil received, but compared to what I see as a superforecaster on the questions it looks like the numbers you have from GJP are wrong.
Davidmainheim, thanks for raising this! The GJI data should be correct now — let me know if you notice any other inconsistencies.
Thanks for flagging. Edited!
Hi Topher,
I really appreciate you engaging so meaningfully with the arguments on countervalue and counterforce targeting. It’s a critical factor in understanding how much harm a nuclear war would cause, so it’s important to get right.
I actually think we may not disagree as much as you seem to think (this makes me think my posts weren’t clear enough on some key points). I want to clarify my position on targeting strategies in the hope that we might tease out exactly how much we disagree:
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Clarification 1: You note that the US and Russia would likely target each others’ cities (e.g. Moscow) during counterforce targeting. I completely agree with this. I think a key miscommunication here stems from the fact that I’m using the following definitions of countervalue and counterforce targeting:
Countervalue targeting: targeting an enemy’s cities with the sole and explicit aim of killing civilians and disabling industry.
Counterforce targeting: targeting an enemy’s nuclear forces — for example, its missile silos and military bases, including those in and around cities.
So even though I’ve made the case that the US and Russia may be less likely to use countervalue targeting, I certainly grant that US and Russian cities near counterforce targets would likely be caught in the crossfire. I attempted to account for this to some extent in the two posts where I estimate the number of deaths caused directly and indirectly by a US-Russia nuclear war, but 1) this wasn’t clear in my posts, and 2) I didn’t do a good enough job of taking this into account in one of the two posts.
In my post on the number of deaths that would be caused directly by nuclear detonations, I quantified the deaths caused by counterforce targeting by the US and Russia by extrapolating from estimates generated by other people (academic researchers in the case of counterforce targeting against the US, and US government analysts in the case of counterforce targeting against Russia). I wasn’t clear about this in the post, but in both cases, the authors assumed that the counterforce scenarios they analyzed would involve the targeting of counterforce targets in and around major US and Russian cities. For example, the study on the expected fatalities caused by Russian counterforce targeting assumed that Russia would target Sacramento, San Francisco, Chicago, among others, as all of these places have key military bases other and facilities that relate to the US’s nuclear forces. Given this, my estimate of the deaths caused directly by nuclear detonations should do a reasonable job of accounting for the fact that some cities near counterforce targets would be bombed. Clearly, this was not well-explained in my write up. I’ll edit the post to make this clearer. If you have other suggestions for how to better account for this, I’d be happy to hear them.
By contrast, my post on the severity of a nuclear winter does not do a good enough job of accounting for the fact that counterforce targeting would involve bombing counterforce targets in or near cities. While I did take account of the fact that both the US and Russia would be quite likely to target each others’ capitals, I didn’t consider the smoke that would be generated by counterforce targeting in and around other cities that might be within the affected radius of a nuclear detonation during a counterforce strike by either country. This could end up making a difference to my conclusions, so I appreciate you flagging it as a gap in my work. I’ll spend some time in the next few weeks revising my model and post to reflect this (and I’ll update this thread once I’ve made those changes).
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However, there’s still a big difference in total direct deaths and nuclear winter risk between some metropolitan areas being caught in a counterforce crossfire and major metropolitan areas being intentionally targeted to maximize civilian casualties (as would likely happen in a countervalue war). This brings me to my next clarification:
Clarification 2: You’ve argued that the US and Russia would definitely use both counterforce and countervalue targeting. My view is that the US and Russia might use countervalue targeting but I don’t think it’s certain that they would. In my post, I hypothesize that there’s a 25% chance (90% CI: 5%–59%) that the US would target Russian cities as part of countervalue targeting (as opposed to targeting Russian cities to destroy its nuclear weapons or incapacitate its leadership). Similarly, I think there’s a 40% chance (90% CI: 7%–81%) that Russia would target US cities as part of countervalue targeting.
I suspect that one of the reasons our views differ on this comes from the fact that you’ve cited discussions of targeting strategies from 2009 and earlier. For example, you noted that “US war planning have not changed significantly between 1976 and 2009.” But while that’s true, the US has updated its war planning as of 2010. In 2010, President Obama, updated the US’s nuclear weapons policy. According to the Nuclear Employment Strategy (2013), a document summarizing the policy changes produced by the Department of Defense, the new guidance from President Obama “requires the United States to maintain significant counterforce capabilities against potential adversaries… The new guidance does not rely on a ‘counter-value’ or ‘minimum deterrence’ strategy.” The report later says, “the United States will not intentionally target civilian populations or civilian objects.”
While I don’t believe this means the US definitely wouldn’t ever use countervalue targeting, I think this offers evidence that 1) nuclear planning strategies have been updated since the Cold War, and 2), nuclear war plans have likely shifted away from countervalue targeting, at least somewhat.
The evidence on whether Russia would target US cities just to maximize casualties and hurt industry is weaker (hence the higher probability and wider confidence interval). I agree that Russia’s development of a nuclear weapon designed to produce a bunch of fallout offers some evidence that Russia would consider using nuclear weapons to target US cities for non-counterforce purposes. And you’re absolutely right that I conflated the nuclear target list discussed in the Popular Mechanics article with targets that might already be part of Russia’s nuclear targeting plan. I’m going to spend a bit more time considering whether/how much to update my estimate of the probability that Russia would use countervalue targeting against the US in light of these points. My current feeling is that there are still compelling reasons to think Russia would be more likely not to implement countervalue targeting relative to implementing it — in particular, because it would threaten the destruction of its society, and possibly (independently) put Russia at a strategic disadvantage during the nuclear exchange.
Lastly, I’d encourage us to be probabilistic here. I’d be quite curious to know how high you’d put the probability that the US and Russia would engage in countervalue targeting (as I’ve defined it), and what kind of results you get given those views. I’d also be curious if you have any other feedback on where my Guesstimate model (for example, see https://www.getguesstimate.com/models/13506) may be wrong. Regardless of where I personally come down on the probability of countervalue targeting by the US and Russia, the Guesstimate models I built are publicly available, and I encourage anyone who disagrees with my views on US and Russian targeting strategies to play with the probability of countervalue targeting and see how tweaks change the results.
Thanks! I have this nausea problem, so I’m going to try taking mine at night :) (checked and it seems fine/safe)