I am currently searching for EA jobs that are not pure research (e.g. community building)! Interested in longtermism & EA infrastructure. Experience in (x-)risk research & community building.
I have a background in (moral) philosophy, business admin, and moral psychology.
I agree with this: a lot of the argument (and related things in population ethics) depends on the zero-level of well-being. I would be very interested to see more interest into figuring out what/where this zero-level is.
I have recently been toying with a metaphor for vetting EA-relevant projects: that of a mountain climbing expedition. I’m curious if people find it interesting to hear more about it, because then I might turn it into a post.
The goal is to find the highest mountains and climb them, and a project proposal consists of a plan + an expedition team. To evaluate a plan, we evaluate
the map (Do we think the team perceives th territory accurately? Do we agree that the territory looks promising for finding large mountains? and
the route (Does the strategy look feasible?)
To evaluate a team, we evaluate
their navigational ability (Can they find & recognise mountains? Can they find & recognise crevasses, i.e. disvalue?)
their executive ability (Can they executive their plan well & adapt to surprising events? Can they go the distance?)
Curious to hear what people think. It’s got a bit of overlap with Cotton-Barratt’s Prospecting for Gold, but I think it might be sufficiently original.
Great report! I have a two questions for you:
1. On the following:
There are already many ongoing and upcoming high-quality studies on psychedelic-assisted mental health treatments, and there are likely more of those to follow, given the new philanthropic funding that has recently come into the area. (p. 45-46)
Based on the report itself, my impression is that high-quality academic research into microdosing and into flow-through effects* of psychedelic use is much more funding-constrained. Have you considered those?
2. Did you consider more organisations than Usona and MAPS? It seems a little bit unlikely that these are the only two organisations lobbying for drug approval?
*The flow-through effects I’m most excited about are a reduction in meat consumption, creative problem solving, and an improvement in good judgment (esp. for high-impact individuals). Effects on long-term judgment seem very hard to research, though.
I was confused about the usage of the term drug development as it sounds to me like it’s about the discovery/creation of new drugs, which clearly does not seem to be the high-value aspect here. But from the report:
Drug development is a process that covers everything from the discovery of a brand new drug for treatment to this drug being approved for medical use.
I speculate that the particulars of the psychedelic experience may drive rescaling like this in an intense way.
I also think that the psychedelic experience, as well as things like meditation, affect well-being in ways that might not be captured easily. I’m not sure if it’s rescaling per se. I feel that meditation has not made me happier in the hedonistic sense, but I strongly believe it’s made optimize less for hedonistic wellbeing, and in addition given me more stability, resilience, better judgment, etc.
I recently moved to a (nearby) EA hub to live temporarily with some other EA’s (and some non-EA’s), while figuring out my next steps in my life/career.
This has considerably increased my involvement. The ability to talk about EA over lunch, dinner, and to join meetups that are 5 minutes away make a big difference. As well as finding nice people I connect with socially/emotionally.
I suppose COVID had somewhat of a positive influence here too: I am less likely to attend a wide range of events, because I don’t know people’s approaches to safety. This leaves more time for EA.
Although communicating the precise expected resilience conveys more information, in most situations I prefer to give people ranges. I find it a good compromise between precision and communicating uncertainty, while remaining concise and understandable for lay people and not losing all those weirdness credits that I prefer to spend on more important topics.
This also helps me epistemically: sometimes I cannot represent my belief state in a precise number because multiple numbers feel equally justified or no number feels justified. However, there are often bounds beyond which I think it’s unlikely (i.e. <20% or <10% or my rough estimates) that I’d estimate that even with an order of magnitude additional effort.
In addition, I think preserving resilience information is difficult in probabilistic models, but easier with ranges. Of course, resilience can be translated into ranges. However, a mediocre model builder might make the mistake of discarding the resilience if precise estimates are the norm.
Just to clarify: Focusmate isn’t meant to talk about your work, so most people don’t try to find people with in-depth knowledge. I mostly don’t explain things in detail and don’t feel like I need to. It’s more an accountability thing and to share general progress (e.g. “I wanted to get 3 tasks done: write an email, draft an outline for a blog post, and solve a technical issue for my software project. I got 2 of them done, and realized I need to ask a colleague about #3, so I did that instead).
Thanks for the elaborate reply!
I think there’s a lot of open space in between sending out surveys and giving people binding voting power. I’m not a fan of asking people to vote on things they don’t know about. However, I have something in mind of “inviting people to contribute in a public conversation and decision-making process”. Final decision power would still be with CEA, but input is more than one-off, the decision-making is more transparant, and a wider range of stakeholders is involved. Obviously, this does not work for all types of decisions—some are too sensitive to discuss publicly. Then again, it may be tempting to classify many decisions as “too sensitive”. Well, organisation “opening up” should be an incremental process, and I would definitely recommend to experiment with more democratic procedures.
Hi Max, good to read an update on CEA’s plans.
Given CEA’s central and influential role in the EA community, I would be interested to hear more on the approach on democratic/communal governance of CEA and the EA community. As I understand it, CEA consults plenty with a variety of stakeholders, but mostly anonymously and behind closed doors (correct me if I’m wrong). I see lack of democracy and lack of community support for CEA as substantial risks to the EA community’s effectiveness and existence.
Are there plans to make CEA more democratic, including in its strategy-setting?
There will be a lot to learn from the current pandemic from global society. Which lesson would be most useful to “push” from EA’s side?
I assume this question is in between the “best lesson to learn” and “lesson most likely to be learned”. We probably want to push a lesson that’s useful to learn, and that our push actually helps to bring it into policy.
Given the high uncertainty of this question, would you (Toby) consider giving imprecise credences?
:(
Not a funding opportunity, but I think a grassroots effort to employ social norms to enforce social distancing could be effective in countries in early stages where authorities are not enforcing, e.g. The Netherlands, UK, US, etc.
Activists (Student EA’s?) could stand with signs in public places asking people non-aggressively to please go home.
I think this article very nicely undercuts the following common sense research ethics:
If your research advances the field more towards a positive outcome than it moves the field towards a negative outcome, then your research is net-positive
Whether research is net-positive depends on the current field’s position relative to both outcomes (assuming that when either outcome is achieved, the other can no longer be achieved). It replaces this with another heuristic:
To make a net-positive impact with research, move the field closer to the positive outcome than the negative outcome with a ratio of at least the same ratio as distance-to-positive : distance-to-negative.
If we add uncertainty to the mix, we could calculate how risk averse we should be (where risk aversion should be larger when the research step is larger, as the small projects probably carry much less risk to accidentally make a big step towards FAI).
The ratio and risk-aversion could lead to some semi-concrete technology policy. For example, if the distance to FAI and UAI is (100, 10), technology policy could prevent funding any projects that either have a distance-ratio (for lack of a better term) lower than 10 or that have a 1% or higher probability a taking a 10d step towards UAI.
Of course, the real issue is whether such a policy can be plausibly and cost-effectively enforced or not, especially given that there is competition with other regulatory areas (China/US/EU).
Without policy, the concepts can still be used for self-assessment. And when a researcher/inventor/sponsor assesses the risk-benefit profile of a technology themselves, they should discount for their own bias as well, because they are likely to have an overly optimistic view of their own project.
I really love Charity Entrepreneurship :) A remark and a question:
1. I notice one strength you mention at family planning is “Strong funding outside of EA”—I think this is a very interesting and important factor that’s somewhat neglected in EA analyses because it goes beyond cost-effectiveness. We are not asking the ‘given our resources, how can we spend them most effectively?’ but the more general (and more relevant) ‘how can we do the most good?’ I’d like to see ‘how much funding is available outside of EA for this intervention/cause area’ as a standard question in EA’s cost-effectiveness analyses :)
2. Is there anything you can share about expanding to two of the other cause areas: long-termism and meta-EA?
A consulting organisation aimed at EA(-aligned) organisations, as far as I’m aware: https://www.goodgrowth.io/.
Mark McCoy, mentioned in this post, is the Director of Strategy for it.
I have a concept of paradigm error that I find helpful.
A paradigm error is the error of approaching a problem through the wrong, or an unhelpful, paradigm. For example, to try to quantify the cost-effectiveness of a long-termism intervention when there is deep uncertainty.
Paradigm errors are hard to recognise, because we evaluate solutions from our own paradigm. They are best uncovered by people outside of our direct network. However, it is more difficult to productively communicate with people from different paradigms as they use different language.
It is related to what I see as
model errors (= wrong model structure or wrong/missing parameters)
Paradigm errors are one level higher: they are the wrong type of model.
Relevance to EA
I think a sometimes-valid criticism of EA is that it approaches problems with a paradigm that is not well-suited for the problem it is trying to solve.