Heuristics from Running Harvard and Oxford EA Groups
This post is co-authored by Aleš Flídr and James Aung. We thank Harri Besceli for helpful comments. Our friend Tobias also wrote an excellent post with a lot of overlap that we highly recommend checking out.
In our experience leading Harvard EA and Oxford EA, we’ve made a lot of failures and therefore have a fair number of tips we would give to our past selves.
Note that the heuristics described below were built up in the context of English-speaking universities. Some points will not generalize to regional/national groups or other cultures. We expect readers to be able to judge that for themselves.
Neither of us has any major disagreements with the current CEA strategy or CEA’s models of community building. We think that the heuristics below can serve as a good complement to these high-level strategic thoughts.
Some underlying beliefs:
- The majority of value will come from a few individuals . As with most other groups, a typical student group will draw a disproportionate amount of value from a relatively small number of deeply engaged members. Most of the counterfactual value is going to come from the smaller number of deeply immersed and engaged people in your community.
Long-termism. Most of the value of our actions will be determined by their impact on the long-run trajectory of humanity (and non-human sentient beings). In the context of community building, this implies a relatively stronger focus on social and epistemic norms and people who can preserve/improve them.
- The Long-term impact of ideas. The long-term impact of EA will be largely determined by the quality of our ideas. We should therefore focus on high-fidelity methods of communication.
What follows is a set of heuristics that we have built up over years. We think that these align relatively well with the underlying assumptions, CEA’s current big-picture strategy and our on-the-ground experience.
Most of these heuristics come from the accumulation of a lot of anecdotal evidence, rather than systematic data-driven analysis. With these caveats in mind, here are the heuristics:
Focus on your understanding of EA. There is no substitute for having detailed models and broad knowledge of everything relevant to EA. People will base their understanding of effective altruism from you so make sure that you are as well versed in the literature as possible and that you can “cite your sources”.
Default to 1:1′s. In hindsight, it is somewhat surprising that 1:1 conversations are not the default student group activity. They have a number of benefits: you get to know people on a personal level, you can present information in a nuanced way, you can tailor recommended resources to individual interests etc. Proactively reach out to members in your community and offer to grab a coffee with them or go for a walk. 1:1′s also give you a good yardstick to evaluate how valuable longer projects have to be to be worth executing: e.g. a 7-hour project would have to be at least as valuable as 7 1:1′s, other things equal. Caveat: we definitely don’t mean to imply that you should cut all group or larger-scale activities. We will share some ideas for such activities in a follow-up post.
Avoid naive EA outreach.
Outreach is an offer, not persuasion. It can be tempting to try and persuade as many people about EA and run events that tweak the message of EA in an attempt to appeal to certain people. From our experience, this is generally a dangerous approach as it leads to low-fidelity diluted or garbled messages. Instead, think about outreach efforts as an ‘offer’ of EA where people can get a taste of what it’s about and take it or leave it. It’s OK if someone’s not interested. A useful heuristic James used for testing whether to run an outreach event is to ask “to what extent would the audience member now know whether effective altruism is an idea they would be interested in”. It turned out that many speaker events that Oxford were running didn’t fit this test, and neither did the fundraising campaign.
Don’t “introduce EA”. It’s fine if people don’t come across EA ideas in a particular sequence First, find entry points that capture a person’s interest. If someone finds EA interesting and likes the community, they will absorb the basics pretty soon.
Don’t teach, signpost. Avoid the temptation to teach EA to people. There’s a lot of great online content, and you won’t be able to explain the same ideas as well or in as much nuance as longform written content, well-prepared talks or podcast episodes. Instead of viewing yourself as a teacher of EA, think of yourself as a signpost. Be able to point people to interesting and relevant material on all areas of EA, and remove friction for people learning more by proactively recommending them content. For example, after a 1:1 meeting, message over 3 links that are relevant to their current bottleneck/area of interest.
Engagement is more important than wide-reach. Engagement with community and resources was typically a much better predictor of the value that an individual brings to the community than the impressiveness of their CV.
Focus on careers, rather than direct impact or fundraising. Getting people in your student community to make progress towards a high-value career path seems like the highest value thing you can be outputting. Students don’t have a lot of money or skills, so you won’t be able to do much good with direct work or fundraising in a student group. 80k’s survey revealed that a median junior hire would be worth $250k to a typical EA org.
Plan changes dominate. The ‘results’ your local group can deliver vary widely in expected impact: a GWWC pledge is much more impactful than a donation to a fundraiser, a career-plan-change for a priority path is significantly more impactful than a GWWC pledge (by 80,000 Hours’ IASPC metric). Given this, if people already in your group aren’t making career plans it’s more important to work out how you can encourage them to do so, rather than trying to get more people into your group.
Optimize content for the most engaged members. A good heuristic for finding useful things to do is to just ask the most engaged members of the community what they would find most valuable. Send Facebook messages to 10 people asking “what things would you find valuable for us to run for you?”
Try to make the community fun and attractive. Having a fun social atmosphere in your community encourages people to keep on exploring EA and motivates people to take action. Be the one to suggest social activities and introduce people to each other.
Beware excessive formalism. Formal team structures tend to just replicate what’s been done the previous year. A better model for a team is a tight knit group of ‘conspirators’. Also beware of getting bogged down in meaningless admin as a substitute for learning more about EA.
Develop a toolkit of questions. You want to help people get as engaged as they want and help them skill up as much as you can, but we often do this by lecturing at people and pushing ideas. A more fruitful strategy is to be able to ask the right questions that encourage people to explore and engage further. For more information of how to get people to reach novel insights or change their mind see David Rock’s excellent books Your Brain at Work and Quiet Leadership (Yes, we know that this article goes against this advice, this approach is harder in writing). Also consider attending a CFAR workshop (Hamming questions are particularly useful).
In a future post, we will share a couple of projects compatible with these heuristics that worked particularly well for our groups.