EA is still a small community. According to @David_Moss ’s estimates, in 2022 the number of active members of the EA community (medium and high levels of engagement) was about 9,600. The medium and high levels of engagement groups were 4,840 and 4,798 people, respectively.

Data on engagement levels start only from 2019, according to @David_Moss , so any extrapolation would have very limited value. But just out of curiosity and having no better quality data, I looked at the 2019-2022 CAGR (compound annual growth rate). For the total group of active participants and the two subgroups of moderately and highly engaged, the CAGRs were 13.6%, 4.9%, and 26.2%, respectively. I applied those CAGRs to the estimates of the numbers of the three corresponding groups at the end of 2022. In 10 years’ time (end of 2034), the size of the total group at its 13.6% CAGR would be 44.5k people. Taken separately, if the most active subgroup (4,798 people) continues to grow at its 26.2% rate, by 2034 it will grow to 78.6k people.

That seems to be too few for a group that wants to make an impact on alleviating global poverty, ending industrial-scale animal farming, not to mention preventing existential risks of planetary scale. Unless we learn from some groups that have had disproportionately high influence relative to their numbers.

Let's examine a group that has achieved remarkable impact despite limited numbers. It is a group of people who have lived and are living within the past 120 years. This group has had only 727 people, but they’ve had extraordinary influence on science—specifically, on physics, chemistry, physiology and medicine, and economics. Rather obviously, they are Nobel Prize laureates.

And these people have more in common than being Nobel Prize laureates. Looking in-depth at the winners, Kerri Smith and Chris Ryan from Nature conclude:

“You might expect lots of separate clusters to emerge as distinct academic families. But it turns out that almost all Nobel laureates share some connection, however distant, as represented by this sprawling network.

An incredible 702 out of 736 researchers who have won science and economics prizes up to 2023 are part of the same academic family—connected by an academic link in common somewhere in their history.”
(Nature, Oct 24, "How to Win a Nobel Prize" - https://www.nature.com/immersive/d41586-024-02897-2/index.html)

Earlier, Richard Tol from the University of Sussex came to the same conclusion:

“Nobel laureates cluster together. 696 of the 727 winners of the Nobel Prize in physics, chemistry, medicine, and economics belong to one single academic family tree.”
(https://link.springer.com/article/10.1007/s11192-024-04936-1)

Extraordinary scientists tend to assist other talented scientists to develop into extraordinary scientists. (There is an argument that Nobelists use their status to disproportionately nominate their protégés, but its extent is limited; otherwise, the prize’s meritocratic value and prestige would have eroded over time.) For example, John W. Strutt, who won a physics prize in 1904 for his work on the properties of gases, has 228 academic descendants with Nobels. Strutt had only one Nobel prizewinner among his trainees—Joseph Thomson, who won his Nobel in 1906. But Thomson really got the tree going—he trained nine physics winners (one of whom was his son, George Paget Thomson) and two in chemistry. And they went on to train many scientists who either won Nobels or produced prizewinners farther down their lineages.
(https://www.nature.com/immersive/d41586-024-02897-2/index.html)

“You can interpret the close relationships between Nobelists as a manifestation of the clustering of quality—the best professors congregate in the best schools (Ellison 2013), reinforce each other (Bosquet and Combes 2017), and select the best students (Athey et al. 2007).”
(Tol, 2018, https://cepr.org/voxeu/columns/professor-student-network-nobel-laureates-economics)

What could the EA movement possibly learn from this? The lessons can be distilled to three words: selection, mentoring, collaboration. The best professors select the best students, mentor them, and collaborate with them in research projects—resulting in scientific breakthroughs which have made an extraordinary impact on humanity.

Selection in the academic world, at least initially, does not seem to be an overly sophisticated process; it works similarly to natural selection. The best students strive to get to the best universities, where they are taught by the best professors. In the process, the brightest and most determined students get the best research supervisors.

Of course, EA is not an educational institution, and it acquires its participants via different channels, so the movement must periodically review which channels bring the most active participants and, if practical, take steps to broaden some channels. Also, trends of generational succession must be periodically analysed and addressed.

Increasing the number of opportunities for mentoring and collaboration is probably a key component now for strengthening the movement. As Feynman said in the preface to his famous lectures on physics, “…the best teaching can be done only when there is a direct individual relationship between a student and a good teacher—a situation in which the student discusses the ideas, thinks about the things, and talks about the things. It’s impossible to learn very much by simply sitting in a lecture, or even by simply doing problems that are assigned.”

For example, what would have happened if Chuck Feeney, an outstanding philanthropist (https://en.wikipedia.org/wiki/Chuck_Feeney), mentored a group of like-minded altruistic entrepreneurs or businesspeople from the next generation and also had their support and collaboration? We will never know the answer, but I personally believe it would have given significant leverage and continuity to his philanthropic activities.

In that respect, EA has big potential to create more projects for mentoring and collaboration, similar to Charity Entrepreneurship (https://www.charityentrepreneurship.com/incubation-program) and Founding to Give (https://www.aimfoundingtogive.com).

Also, such mentoring and collaboration opportunities should not be limited to business and social entrepreneurship but should also include other areas. I am sure EA has prominent participants in different fields who could share their experience and value system with like-minded people from the next generation.

Increasing opportunities for mentoring and collaboration can help us attract, develop, and expand the next generation of effective altruists. I am committed to contributing to these initiatives and encourage others to participate as well. Let's work together to build a stronger, more impactful community.