- Where people first hear of effective altruism (EA) has changed over the years: 80,000 Hours is now much more influential, and Giving What We Can (GWWC) much less so.
- Personal Contacts, books, articles and blogs (other than those by major orgs) and 80,000 Hours seem to now be where most people first hear of EA.
- Peter Singer is sufficiently influential that he should probably be his own category
In the 2018 EA Survey, we asked individuals both:
- How did you first hear about Effective Altruism? [single select]
- Which factors were important in ‘getting you into’ effective altruism, or altering your actions in its direction? Check all that apply. [multi select]
In each case, multiple options were presented by default, as well as an “Other” option with an open comment box.
Where do people first hear about EA?
2593 EA respondents answered the “How did you first hear about EA?” question.
Note: images can be viewed more easily if opened in new tabs.
Across our sample as a whole, Personal Contacts, LessWrong and 80,000 Hours stand out as the places where most people first hear about Effective Altruism, along with “Other” responses. No single route accounts for a particularly large portion of first contacts with EA. The largest single category (other than “Other”) Personal Contact, accounted for 16%. Thus, a wide variety of different sources seem significant for people first hearing about EA.
We exploratorily coded the open comments accompanying the “Other” responses, creating new categories wherever a substantial number of responses seemed to fit into a given theme. These cannot be directly compared to the numbers above, however, as while respondents were intentionally permitted only to select a single place where they first heard about EA, in the open comment box, many responses seemed to fit multiple categories and were coded as such. In addition, how individual responses should be coded is necessarily somewhat subjective.
The largest category within the ‘Other’ responses by a very large margin was Peter Singer, with ~30% of all responses fitting this category. Of these, about 40% referred to a book by Peter Singer and 17% referred to a course, whether his MOOC or another university course where he was taught. However a majority of these did not fit either these categories or others (e.g. they just responded “Peter Singer”).
Approximately 19% of the open comment responses mentioned Podcasts (typically the Sam Harris or Joe Rogan podcasts), 15% mentioned Books, 10% mentioned Articles (online or in a newspaper), 9% mentioned a university or school Course, 7% a Blog, and 4% a Talk. 5% and 6% referred to an EA org that had already been included in the fixed response options (e.g. GWWC) and to a Personal Contact respectively.
Where do people first hear about EA across time?
While the above section reported where people first heard about EA across our sample as a whole, where people first hear about EA seems to have radically changed across time. The full numbers of people reporting hearing about EA from different sources in each year can be viewed here.
The following graph shows the proportion of people hearing about EA in each year who heard about it from different sources. The categories of ‘Other (book, article, blog etc.)’ (bright green) and ‘Personal Contact’ (bright blue) account for a large share of EAs across years (never lower than 10%). LessWrong accounts for very large percentages up until around 2015, at which point it begins to decline. At around the same time, SlateStarCodex begins to increase, perhaps representing some continued recruitment from the ‘rationalist diaspora’.
One of the more striking changes is in the role of Giving What We Can (red) as a first point of contact for EAs. Giving What We Can seemed to have been one of the largest recruiters for EAs in the earlier years, but as early as 2012 appears to have drastically diminished in importance. After 2012, no more than 5% of EAs per year indicate that they first heard about EA from GWWC.
Conversely, 80,000 Hours (purple) represents one of the most dramatic increases in our data. From 2016, the numbers of EAs reporting first hearing about EA from 80,000 Hours explode from 9% to 13% to 25%, making them the largest single source of EA recruitment in 2018.
One important fact to bear in mind is that the number of EAs reporting hearing about EA in a given year has radically increased with time, from a little over 200 in 2009-2012, to 700 in 2017. As the 2018 survey was administered part way through the year, the numbers for this year are, of course, lower.
As such, 80,000 Hours’ large share of people first hearing about EA in later years accounts for a very large number of EAs. For example, the number of EAs in our sample who report hearing about EA from 80,000 Hours in 2017-2018 alone is more than the total who heard from Giving What We Can across all years. This, of course, does not necessarily imply more or less impact, since recruiting EAs in earlier years may be more valuable.
It is therefore also interesting to look at the changes in the total number of people hearing about EA from different sources, rather than simply the proportion hearing about EA from different sources, in order to see whether the numbers of EAs coming from different sources are actually declining in absolute terms.
As the graph would be too crowded to read if we included all 18 sources, we removed those groups accounting for the smallest numbers of EAs overall (SHIC, EAG, ACE, REG/EAF, TLYCS, internet searches and Facebook). We excluded 2018 since fewer EAs had a chance to report first hearing of EA this year and so all the numbers are dramatically lower than in 2017.
For the most part, numbers seem to be reliably increasing across sources, except for LessWrong and Giving What We Can, which decline in absolute terms, since 2015.
Which Factors are Important for People Getting into EA?
For this question, individuals could select multiple options as being important for them getting into EA.
80,000 Hours, Books, Articles or Blogs, and Personal Contact appeared extremely influential here as well, though GiveWell was the second most commonly cited influence, followed by Giving What We Can, local groups, and the online EA community.
There was also some change in the proportion of different cohorts of EAs (i.e. people first hearing about EA in different years) citing different influences as important. LessWrong appears to be cited more frequently among EAs who heard about EA in earlier years and less frequently by those joining more recently, whereas 80,000 Hours is cited much more frequently by those newer to EA. Indeed, around 50% of those who joined EA in 2017 or 2018 cite 80,000 Hours as important for getting them into EA.
In future posts we will explore some further demographic factors and outcomes associated with hearing about EA from different sources.
This post was written by David Moss.
Analysis conducted by Rethink Priorities (David Moss, Peter Hurford and Neil Dullaghan).
Thanks to Tee Barnett and Christina Rosivak for editing.
The annual EA Survey is a project of Rethink Charity that has become a benchmark for better understanding the EA community.
Articles in the 2018 EA Survey Series:
I - Community Demographics & Characteristics
II - Distribution & Analysis Methodology
IV - Subscribers and Identifiers
VIII- Where People First Hear About EA and Higher Levels of Involvement
IX- Geographic Differences in EA
X- Welcomingness- How Welcoming is EA?
XI- How Long Do EAs Stay in EA?
XII- Do EA Survey Takers Keep Their GWWC Pledge?
Prior EA Surveys conducted by Rethink Charity
Hey David and everyone else involved, thank you for the analysis! This is useful data for us.
A quick request for next year: it would be great to keep working on the categories to get fewer 'other' responses and reduce overlap.
The Sam Harris and Joe Rogan podcasts were done by Will as part of the promotion campaign for DGB while he was working at CEA/80k so could arguably be coded as DGB/CEA/80k. Presumably some of the books / articles / talks are also other materials produced by the organisations or press coverage they sought out - does that seem right?
Likewise, maybe 'search' and 'facebook' should be removed as categories, because they're channels you use to find the other content listed. Presumably everyone who found out about EA through 'facebook' likely saw a post by a friend, so should be a personal referral, or saw a post by one of the orgs, so should be coded as an org.
I'm also surprised to see https://www.effectivealtruism.org/ isn't listed - do you know what happened there?
Thanks for the comment!
We will definitely keep refining the categories year-by-year depending on which seem more or less significant.
I entirely agree that Will’s podcasts can be counted as CEA/80K/DGB/Will in terms of assigning credit.
I’m not sure what that tells us about how we ought to design the survey though. In terms of coding open comment responses: as I noted, how to classify people’s open comment answers is somewhat fuzzy, many comments ambiguously fit multiple different options and those numbers can’t be directly compared to the fixed category responses. Your podcast case is a perfect example since, as you note, if someone writes in “Joe Rogan Podcast” it could be classified as ‘DGB’, ‘CEA’, ‘80K’, ‘Podcast’ or ‘Will’ (or depending on our interests, we could code it as ‘mass media outreach’ or ‘online’ and so on). I could go back through the open comments and try to code things as CEA or 80K related (per your specification), but it will be a pretty vague and heterogeneous category with a lot of edge cases like these, that will make it hard to interpret. Explicit references to existing EA orgs or Will etc. were coded as such.
Also, crucially, a lot of the comments weren’t specific enough to code in that way. In the specific case of Sam Harris podcasts, for example, at least one person mentioned the Peter Singer episode (no-one explicitly mentioned Eliezer’s AI episode that I saw, but in principle some people might have first heard through that one), which means technically we can’t code every reference to Sam Harris’ podcast as Will’s- though I think it’s entirely reasonably of you to assume that many of the non-specific comments were referring to Will’s. In terms of refining the categories: note that DGB and 80K were already available as options and respondents chose to select “Other” and write in a response anyway. It would be difficult to change the fixed categories, in such a way that people who would otherwise write “Joe Rogan podcast” would instead select “CEA”/“80K” etc. as a category. For one thing, people need to know (and remember) that, when they hear Will on a podcast, this should be counted as 80K or CEA or as part of the marketing for DGB or whichever category. They may also just feel that ‘Other: Podcast’ better captures their case than DGB or 80K. I think it would be difficult to specify all the things that could reasonably be counted as CEA’s work in a given fixed option (e.g. ‘80,000 Hours, inc. Doing Good Better, 80K Podcasts, Will MacAskill podcasts etc.’), but we’ll continue reviewing the results and trying to think of the best options.
I agree that in light of this year’s results, including Podcast as its own category next year may well make sense. We could also split out Book/Article etc. into multiple options. Though doing this might actually give us less information, in terms of attributing responses to CEA/80K/Will etc., as if people just select ‘Podcast’ as a fixed response, rather than writing in an ‘Other’ response, we won’t know which Podcast it was. We could include/require an open comment to specify further in addition to fixed responses, but requiring open comment would be significantly more onerous for respondents and might reduce response rate, so it’s a tricky balance. Alternatively we could include more fixed options (Podcast: Will; Podcast: 80K/Rob Wiblin; Podcast: Other, and so on), and ditto for other specific books, websites and so on (so far, Doing Good Better is the only one we’ve extended this treatment to), but of course that might make the question too unwieldy.
I definitely agree this is right in terms of assigning credit: no doubt EA orgs such as CEA should claim a lot of credit for vicariously bringing about lots of other outcomes (e.g. lots of Personal Contacts are presumably influenced by the prior work of EA orgs), but again, I don’t think there’s a way to capture that in people’s First Heard responses. And again, when open responses explicitly referred to an EA org, then it was coded accordingly, as well as coding it as ‘Book’ or ‘Article.’.
I think it’s pretty plausible that they should be removed next year (given the relatively small numbers attached to them). Although it doesn’t necessarily follow that the answers could neatly be split off into “personal contact” or “an EA org” because people may remember that they saw something on Facebook, but not which org was responsible (a lot of comments were pretty vague like this): so getting rid of “search” and “facebook” would probably mean a lot more “Other” responses.
We’d certainly be open to including this website if you are particularly interested in it (although then there’s a question of which other specific EA websites should or shouldn’t be included ). For what it’s worth we didn’t receive a single “Other” response referring to it, that I saw, but maybe people classified this as “Search” or something else.
That makes sense. I agree none of this is simple.
have you tried cluster analysis on the question "Which factors were important in ‘getting you into’ effective altruism, or altering your actions in its direction?"? Since it is multi-select, if most people actually selected more options, information about whether there are some patterns/clusters of factors that are important for people to feel they "got into" EA seems to me like it might be more informative than simple ranking of each factor's frequencies independently.
This might be valuable to try for both, the whole sample as well as specifically for more engaged subgroups as Ben suggested.
We briefly looked into this and there was basically no interesting relation between “getting into” EA via the different factors. This isn’t particularly surprising to me, since a priori, for most of these factors, I wouldn’t expect getting more involved in EA via one factor to make you more likely to get involved in EA via a different factor relative to the other factors. For example, if you get more involved in EA via 80,000 Hours, should this make you more likely to get involved with local groups or online EA than if you got involved via GWWC? Or, if you get more involved in EA via 80,000 Hours, should this make you more likely to get more involved in EA via local groups than get more involved via online EA? For the most part, I’d expect not, and that was pretty much what the data shows. Most forms of getting more involved are just weakly positively correlated with most other forms of getting more involved, which is what I’d expect (if you get more involved in EA in any one way you are just slightly more likely to report getting involved in any other way).
The only variables between which there seemed to be any substantial connection (and even these were weak) was that a local group being important for one getting more involved was associated with a personal contact being important for one getting more involved. This makes sense, and is arguably almost trivially true, since it seems like being involved in a local group necessarily entails having personal contacts. In the cluster analysis you could arguably_vaguely_ make out a ‘nothing much selected’ cluster, a ‘local group and personal contact (but also a modest amount of online, 80K, GWWC, and book, blog etc.)’ cluster and an ‘everything else inc. especially online EA, 80K, GWWC, and book, blog etc.)’ cluster, but as noted, there wasn’t much definition within the clusters.
Conversely, a case where I think that cluster analysis does make sense and where the results were more informative was looking at categories of group membership as we do here.
I think another instance where looking at the relationships between reporting getting more involved in EA in different ways and other outcomes is the series of Multiple Correspondence Analyses that we included in the Cause Selection post. If you examine these, then you can see, for example, that there is a correspondence between “getting more involved” via online EA, a personal contact or local group and lower prioritisation of climate change (and the converse pattern for AI/x-risk).
With regards to the question of looking at more engaged subgroups, we looked at the relationship between first hearing about EA in different ways and levels of involvement previously. You’ll note that we found little evidence that different routes into EA lead to substantially higher or lower proportions of people becoming highly engaged EAs. Rather, the number of highly engaged EAs seemed pretty closely proportional to the total number of EAs recruited from each source.
When looking at the multi-select question, we do find some significant differences, though as in the case of ‘first heard’ data, we would expect this to be confounded, most importantly by how long respondents have been in EA. Still, it seems like significantly more people who report getting more involved via a book or blog, etc., EA Global, local EA group, online EA or personal contact are members of the EA Forum than not (across all time periods). You can also compared the raw percentages of people involved in different ways across Forum members and non-Forum members. I don’t think this suggests anything in particular about any causal relations between being involved in one way and being involved in another though.
Thanks, David! My intuition a bit different - most people I talked to about how got they got into EA mentioned multiple factors, so I was curious whether there would be general patterns/strong clusters of e.g. "offline EA (e.g. local groups + personal contact)" vs "Online EA" or clusters based on type of activity/contribution, e.g. "donation cluster (Givewell + GWWC + TLYCS + ACE)" vs "direct work cluster (80K + EA global)" vs "producing/reading research (books/articles + SSC + LW)". I see it doesn't seem to be the case for the whole sample base don your analysis.
Regarding the more engaged subgroup - while I perceive analysing of "where people first heard about EA" as interesting, the question of "which factors actually got people into EA" seems to me as more important. The more that most people I talked to mentioned that first point of contact with EA didn't cause them to "get into it" right away, but only after encountering some other factors they finally made a step to "dive into it" or "get involved". Therefore, looking whether there are some patterns of these factors for more vs less involved people seems to me potentially promising, I agree that "how long people have been in EA" will probably add a lot of noise to this as these patterns could have changed over time. Not sure whether the sample size would be big enough to analyse each year separately or whether there are some other ways to control for it.
Using cluster analysis for the group membership seems to me like a good example of such approach.
Thanks David. I agree the online vs offline idea is pretty intuitive. Arguably you can vaguely see some signs of this in the data, but not to a great extent. As the membership post shows, there's quite a lot of overlap between online (EA Facebook) and offline (Local Group):
Yes, this is what the analysis in the previous comment aims to do. And yes, you are correct that controlling for time in EA is very difficult because of the very small numbers in the earlier years of EA, hence in the analysis above we just display results splitting by those joining before/after 2016.
The other additional analysis which would be great is if you could identify the 20% of the respondents who seem most involved and dedicated, and then repeat the analysis by source for this sub-group. This would give us some sense of the quality as well as the scale of the reach of different sources.
Thanks Ben, this seems like a great suggestion. We're going to be talking about different levels of engagement a lot in the subsequent series of the post (with regards to cause preference in particular), but will make sure to put together an analysis on this specifically.
This data might also be useful to cross-check against:
I just noticed that there were people who report first finding out about EA from 80k in 2009 and 2010. I'd say 80k was only informally formed in early 2011, and the name was only chosen at the end of 2011, so those survey responses must be mistaken. I gather that the sample sizes for the early years are small, so this is probably just one or two people.
Thanks Ben. Yeh, this is 3 people in 2009 and 3 people in 2010 (out of 2473 responses to these questions overall). There are a handful of similar errors for Doing Good Better. Every year, there are a few people who seem to get the years wrong in this way (alongside a lot of responses saying explicitly that they don't remember).
Anecdotally, (both in the survey and elsewhere) I find a surprising number of people confuse CEA, 80K and GWWC (not to mention, Rethink Charity, its various projects and Charity Science).