I’m glad someone is asking what happened with EA Ventures (EAV): it’s an important question that hasn’t yet received a satisfactory answer.
When EAV was discontinued, numerous people asked for a post-mortem of some type (e.g. here, here, and here) to help capture learning opportunities. But nothing formal was ever published. The “Celebrating Failed Projects” panel eventually shared a few lessons, but someone would need to watch an almost hour-long video (much of which does not relate to EAV) to see them all. And the lessons seem trivial (“if you’re doing a project which gives money to people, you need to have that money in your bank account first”) about as often as they seem insightful (“Finding excellent entrepreneurs is much, much harder than I thought it was going to be”).
If a proper post-mortem with community input had been conducted, I’m confident many other lessons would emerge*, including one prominent one: “Don’t over-promise and under-deliver.” This has obvious relevance to a grantmaking project that launched before it had lined up funds to grant (as far as I know EAV only made two grants- the one Jamie mentioned and a $19k grant to EA Policy Analytics). But it also relates to more mundane aspects of EAV: my understanding is that applicants were routinely given overly optimistic expectations about how quickly the process would move.
The missed opportunity to learn these lessons went on to impact other projects. As just one example, EA Grants was described as “the spiritual successor to EA Ventures”. And it did reflect the narrow lesson from that project, as it lined up money before soliciting grant applications. However, the big lesson wasn’t learned and EA Grants consistently overpromised and under-delivered throughout its entire history. EA Grants announced plans to distribute millions of dollars more money than it actually granted, repeatedly announced unrealistic and unmet plans to accept open applications, explicitly described educational grants as eligible when they were not, granted money to a very narrow set of projects, and (despite its public portrayal as a project capable of distributing millions of dollars annually) did not maintain an “appropriate operational infrastructure and processes [resulting] in some grant payments taking longer than expected [which in some cases] contributed to difficult financial or career situations for recipients.”
EAV and EA Grants have both been shuttered, and there’s a new management team in place at CEA. So if I had a sense that the new management had internalized the lessons from these projects, I wouldn’t bring any of this up. But CEA’s recently updated “Mistakes” page doesn’t mention over-promising/under-delivering, which makes me worry that’s not the case. That’s especially troubling because the community has repeatedly highlighted this issue: when CEA synthesized community feedback it had received, the top problem reported was “respondents mentioned several times that CEA ‘overpromised and under delivered’”. The most upvoted comment on that post? It was Peter Hurford describing that specific dynamic as “my key frustration with CEA over the past many years.”
To be fair, the “Mistakes” page discusses problems that are related to over-promising/under-delivering, such as acknowledging that “running too many projects from 2016-present” has been an “underlying problem.” But it’s possible to run too many projects without overpromising, and it’s possible to be narrowly focused on one or a few projects while still overpromising and under-delivering. “Running too many projects” explains why EA Grants had little or no dedicated staff in early 2018; it doesn’t explain why CEA repeatedly committed to scaling the project during that period despite not having the staff in place to execute. I agree CEA has had a problem of running too many projects, but I see the consistent over-promising/under-delivering dynamic as far more problematic. I hope that CEA will increasingly recognize and incorporate this recurring feedback from the EA community. And I hope that going forward, CEA will prioritize thorough post-mortems (that include stakeholder input) on completed projects, so that the entire community can learn as much as possible from them.
* Simple example: with the benefit of hindsight, it seems likely that EAV significantly overinvested in developing a complex evaluation model before the project launched, and that EAV’s staff may have had an inflated sense of their own expertise. From the EAV website at its launch:
“We merge expert judgment with statistical models of project success. We used our expertise and the expertise of our advisers to determine a set of variables that is likely to be positively correlated with project success. We then utilize a multi-criteria decision analysis framework which provides context-sensitive weightings to several predictive variables. Our framework adjusts the weighting of variables to fit the context of the projects and adjusts the importance of feedback from different evaluators to fit their expertise.”
As another resource on effective D&I practices, HBR just published a new piece on “Diversity and Inclusion Efforts that Really Work.” It summarizes a detailed report on this topic, which “offers concrete, research-based evidence about strategies that are effective for reducing discrimination and bias and increasing diversity within workplace organizations [and] is intended to provide practical strategies for managers, human resources professionals, and employees who are interested in making their workplaces more inclusive and equitable.”
Very interesting to see this data- thanks so much for collecting it and writing it up! I hope future versions of the EA Survey will adopt some of your questions, to get a broader perspective.
Thanks Ben! That’s an interesting reference point. I don’t think there are any perfect reference points, so it’s helpful to see a variety of them.
By way of comparison, 1.8% of my sample was black (.7%) or Hispanic (1.1%).
I don’t think placing no value on diversity is a PR risk simply because it’s a view held by an ideological minority. Few people, either in the general population or the EA community, think mental health is the top global priority. But I don’t think EA incurs any PR risk from community members who prioritize this cause. And I also believe there are numerous ways EA could add different academic backgrounds, worldviews, etc. that wouldn’t entail any material PR risk.
I want to be very explicit that I don’t think EA should seek to suppress ideas simply because they are an extreme view and/or carry PR risks (which is not to say those risks don’t exist, or that EAs should pretend they don’t exist). That’s one of the reasons why I haven’t been downvoting any comments in this thread even if I strongly disagree with them: I think it’s valuable for people to be able to express a wide range of views without discouragement.
Glad this is something you're tracking. For reference, here's the relevant section of the annual review.
To clarify, my comment about EA's political skew wasn't meant to suggest Larks doesn't care about viewpoint diversity. Rather, I was pointing out that the position of not caring about racial diversity is more extreme in a heavily left leaning community than it would be in a heavily right leaning community.
Thanks Ben! Great to see 80K making progress on this front! And while I haven’t crunched the numbers, my impression is that 80K’s podcast has also been featuring a significantly more diverse set of guests than when the podcast first started- this also seems like a very positive development.
Given the nature of your work, 80K seems uniquely positioned to influence the makeup of the Longtermist ecosystem as a whole. Do you track the demographic characteristics of your pipeline: people you coach, people who apply for coaching, people who report plan changes due to your work, etc.? If not, is this something you’d ever consider?
Thanks Sky! I’ll be in touch over email.
Agreed - though many of the more successful diversity efforts are really just efforts to make companies nicer and more collaborative places to work (e.g. cross-functional teams, mentoring).
Agreed. This makes those sorts of policies all the more attractive in my opinion, since improving diversity is just one of the benefits.
I'm also a little sceptical of the huge gains the HBR article suggests - do diversity task forces really increase the number of Asian men in management by a third? It suggests looking at Google as an example of "a company that's made big bets on [diversity] accountability... We should know in a few years if that moves the needle for them" - it didn't.
I’m also skeptical that particular programs will lead to huge gains. But I don’t think it’s fair to say that Google’s efforts to improve diversity haven’t worked. The article you cited on that was from 2017. Looking at updated numbers from Google’s site, the mix of new hires (which are less sticky than total employees) does seem to have shifted since 2014 (when Google began its initiatives) and 2018 (most recent data available). These aren’t enormous gains, but new hires do seem to have become notably more diverse. I certainly wouldn’t look at this data and say that Google’s efforts didn’t move the needle.
Women: 30.7% in 2014 vs 33.2% in 2018 (2.5% diff, 8% Pct Change)
Asian+: 37.9% in 2014 vs 43.9% in 2018 (6% diff, 16% Pct Change)
Black+: 3.5% in 2014 vs 4.8% in 2018 (1.3% diff, 37% Pct Change)
Latinx+: 5.9% in 2014 vs 6.8% in 2018 (.9% diff, 15% Pct Change)
Native American+: .9% in 2014 vs 1.1% in 2018 (.2% diff, 22% Pct Change)
White+: 59.3% in 2014 vs 48.5% in 2018 (-10.8% diff, -18% Pct Change)