Well done Roman! The post is great (and important!). And I love visual storytelling like this - there should be more of it in the AI safety field. This Hans Rosling video is one of my favourite examples of data visualisation / storytelling, in case you're not familiar with it already:
I think the pipeline (or funnel) is a a solid analogy - we are trying to direct people towards impactful contributions and impactful careers. And that pipeline is very leaky - there are a lot of people who are interested in contributing to fields like AI safety, but arent able to navigate the process. Some of the reasons you've mentioned in your article. Additionally, if hiring organisations get 300 to 500 applicants for each position, they can choose the top candidate, which potentially means that many similarly capable candidates are not selected. Some of those candidates will eventually get discouraged and find work in other fields - not because they were not passionate about making an impact, but because at some point they have done as much as they can, and they need a job. This is not the fault of the candidate - this is an employment marketplace failure, where people who have skills and want to work are not able to be matched to a role in what ought to be a rapidly scaling ecosystem.
To give credit where credit is due, I have seen some organisations starting to provide rejection letters (at least at first round) which point candidates towards existing resources and courses that could help them gain more context. I agree this is a good practice and should be encouraged.
Well done, this is a valuable and thoughtful piece.
I agree that a lot of talent appears to be left on the table currently. There's a high workload for hiring organisations, who need to sort through increasing numbers of applications (including AI prepared submissions). And there's a high workload for applicants, who might collectively spend thousands of hours applying for a single post.
It seems there are worthwhile ideas on how hiring practices could be made more efficient - standardising taxonomies (what do we call positions and functions), establishing competency frameworks for common roles and tasks, standardised terms of reference for common roles, addressing challenges of AI use in applications etc. Through to more ambitious approaches, like running joint recruitments, establishing rosters of pre-qualified candidates, and expanding lower risk / lower commitment ways for organisations and applicants to test their fit.
It's great that organisations can be selective and appoint the top 1% of talented applicants. But if the field needs to grow to meet urgent timelines and risks, it's important to think about other ways that we can do things, while still preserving the culture and values. I think there are models and lessons learned from other industries, and some of these could be valuable for AI safety organisations.
A question - I understand there's an operations group for colleagues working on Ops in EA organisations. Is there any HR working group to look at some of these HR challenges across the field, rather than taking an organisation by organisation approach?
I'm with Racoocoonie and Claude on this one. It's astounding to argue there are no pools of candidates outside the AI safety community that have experience in fieldbuilding, apart from EA community builders.
The environmental movement has decades(++) of experience in fieldbuilding. The Sierra Club was founded 130 years ago for environmental advocacy - it has chapters in every US state and around 4m members. There are social justice movements, LGBTQI movements, religious movements, labour movements, voter registration movements, health movements and development networks, each with decades of fieldbuilding experience. There are tens of thousands of people working in fieldbuilding and organisation roles within these movements.
All of these people are part of different networks (or 'pools', if you prefer). Many of these networks are also present on platforms like linkedin.
However, this is a very niche background, and people who have it are very difficult to find
Honestly, I think it's not so niche. If it's so hard to find people then perhaps we're not looking in the right places?
The other alternative is that we're quite happy with the pool of people we already have and we dont need to try harder to bring in other fieldbuilders. If that's the case, let's not say it's because those people dont exist, please.
Title the role "Senior [whatever]." I think this is ok, but in many fields "senior" is a synonym for "old", so this title causes talented young people to not apply (and untalented old people to apply).
I think 'specialist' works as a title in this situation, without invoking issues of age - eg Finance specialist, Comms specialist etc.
For me TOR are important, and I wonder sometimes if enough time is spent by hiring organisations (including commercial organisations) in defining what they want out of roles. I see Chief of Staff roles in some organisations that are quite strategic, and in other organisations that are essentially an admin assistant. I appreciate defining responsibilities and tasks is especially tricky in startups, where the roles are harder to define, and you might want a true generalist who can do a bit of everything.
If an organisation advertises for a HR manager, and talks about how they are scaling up and rapidly recruiting, I might apply - I've done end to end recruitment roles, performance management, HR policy etc. If the organisation advertises for a 'HR specialist', and talks about recruitment, setting comp, HR compliance across multiple jurisdictions, I've got a better idea what they're looking for and I'm going to screen myself out by not applying because I dont have all that expertise.
I dont think I'm an 'untalented old person' in the first scenario - the organisational asked for something that I've done before, so I apply based on the information that was available. But if the organisation asks for A but really intends B, then everyones' time has been wasted.
5. Ask for referrals from people who I know well enough that I can effectively say "highly skilled generalist" and they will apply that criterion in a way that I would endorse. This is good but means I don't hire from outside my circle.
If everyone hires from within their existing circles then the community doesnt grow - it's just musical chairs with the same people swapping between same organisations. If the thesis is that the community needs to grow to be able to (1) effectively respond to urgent AI safety challenges and (2) effectively absorb and use anticipated increased levels of funding, then to my mind looking at recruitment practices is an important part of the solution.
And I think it's not necessarily about people's ability to do work, but people's perceived commitment to 'the cause' and their perceived 'moral fit' with the organisation.
I think there's a higher importance placed on this by some organisations, and for some roles. But it seems that some degree of 'alignment' is required to be recruited to almost all roles in the EA eco-system.
I'm not taking a stance on whether this is good or bad - people can rightly have opinions both ways on this I think. Just making an observation that it's a factor.
I'm also going to refer to this post that is based on 'context' being a missing criteria for external candidates, but I think this concept includes alignment.
Thanks for sharing your experience Emily! I think your experience is consistent with many of the colleagues I've been speaking with as I go through bluedot courses, CEA bootcamps etc. People are interested in learning more about AI safety, they want to gain context, but the pathways for generalists are not so clear or well developed. I've spoken to mid-career and senior level people who would love to contribute, but its hard for them to find entry points after the initial courses and fellowships. I expect that EA is missing out on some interested and committed people, who cant figure out how to navigate networks to find opportunities (or who give up after a year or two of trying).
I appreciate that EA and AI safety recruiting is done in a high-trust context, and there's a premium placed on alignment and evidence like public writing. I also think that working or volunteering with EA / AI safety organisations is probably the fastest way for people to advance their understanding, once they've reached some baseline level.
Similar to the 'freelancers for good' idea, I wonder if there's a way for recruiting organisations to 'projectise' some of their generalist work a bit more, as an opportunity for recruiting organisations to get some work done, but with a lower level of commitment required in case the recruit isnt a good fit. For example, recruit a short term comms person to develop a communications strategy and brand assets, recruit a short-term HR person to streamline recruitment processes and create banks of exam scenarios, recruit a short-term operations person to look at how systems can be streamlined, bring in a short-term legal person to review templates for legal agreements etc etc.
These are just examples, and different organisations will have different needs. But it seems to me that by opening up these kinds of short-term / lower-commitment roles for external candidates, it would help grow the EA / AI safety field, while helping interested people build their EA understanding. At the end of a short-term assignment, the recruiting organisation ideally has some useful product, the candidate has a new work product they can talk about, and both the organisation and the candidate would both have a clearer sense of whether the 'fit' was right for them.
Adding to this - people with mental illnesses in developing countries are often stigmatised and shunned by their families, and at worst imprisoned. They are imprisoned due to (1) public order offences (ie being disruptive in public) and (2) a lack of other facilities to accommodate them long term (ie hospital facilities or mental health programmes).
There is a lot that could be done relatively cheaply if this was taken up as a priority.
My understanding of most structured interview formats is that follow up or clarifying questions are still expected and encouraged. There's limited value in robotically sticking to a list of identical questions, and missing out on the opportunity to get additional information with a follow-up question.
I find the best interviews feel like a structured conversation. There's interaction between the panel and the candidate, because that's how we really interact when we meet together. There are efforts made to help the candidate feel relaxed and comfortable, and to value the experiences that they share with the panel. I cover the same questions in the same order with the candidate, but we might spend longer on some questions than others, depending on the background and strengths / weakness of the candidate.
Well done Roman! The post is great (and important!). And I love visual storytelling like this - there should be more of it in the AI safety field. This Hans Rosling video is one of my favourite examples of data visualisation / storytelling, in case you're not familiar with it already:
I think the pipeline (or funnel) is a a solid analogy - we are trying to direct people towards impactful contributions and impactful careers. And that pipeline is very leaky - there are a lot of people who are interested in contributing to fields like AI safety, but arent able to navigate the process. Some of the reasons you've mentioned in your article. Additionally, if hiring organisations get 300 to 500 applicants for each position, they can choose the top candidate, which potentially means that many similarly capable candidates are not selected. Some of those candidates will eventually get discouraged and find work in other fields - not because they were not passionate about making an impact, but because at some point they have done as much as they can, and they need a job. This is not the fault of the candidate - this is an employment marketplace failure, where people who have skills and want to work are not able to be matched to a role in what ought to be a rapidly scaling ecosystem.
To give credit where credit is due, I have seen some organisations starting to provide rejection letters (at least at first round) which point candidates towards existing resources and courses that could help them gain more context. I agree this is a good practice and should be encouraged.
Well done, this is a valuable and thoughtful piece.
I agree that a lot of talent appears to be left on the table currently. There's a high workload for hiring organisations, who need to sort through increasing numbers of applications (including AI prepared submissions). And there's a high workload for applicants, who might collectively spend thousands of hours applying for a single post.
It seems there are worthwhile ideas on how hiring practices could be made more efficient - standardising taxonomies (what do we call positions and functions), establishing competency frameworks for common roles and tasks, standardised terms of reference for common roles, addressing challenges of AI use in applications etc. Through to more ambitious approaches, like running joint recruitments, establishing rosters of pre-qualified candidates, and expanding lower risk / lower commitment ways for organisations and applicants to test their fit.
It's great that organisations can be selective and appoint the top 1% of talented applicants. But if the field needs to grow to meet urgent timelines and risks, it's important to think about other ways that we can do things, while still preserving the culture and values. I think there are models and lessons learned from other industries, and some of these could be valuable for AI safety organisations.
A question - I understand there's an operations group for colleagues working on Ops in EA organisations. Is there any HR working group to look at some of these HR challenges across the field, rather than taking an organisation by organisation approach?
I'm with Racoocoonie and Claude on this one. It's astounding to argue there are no pools of candidates outside the AI safety community that have experience in fieldbuilding, apart from EA community builders.
The environmental movement has decades(++) of experience in fieldbuilding. The Sierra Club was founded 130 years ago for environmental advocacy - it has chapters in every US state and around 4m members. There are social justice movements, LGBTQI movements, religious movements, labour movements, voter registration movements, health movements and development networks, each with decades of fieldbuilding experience. There are tens of thousands of people working in fieldbuilding and organisation roles within these movements.
All of these people are part of different networks (or 'pools', if you prefer). Many of these networks are also present on platforms like linkedin.
Honestly, I think it's not so niche. If it's so hard to find people then perhaps we're not looking in the right places?
The other alternative is that we're quite happy with the pool of people we already have and we dont need to try harder to bring in other fieldbuilders. If that's the case, let's not say it's because those people dont exist, please.
Title the role "Senior [whatever]." I think this is ok, but in many fields "senior" is a synonym for "old", so this title causes talented young people to not apply (and untalented old people to apply).
I think 'specialist' works as a title in this situation, without invoking issues of age - eg Finance specialist, Comms specialist etc.
For me TOR are important, and I wonder sometimes if enough time is spent by hiring organisations (including commercial organisations) in defining what they want out of roles. I see Chief of Staff roles in some organisations that are quite strategic, and in other organisations that are essentially an admin assistant. I appreciate defining responsibilities and tasks is especially tricky in startups, where the roles are harder to define, and you might want a true generalist who can do a bit of everything.
If an organisation advertises for a HR manager, and talks about how they are scaling up and rapidly recruiting, I might apply - I've done end to end recruitment roles, performance management, HR policy etc. If the organisation advertises for a 'HR specialist', and talks about recruitment, setting comp, HR compliance across multiple jurisdictions, I've got a better idea what they're looking for and I'm going to screen myself out by not applying because I dont have all that expertise.
I dont think I'm an 'untalented old person' in the first scenario - the organisational asked for something that I've done before, so I apply based on the information that was available. But if the organisation asks for A but really intends B, then everyones' time has been wasted.
5. Ask for referrals from people who I know well enough that I can effectively say "highly skilled generalist" and they will apply that criterion in a way that I would endorse. This is good but means I don't hire from outside my circle.
If everyone hires from within their existing circles then the community doesnt grow - it's just musical chairs with the same people swapping between same organisations. If the thesis is that the community needs to grow to be able to (1) effectively respond to urgent AI safety challenges and (2) effectively absorb and use anticipated increased levels of funding, then to my mind looking at recruitment practices is an important part of the solution.
I think alignment -is- the right word.
And I think it's not necessarily about people's ability to do work, but people's perceived commitment to 'the cause' and their perceived 'moral fit' with the organisation.
I think there's a higher importance placed on this by some organisations, and for some roles. But it seems that some degree of 'alignment' is required to be recruited to almost all roles in the EA eco-system.
I'm not taking a stance on whether this is good or bad - people can rightly have opinions both ways on this I think. Just making an observation that it's a factor.
I'm also going to refer to this post that is based on 'context' being a missing criteria for external candidates, but I think this concept includes alignment.
https://forum.effectivealtruism.org/posts/b82SLXwEHRCs3TFJA/why-experienced-professionals-fail-to-land-high-impact-roles
Thanks for sharing your experience Emily! I think your experience is consistent with many of the colleagues I've been speaking with as I go through bluedot courses, CEA bootcamps etc. People are interested in learning more about AI safety, they want to gain context, but the pathways for generalists are not so clear or well developed. I've spoken to mid-career and senior level people who would love to contribute, but its hard for them to find entry points after the initial courses and fellowships. I expect that EA is missing out on some interested and committed people, who cant figure out how to navigate networks to find opportunities (or who give up after a year or two of trying).
I appreciate that EA and AI safety recruiting is done in a high-trust context, and there's a premium placed on alignment and evidence like public writing. I also think that working or volunteering with EA / AI safety organisations is probably the fastest way for people to advance their understanding, once they've reached some baseline level.
Similar to the 'freelancers for good' idea, I wonder if there's a way for recruiting organisations to 'projectise' some of their generalist work a bit more, as an opportunity for recruiting organisations to get some work done, but with a lower level of commitment required in case the recruit isnt a good fit. For example, recruit a short term comms person to develop a communications strategy and brand assets, recruit a short-term HR person to streamline recruitment processes and create banks of exam scenarios, recruit a short-term operations person to look at how systems can be streamlined, bring in a short-term legal person to review templates for legal agreements etc etc.
These are just examples, and different organisations will have different needs. But it seems to me that by opening up these kinds of short-term / lower-commitment roles for external candidates, it would help grow the EA / AI safety field, while helping interested people build their EA understanding. At the end of a short-term assignment, the recruiting organisation ideally has some useful product, the candidate has a new work product they can talk about, and both the organisation and the candidate would both have a clearer sense of whether the 'fit' was right for them.
Hey Sophie,
I have quite a lot (decades) of grant making and grant administration experience.
Happy to brainstorm with you if you're interested in pulling together an introductory level course etc. Send me a DM :)
Adding to this - people with mental illnesses in developing countries are often stigmatised and shunned by their families, and at worst imprisoned. They are imprisoned due to (1) public order offences (ie being disruptive in public) and (2) a lack of other facilities to accommodate them long term (ie hospital facilities or mental health programmes).
There is a lot that could be done relatively cheaply if this was taken up as a priority.
I fully agree.
My understanding of most structured interview formats is that follow up or clarifying questions are still expected and encouraged. There's limited value in robotically sticking to a list of identical questions, and missing out on the opportunity to get additional information with a follow-up question.
I find the best interviews feel like a structured conversation. There's interaction between the panel and the candidate, because that's how we really interact when we meet together. There are efforts made to help the candidate feel relaxed and comfortable, and to value the experiences that they share with the panel. I cover the same questions in the same order with the candidate, but we might spend longer on some questions than others, depending on the background and strengths / weakness of the candidate.