Just in case you haven't seen it, we (Probably Good) have written an overview on mental health, which comes to a similar conclusion on it being a serious global problem. It highlights a few high-impact organizations working in this space, in addition to those already mentioned here by others!

Happy to clarify: What you're missing is that there are tons of impactful roles—and people who are interested in them—that aren't part of our highlighted roles. It's perfectly fine to focus on the subset of roles where there's more confidence in the impact (though never certainty), which is why we've set up a filter for it. But we've designed our board primarily for people who are considering impactful roles both inside and outside that subset, which we expect to be the right call for many (when considering factors like fit, absorbency, counterfactual impact, etc.).

So we think that a potential way to view this is:

• For someone who seems primarily interested in AI safety & policy, you can recommend 80K.
• For someone who seems primarily interested in more traditional EA roles, you can recommend the Opportunities Board (or the highlighted filter on our board).
• For someone who seems interested in a wider range of impactful roles across cause areas, you can recommend the Probably Good board.

There are also smaller differences, such as that 80K and us offer custom email alerts and are stricter about removing expired roles, but I expect these differences will narrow as the Opportunities Board develops, and the above seems like a useful heuristic.

Thanks for the question! We’re excited to collaborate on this with CEA, as well as with other orgs who asked to source roles from our job board.

Based on our current understanding, here’s how we’re thinking of what to recommend:

• For people interested in AI safety & policy: 80K has the clearest focus on roles within this cause area.
• For people interested in roles where there’s more confidence in the expected impact: CEA’s board or the highlighted orgs filter on our board seem most relevant (~20% of the roles on our board fall under this filter, and the Opportunities Board includes most of those).
• For people interested in a range of impactful roles across cause areas: Our (Probably Good’s) board has the widest coverage.

Thanks for flagging this use case! We don't have a separate API or raw export yet, but it's definitely on our list. 

Hi Constance, we've set up a public Airtable that you can use to set up a filtered job-board feed in Slack (instructions here). Hope this helps, and let us know if you have any comments or questions!

Our board now has more roles than before (1600+), and a public Airtable version that you can use to set up custom views and automations (including with Slack).

A quick guide for using the new Airtable:

1. Open the public Airtable and click "Use this data". Make sure "Create a synced table" is selected. Choose which Airtable base you'd like the jobs data to live in. This creates a read-only synced table with our published roles.
2. Create a filtered view in the new table (e.g., filter by cause area, location, or role type).
3. From here, you can set up Slack notifications:
   1. Trigger: "When record enters view", selecting the filtered view you created in step 2. 
   2. Action: "Send a Slack message" (via Airtable’s built-in Slack integration)
   3. Compose your message using field tokens to pull in live data from each role, e.g. New role: {Job Title} at {Org Name} | {Job URL}. Use markdown for basic formatting like bold or italics. 

If you use our job board, here’s a few ways you can help us to help you:

• Test out the new Airtable and let us know if there are any issues or if you do anything cool with it.
• If you land a role that you found on the job board, please get in touch! Even a short message about how our services helped you makes a huge difference to our ability to continue providing these services.
• If you know of any orgs you think we should monitor for the board (including ones you work for), please share them!
• If you work at an org that's listed on the board, note that links to your roles from our job board automatically include utm_source=probablygood_board so if you track referral sources, you'll be able to see applications that came via us. If you have a question on your application forms regarding where candidates heard about the role, please also consider adding "Probably Good" as an option. 
• If you’re a hiring manager/recruiter who ends up hiring a candidate who found your role through our job board, please let us know!

Other than that, please also share the job board with people you think could benefit from it, and get in touch with us if you have any feedback or other suggestions. Thank you!

AI systems that match or exceed human intelligence could very plausibly arrive within the next decade, and raise some significant challenges as they do. Alongside the well-known issues surrounding AI safety, there are many other potential problems that we don’t yet seem prepared for, but that could affect society on a huge scale. Forethought has published lots of research on this recently, and we wanted to cover some of the key points for people who might be interested in exploring some of these challenges with their career.

A few of the issues that seem particularly important:

• How a sharp acceleration in technological progress could leave us unprepared for new technologies, including potentially dangerous ones like engineered pathogens.
• How growing reliance on AI for information could reshape how individuals and institutions form beliefs, and the risks this might bring.
• The prospect of power and value lock-in, where AI provides the means for institutions and groups to entrench power dynamics and values.
• Questions around AI sentience and welfare, and why now may be a particularly important window for thinking about them.
• Ideas for how people can engage with these problems through their career, along with relevant organizations in the (broad) space.

Here’s an excerpt from our section on the risks of accelerated technological progress:

We can think of technological development as akin to pulling balls from an urn. As we develop each new piece of technology, it’s like we’re reaching into the urn hoping to pull out balls that will help humanity. Many of these are straightforwardly beneficial, like vaccines and other medical technologies. But some balls can be highly dangerous, like nuclear technology. The trouble is, we have a limited ability to know whether technology will harm us or help us until we’ve developed it.

The scientific speedup that advanced AI may bring is like tipping this urn upside down, spilling thousands of balls onto the ground at once. If this happens, we’ll have little time to evaluate and prepare for each new technology before the next arrives, leaving us able to do little more than hope that one of these destructive technologies isn’t revealed.

You can read the full article here, and explore the many other cause areas we’ve covered here.

We recently published an interview with Matthew Coleman - another entry in our Career Journeys series. Matthew is the Executive Director of Giving Multiplier, a platform that encourages donations to highly effective charities through donation matching. Before this, he completed a PhD in psychology, researching the psychology of altruism.

The interview covers quite a lot of ground, but a few of the things we talked about include:

• The gap between what a career looks like from the outside and what it's actually like day-to-day.
• Advice for people wanting to make an impact through psychology.
• The tension between keeping your options open and committing to a path.

Here’s one of our favorite extracts from the full interview:

On engaging with the (often mundane) realities of academic research:

I learned a lot. By the time I started my lab manager role, I was fairly confident I wanted to do a PhD. But my research lab in undergrad, which I loved, was a very small lab where I was working closely with the faculty advisor, and I wanted to try out a larger lab studying different topics to explore a bit more.

As the lab manager of an unusually large lab, I got a bird’s-eye view of a lot of the research projects going on and understood what the day-to-day looked like, whether that was grant applications, hiring and onboarding, or actually conducting research myself alongside my colleagues. I found the experience amazing and fascinating and really intellectually stimulating, which confirmed that I wanted to go the PhD route, so I followed through on my original plan from undergrad.

[…] I was certainly very fortunate to have gotten a lot of hands-on experience in research as an undergraduate, so I think I had a better sense of the day-to-day than many people do. But I do think it’s a very important point, and some related advice I like to give is: when you wake up on a random Tuesday in February, do you actually want to do the things that you have to do? Not just do you like the topics or ideas you’re studying (although that’s of course very important, too). Maybe you read a book, watched a TED talk, or listened to a podcast about some topic you found fascinating, and maybe you do want to pursue work in that domain. But I think the ideas themselves aren’t enough, because you actually have to do the day-to-day work.

So what are the actual responsibilities and tasks you like doing? For example, you may find neuroscience fascinating, but maybe you don’t want to spend a large portion of your workweek interacting with research subjects running brain imaging sessions, or whatever it might be. In such a case, even if you think the subject matter is fascinating, maybe that’s not the best career fit for you. Or maybe you do also enjoy most of the regular responsibilities associated with that career, in which case it could be a great fit. So I think a combination of enjoying the topic itself plus the day-to-day responsibilities is important. I was lucky that, early in my career, I was able to test it out and experiment with which responsibilities I liked more than others. 

That's awesome to hear, thank you for letting us know!

Thanks, Siobhan!

1. We try to assess this type of counterfactual causal attribution through several approaches, including asking people how likely they were to make career changes without our services, looking at other information they provide (like qualitative notes they share), and looking at other information we have on them (like which of our services they used). This is very much a work in progress though.
2. Mainly, being broader in who we can help and with what, in terms of causes we touch on, audiences we engage, and services we provide. As one example, this sometimes involves doing 1:1 advising with people who are interested in career impact and want a broad perspective across a range of causes, including ones that are underrepresented by other orgs (though we might then refer them to a specialist org). As another example, this involves aiming to offer a broader range of impactful roles on our job board than other organizations might.
3. (Answering this question from a generalizable hiring perspective, which seems more helpful and appropriate here, though note there’s significant variances across orgs and roles.) While internal rounds sometimes make sense, that’s not the case for a tiny org with only 1-2 potential hires. Closed rounds can also make sense sometimes, but only when you’re confident you’ll get the right candidate pool from this, given how important and hard it is to get hiring right (particularly for a small org, and even more so for a leadership role). The time savings aren’t necessarily great either, since many hiring costs are fixed (e.g., the time it takes to create a job description), and many of the seemingly marginal costs are actually fixed too (e.g., the time it takes to do interviews, if you have a cap for the number of interviews you can do).