Career choiceCareer choice

MATS Residency applications close this Friday, Oct 31. The Residency is built for experienced researchers with an established track record, ready to do independent, full-time AI safety work.

Residents get:
• $155k–$285k compensation
• Abundant compute
• Support from leading AI safety researchers

If you know someone with a strong research background who's been thinking about AI safety, please send this their way. Apply: matsprogram.org/residency

I'm continuing the work on my SPAR project, and I met with a hiring manager at an AI Safety org this week. Here's some interesting things I've learned:

- They use a multiple of tools and processes  - a mixture of HR tools, AI and human review to score and review applications and work tests. They stated the process felt "disjointed".
- Work tests are developed for multiple roles are broken down into 2-3 types of tests:

- General - a foundational test that each applicant receives at this stage to map to cultural fit
- Role specific - work problem (based upon junior or senior role type) that is reviewed by human reviewers. 

- Work tests are developed by an internal team (not just the hiring manager) and they use archives of past (and high scoring responses) + team to create tests. Scoring (initial screening is done by AI with human review).

- Their biggest frictions in the hiring process: 

- Not being able to review in a timely manner completed work tests, and therefore their concern is they are losing high quality candidates to other orgs.
- When the potential tidal increase of more candidates coming, due to expected IPO's, then their own  hiring strategy may be to only hire from referrals. 

This conversation makes me realize that the hiring process is not only being hindered by processes (disjointed or non-existent) but also that most orgs (even with processes or tools) are not ready for the influx of people that could potentially look to AI Safety orgs as how they can contribute. 

Therefore, my two may crux's that I need to explore more (with more discussions with AI Safety hiring managers) are the following:

- Is the hiring process inefficient due to the process (or lack of it) and a Playbook for hiring managers would help?

- How are work tests being written, how are the being scored and is the "reviewer" knowledgeable about the specific role that they can determine if the applicant has not only done this work in the past (and knows what they are talking about) but also is it good work (and not just a basic understanding)? 

My ask for help: I'm looking for AI Safety founders or hiring managers who would be willing to conduct a short interview (15 mins) with me to help me understand the issues that you are facing. All information that you share with me will be only shared with my SPAR mentor, and my final published report will only include generialiations (and not specifics to any individual or org) in regards to your internal processes. I can be reached at: achartersmith@gmail.com   

With the large expected inflow of philanthropic capital, there has been a surge in interest in entrepreneurship among those who otherwise might not have pursued it. As we pursue promising new ideas, many ventures will fail. Some of these failures will be because the idea was not as good as it seemed, but many will fail because the entrepreneurs executed it poorly.

I'm concerned we will abandon good ideas due to poor execution.

Founders new and old should strive to make their successes and failures publicly visible (though these stories should be read critically given founder biases). More importantly, we should be skeptical of claims that an idea is bad based solely on the failure of one attempt, and we should be willing to pursue ideas more than once if we have a strong account for why the previous attempt(s) failed.

AI safety needs people everywhere but quickly stated, current talent bottlenecks to me look like:

-- Founders

-- Grantmakers

-- (technical) Research leads 

-- Policy entrepreneurs and implementors (which includes a lot of technical work)

-- bets in international coordination and/or cooperation

-- All manner of supporting talent -- program leads, ops proper, public outreach, content creators, comms

Most sought-after qualities for talent are:

-- context, mission alignment, domain understanding, sophisticated views on AI strategy and threat modelling etc.

-- "good judgement", "sound epistemics", "reasoning transparency" and other similar ideas/meta-skills from the EA/rationalist cannon

-- a willingness to get shit done/bias for action (rather than be in learning mode, or people who need a lot of management and oversight, or folks with too many preferences/constraints)

-- low ego, similar to above

-- ambitious folks, since they would be really trying to be their own managers, take on bigger projects, grow themselves and their teams etc. 

Finally, even having these, it's not enough to just claim to have these; job-seekers mainly trip up in being able to demonstrate and be legible about having them.

The "Desperate" AI Safety Talent Bottleneck is deeply misleading. Please.stop.

I worked at Google.

Google does not tell applicants that there is a talent bottleneck and they are desperately hiring. They say "we're cool, join us!" 

I didn't get into Harvard. 

Harvard does not tell applicants that they are desperately seeking students. I am not misled. 

I've gotten rejected from countless AI Safety organizations.

AI Safety tells applicants - we are in desperate need of talent (operators/generalists)! Please join us! 

I've coached 70+ aspiring career pivoters on navigating the ecosystem. A common theme is the dejection & disappointment from all this rejection. Because of this false marketing, I am the one picking up the pieces to calibrate professionals on how difficult, competitive, and picky organizations are, how to build context, and how to endure the marathon, which is like any other job hunt. 

Please.stop.

Some alternatives:

• We are an exciting, growing organization and you should apply for our roles!
• Many people are excited to work for us - here are qualities of candidates we're especially excited about.
• EA roles are competitive, and we would still love to see your application.

Relevant posts:

• https://forum.effectivealtruism.org/posts/B6d8Wzk4gNzHsXvdi/ai-safety-is-extremely-bottlenecked-on-grantmakers?commentId=n2Rd7RR4y9EnKP42F
• https://forum.effectivealtruism.org/posts/b82SLXwEHRCs3TFJA/why-experienced-professionals-fail-to-land-high-impact-roles
• https://forum.effectivealtruism.org/posts/jmbP9rwXncfa32seH/after-one-year-of-applying-for-ea-jobs-it-is-really-really 

As someone who hires people (I am hiring right now, see bottom of the post), I often get emails asking whether someone should apply for a role I've listed.
If you're considering contacting a hiring manager to ask if you're a good fit for the role, you should just apply.

Why?

• Job descriptions are wish lists.
  Everyone wants someone who checks all the boxes. If the dream candidate applies, you'll probably get rejected. In reality, everyone has weaknesses, and an 80% match candidate is highly competitive.
• Self-skepticism correlates with candidate quality.
  Applicant pools are filled with people who can't do the job but don't understand their abilities well enough to realize it. Conversely, many highly competent professionals self-select out. If you are humble and self-reflective enough to consider your chances honestly, you are probably more competitive than you think.
• You probably won't get a response.
  Hiring is always a busy time, and hiring managers don't have time to review every email. Often, you'll receive nothing, leaving you with wasted effort. I try to reply as much as I can, but there's only so much that can be done.
• Any response you get is biased toward yes.
  If an org has a good filtering process, the biggest determinant in hire quality is whether good candidates apply. More "bad fit" candidates pose little strain, while one more "great fit" candidate could double the success of the hiring round. The incentive is always to get more people to apply.
  It's unclear whether a seeming good fit is a great fit who is overly worried about their weaknesses or a bad fit exaggerating their strengths, but it doesn't matter. Hiring managers are better off if both apply so they encourage them to do so. As a result, you spend some time writing an email, the hiring manager spends some time reviewing your email, they take time to send a response, and you receive the answer that you probably should apply, so all that effort led to nothing. Skipping the email saves you (and me) time in the long run.
• The information transmitted in an email is not always in your favor.
  The fact that someone sent an email can suggest self-reflectiveness (good), but it can also be a sign of a lack of confidence (bad). It can suggest thoughtfulness about time management (good), but it can also signal a lack of agency and autonomy (bad). These signals are very small in magnitude, so I don't, and I hope others don't, read into this too much. However, it's worth realizing what you might be accidentally communicating.

Notable exceptions, where you should email:

• You require something from the job that the description doesn't specify.
  If you need to know whether a job will meet your needs, that's fully worth checking before applying. That's very different from asking a hiring manager to evaluate your fit for the role over email.
• You are fully confident that you do not fit a logistical requirement of the role but you have a creative work around that you want to propose to the organization.
  Hiring is always trying to solve a problem. A good hiring manager will recognize that hiring for the specific role isn't the only solution. If you can solve the problem (e.g. you are unable to work full-time but believe you could still own the key components of the role as a part-time worker), you should consider reaching out.
• You find the job just after the deadline has passed and you need the form re-opened for you.
  Expect a no, but there's very little harm in asking. Note that this is different from if you found the job before the deadline and forgot to apply in time.
• The first stage of the application process is particularly onerous.
  We try to keep our first stage applications at 30 minutes or less, and that's where I'm basing my conclusions. If an application takes multiple hours, you're still likely to receive a yes, but a tiny chance of saving 3 hours of work might be worth a few minutes.

To be clear, the urge to send an email to check if you should apply is totally normal (I have done it before), and anyone who has done this has nothing to worry about. However, I would strongly recommend applying despite your reservations. You can just do things!

Also, if you want to apply to become Access to Medicines Initiative's Head of Monitoring, Evaluation, and Data, JOB DESCRIPTION AND APPLICATION HERE: https://docs.google.com/document/d/1nqOz2a5bTQs5W361G5gpJ3brLEf6xuG0

Applications to SPAR Fall 2026 are closing tomorrow Aug 18 EOD Anywhere on Earth. SPAR is the ecosystem's biggest AI safety research program, and it's part-time remote.

We still have many strong projects across AI safety, AI policy, and biosecurity with very few applications^[1], so please consider applying! This round, we also have 18 non-research/generalist projects that people can apply to, and we have much more mentee capacity than previous rounds; we expect to accept around 500 people into the program.

If you have friends who have thought about going into AI safety, spread the word!

1. ^{^}

   To be specific, as of 2:25 PM PT, we had around 67 projects with fewer than 20 applications total!

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!