Billions of dollars don’t solve problems
Bill Gates has joined the club of people who realise there’s no plan for making AI go well.
We’re barrelling towards a world where AI companies and the US and Chinese governments amass extreme power; where the ability to destroy civilization with bioweapons is democratized to millions; where rogue AI swarms coordinate to pursue their alien desires; and where laypeople lose their livelihoods en masse.
There’s so much to do, so many problems to solve, and so little time.
But it’s not just a bunch of nerds who are worried about AI anymore. A billion people use ChatGPT every week. Tens of millions of people watched AI 2027 videos describing how AI could destroy civilization. Opposition to datacentres is becoming a powerful political force. But there’s still only 2-3,000 people working full-time on making AI go well.
Meanwhile, philanthropic foundations like Good Ventures and the OpenAI Foundation have tens of billions of dollars they want to spend on this issue. The “third wave of philanthropy” is upon us. But they’re unable to deploy capital at anywhere close to the rate they want to.
Why aren’t we able to turn the growing body of capable, concerned people, and billions of dollars of philanthropic capital, into solutions to the most important problems?
I thought I wasn’t smart enough
Many moons ago, in the before-times of 2018, I was an engineering student worried about factory farming and climate change. I thought maybe I’d start a cultivated meat company, or launch a YouTube channel on how to decarbonise the electricity grid. Then I learnt about AI and bioweapons.
I was already confused about what I should do after graduating. Now I was even more confused. I felt paralysed by the scale of these problems.
I moved to Cambridge in 2021, expecting that the super smart people there would have already figured this stuff out. Instead, I found students who cared deeply about doing good, who were worried about catastrophic threats, but were equally confused. The one reading group on AI safety was scaring away newcomers with all its jargon, while the regulars also didn’t know what they were talking about. How could this be the case! This is one of the world’s most important problems, and these are some of the world’s smartest people.
I realised this was much bigger than me or my friends. The field lacked the infrastructure needed to mobilise people into action. If that talent infrastructure didn’t get built, the problems would not get solved. This was the insight behind BlueDot’s founding.
Our strategy: Build talent infrastructure
Our mission is to build the workforce that protects humanity. For us, “winning” is when the most important problems in AI safety and biosecurity have capable owners, who then build the teams and assemble the capital needed to solve those problems.
Examples of people “owning problems” include an entrepreneur founding an organisation that audits AI companies’ safety practices, an advocate taking responsibility for getting AI transparency legislation passed, an operator building the hiring system a biosecurity nonprofit needs to triple its team, and a researcher investigating which threats are most urgent for a specific decision-maker to prioritise.
Building that workforce requires talent infrastructure: the organisations, programs and activities that find talented people and support them on their journey into full-time impactful work.
So, what’s preventing talented people from going full-time owning important problems? What are they missing, and what do they need?
Awareness: Most people on Earth have no idea that a few companies in San Francisco are trying to build a technology that outcompetes humans at everything. Talented people need to know that there’s a threat, that they’re needed, and how to get involved.
Context: The AI safety and biosecurity fields are built on decades of dialogue, debates, and drama. Navigating these fields becomes much easier once people spend a few hundred hours learning about their history, dissecting arguments about threats and mitigations, and understanding who’s working on what and why.
Relationships: Most jobs aren’t posted publicly. The spiciest takes live in private google docs. Co-working spaces are invite-only. Backdoor references are standard for job and grant applications. Collaborations are born during spontaneous conversations. High-trust relationships give people access to opportunities and information they wouldn’t otherwise have, and those relationships arise from repeated positive interactions, and ideally in-person.
Direction: People need to understand which problems are unsolved, what’s already been tried, and where their skills could help. They need to know what challenges organisations face, what type of people they’re looking for, and what funders are excited to fund. They need feedback that helps them develop their own judgement about what’s most impactful. And given the dual-use nature of AI and biology, they also need guidance on how to avoid harmful directions.
Capital: Few people have enough runway to quit their job and then spend months figuring out how to transition into the field. They have bills to pay and mouths to feed. It could take 6 months of full-time effort to overcome the aforementioned challenges before they receive their first AI safety paycheck. This becomes possible if they receive a grant to bridge the gap.
Conviction: The pace of AI is overwhelming and it’s easy to feel hopeless. However, we can and we will succeed, and it will be because a small group of people thought hard about what to do, and then worked extremely hard to make it happen. Conviction can arise due to inspiring leaders, learning about small wins, and internalising how bad and how good the future could be, and that there are paths we can take to steer things in a better direction.
The field has built useful routes for junior talent into research and policy, including BlueDot’s online courses, research fellowships like MATS, GovAI and Pivotal, training programs like ARENA, and placement programs like Horizon and Tarbell. However, most people still struggle to see where they fit and how they can get involved. This includes a range of backgrounds, including operators, diplomats, communications experts and founders.
For the research fellowships, many people assume that specific academic credentials are required. Others assume that online courses are only for young people, or that the field doesn’t actually need their expertise.
Building AI safety and biosecurity talent infrastructure is tractable, neglected and desperately needed.
Other fields have built infrastructure that we can draw inspiration from too: coding bootcamps support thousands of people to go from low-income to high-income jobs after only a few months of training; militaries provide months of intensive, specialised training to create fighter pilots, medics, engineers, and infantry soldiers; quant firms recruit mathematicians from top universities and then train them in trading.
While AI safety is more complex and fast-moving than these fields, they demonstrate that we could be operating at a much larger scale and quality than we are today.
How BlueDot is executing on this strategy
We’re building pipelines that support exceptional people from their first engagement with AI safety and biosecurity, to being full-time and taking responsibility for an important problem. We want to minimise the time between us identifying an exceptional person and them starting to produce impact. And we want to maximise the total number of people who go through this pipeline, while maintaining a high talent bar.
We’ve raised $71M so far to make this happen.
As of September 2026, our courses and grantmaking are live. We’ve launched our first experimental in-person programs. And we’re in the process of securing a large campus in downtown San Francisco.
Courses: Our online courses train thousands of people each quarter, providing them with their first tens of hours of engagement with the field, and relationships with motivated peers. They’re already the default recommendation for new people in the field, they’re growing 10% each month, and they’re a great filter for people who take these ideas seriously. Of the 9,000+ people who’ve done our courses so far, 1,200 are in impactful roles today.
In-person programs: We’re launching 1-week and multi-month in-person programs for a smaller, more select group of people. These programs help them gain more context, build deeper relationships with longtime members of the field, and give us more information about them to inform grant-making decisions. These programs will run each month. This includes Incubator Week, AI Security Bootcamp, Context Week and the planned Context Program.
Grant-making: Coefficient Giving has handed over its career transition grants program to BlueDot. Our grants range from $100 to $200,000. We want to remove all financial barriers preventing exceptional people from going all-in on AI safety and biosecurity, by making career transitions and early projects financially possible.
Physical campus: To enable our in-person programs, we’re building a campus in downtown San Francisco that will accommodate more than 200 people.
Talent investors: We’re building a team of talent investors that provide personalised support for a small number of the most exceptional people we source. Our talent investors will recruit and headhunt exceptional people, build strong relationships with them, diagnose their blockers, and support them until they’re full-time owning an important problem.
Every time an exceptional person we’ve supported goes full-time on an important problem, we ring a blue bell in the office.
How you can help
BlueDot’s near-term bottleneck is also talent. We’ve raised $71M, but we’re only 15 people. We could grow 3-5x over the next year if we find exceptional people who have enough context on AI safety and biosecurity to contribute to our mission, and are motivated to work on talent and field-building.
If you want to help build this infrastructure, see our open roles or email me at dewi@bluedot.org.
And if you know someone who could be protecting humanity, but hasn’t yet made the move, please direct them towards our courses, programs and grants!
There are twice as many people working at Docusign (7,000+) than there are working full-time on helping AI goes well!
I just have to say thank you for the opportunities presented here and your vision regarding AI & Agentic governance. I'll send through my white paper on AI governance for Grant consideration.