I expect the third, fourth, fifth etc. person we hire to be at least as effective at getting those meetings as current staff were at equivalent tenure, and probably more so. I also expect the team in aggregate to get more effective over time: this is what has happened over and over for each of our workstreams.
This is for a few reasons, also listed in the post:
ControlAI’s success relies on strong processes and infrastructure, not on pre-existing political insider networks or rare and obscure talent. Our lawmaker efforts all started with staff members (who are great!) with no insider networks, and between 0 and a few years of experience in policy. We don’t succeed based on insider connections: we succeed because of our direct, scalable method. New hires also inherit advantages the first hire didn’t have: a refined playbook and existing campaign traction to point to.
Success compounds vertically in each country, and horizontally across countries.
a. Vertically, within a single country, the more lawmakers support a campaign as a result of our meetings, the more other lawmakers learn about extinction risk from AI and the need to tackle the threat from superintelligent AI, making it marginally easier to get more meetings and more lawmakers on board. This is a micro-example of our macro-strategy: the bottleneck right now is lack of awareness, and building common knowledge leads to faster and faster change.
b. Horizontally, across countries, the more lawmakers in a major country support the campaign, the (slightly) easier it is for lawmakers in another country to take the topic seriously, meet us, and support. In the UK, we started from 0. In Canada, Germany and the US, we started with “Dozens of UK lawmakers, across parties, recognize extinction risk from AI and superintelligence as a national security threat”.
Our approach compounds across ControlAI as a whole. Every week, our briefing gets better: our materials, processes, arguments and pitch are improved continuously based on real-world feedback from the meetings we have. Each iteration is propagated across the org.
Given this, the main scaling risk here for me is not that hire 3 underperforms hires 1 and 2. It’s the normal risk of hiring and onboarding well, which we’re actively investing in right now with more onboarding materials, internal and external writeups of our theory of change and our approach, and even more streamlined processes.
Thanks Michael!
I expect the third, fourth, fifth etc. person we hire to be at least as effective at getting those meetings as current staff were at equivalent tenure, and probably more so. I also expect the team in aggregate to get more effective over time: this is what has happened over and over for each of our workstreams.
This is for a few reasons, also listed in the post:
ControlAI’s success relies on strong processes and infrastructure, not on pre-existing political insider networks or rare and obscure talent. Our lawmaker efforts all started with staff members (who are great!) with no insider networks, and between 0 and a few years of experience in policy. We don’t succeed based on insider connections: we succeed because of our direct, scalable method. New hires also inherit advantages the first hire didn’t have: a refined playbook and existing campaign traction to point to.
Success compounds vertically in each country, and horizontally across countries. a. Vertically, within a single country, the more lawmakers support a campaign as a result of our meetings, the more other lawmakers learn about extinction risk from AI and the need to tackle the threat from superintelligent AI, making it marginally easier to get more meetings and more lawmakers on board. This is a micro-example of our macro-strategy: the bottleneck right now is lack of awareness, and building common knowledge leads to faster and faster change. b. Horizontally, across countries, the more lawmakers in a major country support the campaign, the (slightly) easier it is for lawmakers in another country to take the topic seriously, meet us, and support. In the UK, we started from 0. In Canada, Germany and the US, we started with “Dozens of UK lawmakers, across parties, recognize extinction risk from AI and superintelligence as a national security threat”.
Our approach compounds across ControlAI as a whole. Every week, our briefing gets better: our materials, processes, arguments and pitch are improved continuously based on real-world feedback from the meetings we have. Each iteration is propagated across the org.
Given this, the main scaling risk here for me is not that hire 3 underperforms hires 1 and 2. It’s the normal risk of hiring and onboarding well, which we’re actively investing in right now with more onboarding materials, internal and external writeups of our theory of change and our approach, and even more streamlined processes.