How to get into AI policy (part 1)

B stands in front of the US Capitol holding up a hand to gesture toward the iconic dome

I’m frequently asked for advice on how to break into the industry I’m in or how to achieve a position I’ve held. I’ve been privileged to serve in many interesting and varied roles across sectors, from small nonprofits and garage startups to huge multinationals and even the US Federal Government. While I personally owe a lot of my journey to privilege, luck, and the good graces of others, I know that “be lucky” isn’t particularly useful advice. In the spirit of providing something actionable, I’ve gathered here some reflections on things that I think have served me in my journey. I hope these reflections will be helpful for others on their journey as well, and I encourage those with experience in this space to share more about their experiences, lessons learned, and advice as well!

Note: For the purpose of this post, I’ll be talking about “getting into AI policy” and offering some specific examples, but most of these suggestions should hold regardless of what it is specifically you want to do. For more on entering the tech policy field, see my Emerging Technology Policy Careers profile.

This series comes in five parts:

  1. Mindset
  2. Be perceived
  3. Be the reply guy you want to see in the world
  4. Don’t wait to do the work
  5. Pay it forward (don’t skip this!)

Once all five parts are posted, I'll make it possible to read them all in one place, if you're into that kinda thing.


Before we get started, it’s important to acknowledge that in many ways “AI policy” isn’t really A Thing. It may be becoming more of A Thing, but more often AI policy is actually privacy policy, intellectual property policy, trade policy, labor policy, etc with a technology angle. AI policy is very mushy. Since it can be thought of as the Venn diagram intersection of AI and [insert just about any other sort of policy here], that means there are a million ways to “be in it,” and even more ways to “get into it.”

Unlike some other fields or career paths, there isn’t (yet) an agreed upon qualification, like getting a particular certification or degree, that will clarify that you are “ready for AI policy.” This may feel daunting, especially if you are trying to make decisions about what to pursue in school, for instance. On the other hand, this may feel liberating. I studied economics as an undergrad, and some of my AI policy inspirations studied aerospace engineering, international relations, cognitive science and philosophyhistory of art and visual studies, and computer science. There are many different courses of study and life experiences that are relevant to AI policy, and my hope is that the field continues to embrace this variety because we need many diverse perspectives to do this work well.

AI policy is wiggly. (Much of the world is!) There are many possible paths, and there likely (and HOPEFULLY) always will be.

That said, it does help to get specific. Remember “AI policy” isn’t really A Thing. It is everything and nothing. It’s almost like saying you want to work on “academia” or “business.” It is important to be able to articulate the particular elements of AI policy that are interesting to you or that you have skills or experience in.

Maybe there’s an issue you’re especially passionate about. Do you have personal experience with something that makes you an experiential expert? Your particular background or expertise may be needed but missing in the dominant conversation. Perhaps you’re transitioning from another career, and you have a deep understanding of an industry and how AI is impacting (or could impact) that field. Maybe you have technical expertise you can bring to the policy space or a policy background that you're now ready to apply to AI.

Whatever the case, try to go at least one level deeper beyond “AI policy” to give some color to the particular problems you want to solve. If you’re not sure yet, that’s okay. But you should aim to develop an answer (or a couple) to this question if you’re serious about getting into this space.

Another thing to acknowledge before we dive in: while there are many possible paths into AI policy, there are also many possible humans. If you want to get a job in this space (which is NOT the only way to be involved, more on that to come!), you’ll need to convince another person to pay actual money to employ you. The AI policy market is competitive. There are lots of people trying to enter this domain, so it’s important to understand what value you bring and what other people actually want.

When I say “what other people want,” I use the word “want” on purpose. There are lots of things that are in need of doing in the world, but the harsh reality is that if you want to do this work professionally, you are subject to the forces that make people willing to pay for things and, thus, to the desires of people who have the money to pay for them. Be prepared to think about what skills and experience you have to offer and how your labor “adds value” compared to alternatives. It also helps to understand that careers in this space are often full of compromises (on things like salary and location but also things like subject matter, impact, and even personal safety).

Also worth noting: Pretty much everywhere is shaped by dominating forces of capitalism. Everyone has funders/clients to satisfy, be they in nonprofit, academia, government, or corporate work. We may be able to create enclaves as we build alternatives, but even those spaces will  have to interface with capitalism, at least at their edges.

Sorry. I know this is a kinda spooky start to a piece on entering an exciting new field, but I feel like if you’re ready to navigate the ambiguity of qualifying expertise and to acknowledge the power dynamics at play, then you’re ready to really get started.

Step 1: Mindset

Step 2: Be perceived