Expert in AI hardware
In a nutshell: Given that AI is likely to be an especially important technology — and that hardware is an important input for developing and deploying AI — specialists who understand AI hardware will probably have opportunities to positively shape the development of AI. We haven’t yet looked into what those opportunities may be, or how to get into the best position to take them, so we currently can’t confidently recommend this path.
Sometimes recommended — under-researched
This career is potentially high-impact, but we haven't yet researched it enough to recommend it confidently.
Based on a shallow investigation
Why might becoming an expert in AI hardware be high impact?
Advances in hardware — such as the development of more efficient, specialised chips — have played an important role in improving the performance of AI systems and allowing them to be used economically.
There is a common-sense argument that if AI is an especially important technology, and hardware is an important input in the development and deployment of AI, specialists who understand AI hardware will have opportunities for impact — even if we can’t foresee exactly what form they will take.
Some ways hardware experts may be able to help positively shape the development of AI include:
- More accurately forecasting progress in the capabilities of AI systems, for which hardware is a key and relatively quantifiable input.
- Advising policymakers on hardware issues, such as export, import, and manufacturing policies for specialised chips. (Read a relevant issue brief from the Center for Security and Emerging Technology.)
- Helping AI projects make credible commitments by allowing them to verifiably demonstrate the computational resources they’re using.
- Advising on and fulfilling hardware needs for safety-oriented AI labs.
These are just examples of ways hardware specialists might be helpful. We haven’t looked into this area very much (though we do talk about AI hardware as a path to impact at the end of our podcast episode with Danny Hernandez). So, we are pretty unsure about the merits of different approaches, which is why we’ve listed working in AI hardware as only sometimes recommended, rather than as a part of the AI technical safety and policy priority paths. (See an example of how one person has explored this area.)
We also haven’t come across research laying out specific strategies in this area, so pursuing this path would likely mean both developing skills and experience in hardware and thinking creatively about opportunities to have an impact in the area.
If you do take this path, we encourage you to think carefully through the implications of your plans, ideally in collaboration with strategy and policy experts also focused on creating safe and beneficial AI.
Want one-on-one advice on pursuing this path?
If you think this path might be a great option for you, but you need help deciding or thinking about what to do next, our team might be able to help.
We can help you compare options, make connections, and possibly even help you find jobs or funding opportunities.
- What does it mean to become an expert in AI Hardware?
- Podcast: Danny Hernandez on forecasting and the drivers of AI progress
- Podcast: Prof Allan Dafoe on trying to prepare the world for the possibility that AI will destabilise global politics
Read next: Learn about other high-impact careers
Want to consider more paths? See our list of the highest-impact career paths according to our research.
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