Introduction Often when we as legal scholars write about AI, the major risk is that we create, destroy, discuss or dissect AI law without adequately understanding AI itself and its various technical details or complexities. It is with great pleasure, then, that we have all watched this situation play out
One of the few downsides of having degrees and job experience in both AI and Law is that at any given time, the media is hyping up and misrepresenting at least one non-story between them, using a mixture of journalistic creativity and the ignorance of the general public on that
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Introduction Law is a deep, complex, and highly compartmentalised field where specialism is the status quo. For this reason it is difficult for lawyers to get to grips with where the field of 'AI Law' is at present - never mind those in the technical, sociological, policy, or governance sides.
Tl;dr - AI Safety, AI Alignment, and AI-related Longtermism (i’m gonna use AI Safety as a catch-all) all require strongly multidisciplinary solutions. Even purely technical solutions such as value alignment require input from policy, law, and governance to be effective or even deployed in real-world the first place.
Today I want to say something quite unpopular - it is my belief that the talent bottleneck is a barrier we have created ourselves. Not only are we failing to attract talent from a wide variety of sources, but we actively push away talent that approaches us.
I wrote a blog post recently on how EA is losing large amounts of talent both passively and actively due to socioeconomic factors [https://legal-longtermist.ghost.io/why-eas-talent-bottleneck-is-a-barrier-of-its-own-making/] , and promised to write a shorter, punchier piece listing ways we can address this issue. So here we are. They’re not
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