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Comment by throw1235435

14 hours ago

Not really. I used to think more general with the first generation of LLM's but given all progress since o1 is RL based I'm thinking most disruption will happen in open productive domains and not closed domains. Speaking to people in these professions they don't think SWE's have any self respect and so in your example of law:

* Context is debatable/result isn't always clear: The way to interpret that/argue your case is different (i.e. you are paying for a service, not a product)

* Access to vast training data: Its very unlikely that they will train you and give you data to their practice especially as they are already in a union like structure/accreditation. Its like paying for a binary (a non-decompilable one) without source code (the result) rather than the source and the validation the practitioner used to get there.

* Variability of real world actors: There will be novel interpretations that invalidate the previous one as new context comes along.

* Velocity vs ability to make judgement: As a lawyer I prefer to be paid higher for less velocity since it means less judgement/less liability/less risk overall for myself and the industry. Why would I change that even at an individual level? Less problem of the commons here.

* Tolerance to failure is low: You can't iterate, get feedback and try again until "the tests pass" in a court room unlike "code on a text file". You need to have the right argument the first time. AI/ML generally only works where the end cost of failure is low (i.e can try again and again to iron out error terms/hallucinations). Its also why I'm skeptical AI will do much in the real economy even with robots soon - failure has bigger consequences in the real world ($$$, lives, etc).

* Self employment: There is no tension between say Google shareholders and its employees as per your example - especially for professions where you must trade in your own name. Why would I disrupt myself? The cost I charge is my profit.

TL;DR: Gatekeeping, changing context, and arms race behavior between participants/clients. Unfortunately I do think software, art, videos, translation, etc are unique in that there's numerous examples online and has the property "if I don't like it just re-roll" -> to me RLVR isn't that efficient - it needs volumes of data to build its view. Software sadly for us SWE's is the perfect domain for this; and we as practitioners of it made it that way through things like open source, TDD, etc and giving it away free on public platforms in numerous quantities.