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Notes -
Okay, to back up a bit: I'm arguing that today's LLMs couldn't be agentic even if they wanted to be, so their behavior shouldn't "lower one's p(doom)". Future LLMs (or not-exactly-LLM models), being much more capable and more agentic, could easily just have different properties.
They can write things that sound like workable plans, but they can't, when given LangChain-style abilities, "execute on them" in the way that even moderately intelligent humans can. Like, you can't currently replace a median IQ employe directly with huge context window GPT4, it's not even close. You can often, like, try and chop up that employe's tasks into a bunch of small blocks that GPT-4 can do individually and have a smaller number of employees supervise it! But the human's still acting as an agent in a way that GPT-4 isn't.
I think the alignment concern is something like - once the agents are complex enough to act on plans, that complexity also affects how they motivate and generate those plans, and then you might get misalignment.
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