The key decisions were limited to a group of roughly fifteen individuals — the Executive Committee of the National Security Council, or “ExComm” — with President John F. Kennedy himself spending a great deal of time shaping and steering discussions. There was incomplete information, large uncertainty [...] and a lot of chaos.
I expect the initial phase of AI superintelligence management to share these features.
Sounds like it would be a very bad idea to rely on “(democratic) checks and balances” to prevent catastrophic concentration of power, if grabbing such power is possible during a scramble. (E.g. due to the fledgling ASIs being corrigible, or something.)
Possibly important and neglected: What is the plan for the following scenario?
LLM hyperscalers (OpenAI, Anthropic, etc.) go bankrupt [1]
The lesson decisionmakers and the public take away from that is something like “See? All that AI stuff was just hype, AI couldn’t even make a profit. Stories of existential risks were nonsense (or a marketing strategy) all along.”
The political will to pass any kind of regulation (let alone do international coordination) effectively dies.
AGI research continues. (Possibly: lots of researchers looking for a more compute-efficient (and thus dangerous) paradigm.)
Some first-pass thoughts:
Probably a good idea to sometimes try to clearly communicate that LLMs are just one approach to building powerful AIs. Beware leading people to equate “AGI” with “what OpenAI/Anthropic/GDM do”.
OTOH, don’t go fearmongering about possible more efficient/dangerous paradigms; the historical lesson seems to be that warning about world-endingly-dangerous thing X leads lots of Darwin-Award-aspirants going and working on building X.
I haven’t looked into it much, but IIUC, they have hundreds of billions in purchase commitments (chips/infrastructure), and their continued existence depends on being able to scale up their profits fast enough; which seems somewhat precarious?