Between working with the GPT-4 API, unfiltered models like LLaMA, and agent toolchains, it strikes me as obvious and self evident that things could quickly get

Between working with the GPT-4 API, unfiltered models like LLaMA, and agent toolchains, it strikes me as obvious and self evident that things could quickly get out of hand even with current capability levels. One we're dependent on it, just as how we very quickly became dependent on airplanes, electricity, and cloud datacenters, we will have to trust the machines because it will not be practical or economical to understand and double check what they are doing in real time. You don't need super intelligence for very bad disasters, just billions of coordinated super speed more-or-less-regular intelligences - which we are at the moment deploying as fast as we can manufacture the silicon. All of history is bad disasters instigated by merely millions of semi-coordinated regular speed regular intelligences, so presumably future disasters will be worse. We have barely begun to feed data into these systems, almost all of the giant models were trained only on text with the exception of GPT-4 which received static images (notably displayed superior performance than it did before image training). If we supply a multimodal system the same or greater array of physical sensing data that animals like humans have, it seems reasonable to assume capabilities will continue to improve beyond what is even capable today, exasperating the issues I described above.