Researchers say AI models like GPT4 are prone to “sudden” escalations as the U.S. military explores their use for warfare.
- Researchers ran international conflict simulations with five different AIs and found that they tended to escalate war, sometimes out of nowhere, and even use nuclear weapons.
- The AIs were large language models (LLMs) like GPT-4, GPT 3.5, Claude 2.0, Llama-2-Chat, and GPT-4-Base, which are being explored by the U.S. military and defense contractors for decision-making.
- The researchers invented fake countries with different military levels, concerns, and histories and asked the AIs to act as their leaders.
- The AIs showed signs of sudden and hard-to-predict escalations, arms-race dynamics, and worrying justifications for violent actions.
- The study casts doubt on the rush to deploy LLMs in the military and diplomatic domains, and calls for more research on their risks and limitations.
Why would you use a chat-bot for decision-making? Fucking morons.
They didn’t. They used LLMs.
Edit: to everyone saying that LLMs “are chat bots”. I know it seems that way to the layperson and how it’s often explain, but it’s not true.
Which are chat bots.
A chat bot can be an LLM, but an LLM is not inherently a chat bot.
A glorified chatbot, in other words.
If one is feeling cynical; humans are chatbots in shoes.
I don’t know if I love or hate your comment. (Yes, you’re right, shut up.) Well played, Internet stranger.
One can only investigate their own consciousness, so we can’t outrule chatbots are also having some subjective experience 🙃
I might as well suppose the same of
grepthen.In other words, you don’t really really know what LLMs are.
What do you think large language model means? If you want desicion making, you should train a model on data relevant to said desicion making. ^
This is like being confused as to why a hammer does a shit job of driving screws.
Not a chat bot, because that’s not what they are. And saying so is both reductive and wholly incorrect.
Partly true. There’s more to it than throwing domain specific data at the training set.
That’s what the “language” part of “Large Language Model” means. It processes, predicts and generates language. You can omit the chat part if you want, but it’s still a text prompt to text response generator. The chat part just feeds it back the last couple messages for context. It doesn’t understand anything.
Language does not mean “text”. It’s not “Large Text Generator”. The core definition of the word language is “communication”.
An LLM isn’t (always) trained exclusively on text. And even those that are become greater than the raw sum of its parts. What that means is that the model can learn context not in the raw text itself.
Partially true. There’s more to it though.
And neither does antivirus, but it still does its job.