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Large language models in national security applications
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Re: Large language models in national security applications
#12If the probability beats human error margin in regards to collateral damage, then sure. That was the sentiment in regards to Level 5 automaton driven vehicles. I see no logical difference, only human sentiment ones.
The problem you have is there's no way to estimate probability in situations like warfare or similar chaotic environments.
Re: Large language models in national security applications
#13If the probability beats human error margin in regards to collateral damage, then sure. That was the sentiment in regards to Level 5 automaton driven vehicles. I see no logical difference, only human sentiment ones.
The problem you have is there's no way to estimate probability in situations like warfare or similar chaotic environments.
Sure you do, it's accumulated heuristics, no different than meteorology, or other macro-sims of chaotic systems.
The difference is that human lives are intentioned for different fates; so the negative cognitive dissonance is going to persist consciously, then sub-consciously.
Re: Large language models in national security applications
#14The paper argues against using LLMs for military strategy, claiming "no textbook contains the right answers" and strategy can't be learned from text alone (the "Virtual Clausewitz" Problem). But this seems to underestimate LLMs' demonstrated ability to reason through novel situations. Rather than just pattern-matching historical examples, modern LLMs can synthesize insights across domains, identify non-obvious patter…
You are using a different definition of strategic than the DoD uses, what you are describing is closer to tactical decisions.
They are talking about typically Org wide scope, long-term direction .
They aren't talking about planning hidden as 'strategic planning' in the biz world.
LLMs are powerful, but are by definition past focused, and are still in-context learners.
As they covered, hallucinations, adverse actions, unexplainable models, etc are problematic.
The "novel strategic approaches" is what in this domain would be tactics, not stratagy which is focused on the unknowable or unknown knowable.
They are talking about issues way past methods like circumscription and the ability to determine if a problem can be answered as true or false in a reasonable amount of time.
Here is a recent primer on the complexity of circumscription as it is a bit of a obscure concept.
https://www.arxiv.org/abs/2407.20822
Remember, finding an effective choice function is hard no matter what your problem domain is for non trivial issues, setting a durable shared direction to communicate in the presence of the unknowable future that can't be gamed or predictable by an advisory is even more so.
Researching what mission command is may help understand the nuances that are lost with overloaded terms.
Strategy being distinct from stratagem is also an important distinction in this domain.
Re: Large language models in national security applications
#15The most obvious way the US national security industry could use LLM's right now is simply to spam foreign adversaries with chatbots. That's their greatest strength right now—a use-case they have amply proven themselves for. This paper comes off as eager to avoid this topic: they (briefly) talk about detecting foreign LLM spam, which is called propaganda, but sidestep the idea of our own side using it. If we were con…
Oh, national security professionals aren't going to be talking about psyops, offensive applications and etc, because such things make a given state look bad - they're an offense against democracy and respect for facts and they make the overt media of a given nation look bad. But hey, leave it to HN commentators to root for taking the gloves off. Not to worry post, I'd bet dollars to donuts the actual classified discussions of such things aren't worried about such niceties. But even more, in those activities of the US and other secret states, that have come to light, these state have propagandized not only enemy populations but also their own. After, have to counter enemies trying to nefariously prevent wars as well.
Re: Large language models in national security applications
#16The most obvious way the US national security industry could use LLM's right now is simply to spam foreign adversaries with chatbots. That's their greatest strength right now—a use-case they have amply proven themselves for. This paper comes off as eager to avoid this topic: they (briefly) talk about detecting foreign LLM spam, which is called propaganda, but sidestep the idea of our own side using it. If we were con…
Or, to rephrase this as a question: Is it ethical to spam another democracy with millions of chatbots pretending to be citizens of that country—if the effect is to manipulate those citizens to [take any action advantageous to US national interest]...?
Just, Devil's Advocate, but ethical or not, that's what we should be doing and what we are doing. Every nation has its sock puppets out there, our job is to stop everyone else' sock puppets, and do everything we can to extend the reach of our own sock puppets.
Re: Large language models in national security applications
#17The most obvious way the US national security industry could use LLM's right now is simply to spam foreign adversaries with chatbots. That's their greatest strength right now—a use-case they have amply proven themselves for. This paper comes off as eager to avoid this topic: they (briefly) talk about detecting foreign LLM spam, which is called propaganda, but sidestep the idea of our own side using it. If we were con…
Oh, national security professionals aren't going to be talking about psyops, offensive applications and etc, because such things make a given state look bad - they're an offense against democracy and respect for facts and they make the overt media of a given nation look bad. But hey, leave it to HN commentators to root for taking the gloves off. Not to worry post, I'd bet dollars to donuts the actual classified discu…
[deleted]
Re: Large language models in national security applications
#18Earlier quoted context omitted.
LLMs can combine cross-domain insights, but the insights they have — that I've seen them have in the models I've used — are around the level of a second year university student. I would concur with what the abstract says: incredibly valuable (IMO the breadth of easily discoverable knowledge is a huge plus all by itself), but don't put them in charge.
The "second year university student" analogy is interesting, but might not fully capture what's unique about LLMs in strategic analysis. Unlike students, LLMs can simultaneously process and synthesize insights from thousands of historical conflicts, military doctrines, and real-time data points without human cognitive limitations or biases. The paper actually makes a stronger case for using LLMs to enhance rather tha…
> Unlike students, LLMs can simultaneously process and synthesize insights from thousands of historical conflicts, military doctrines, and real-time data points without human cognitive limitations or biases.
Yes, indeed. Unfortunately (/fortunately depending on who you ask) despite this the actual quality of the output is merely "ok" rather than "fantastic".
If you need an answer immediately on any topic where "second year university student" is good enough, these are amazing tools. I don't have that skill level in, say, Chinese, where I can't tell 你好 (hello) from 泥壕 (mud hole/trench)* but ChatGPT can at least manage mediocre jokes that Google Translate turns back into English:
问: 什么东西越洗越脏？ 答: 水！
But! My experience with LLM translation is much the same as with LLM code generation or GenAI images: anyone with actual skill in whatever field you're asking for support with, can easily do better than the AI.
It's a fantastic help when you would otherwise have an intern, and that's a lot of things, but it's not the right tool for every job.
* I assume this is grammatically gibberish in Chinese, I'm relying on Google Translate here: https://translate.google.com/?sl=zh-TW&tl=en&text=泥%20壕%20%2...
Re: Large language models in national security applications
#19Earlier quoted context omitted.
The problem you have is there's no way to estimate probability in situations like warfare or similar chaotic environments.
Sure you do, it's accumulated heuristics, no different than meteorology, or other macro-sims of chaotic systems. The difference is that human lives are intentioned for different fates; so the negative cognitive dissonance is going to persist consciously, then sub-consciously.
it's accumulated heuristics, no different than meteorology
Meteorology is based on physics, meteorology doesn't have a hostile agent attempt counter prediction attempts, meteorology doesn't involve a constantly changing technological landscape, meteorology has access to vast amounts data whereas data that's key to military decisions is generally scarce - you know the phrase "fog of war"?
I mean, LLMs in fact, don't provide probabilities for their predictions and indeed the advance of deep learning has hinge "just predict, ignore all considerations of 'good statistics' (knowing probabilities, estimating bias)".
Re: Large language models in national security applications
#20This is how you get CIAGPT
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