[HN Gopher] The leading AI models are now good historians
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       The leading AI models are now good historians
        
       Author : benbreen
       Score  : 54 points
       Date   : 2025-01-22 23:29 UTC (3 days ago)
        
 (HTM) web link (resobscura.substack.com)
 (TXT) w3m dump (resobscura.substack.com)
        
       | BeefWellington wrote:
       | Good read on what someone in a specific field considers to have
       | been achieved (rightly or wrongly). It does lead me to wonder how
       | many of these old manuscripts and their translations are in the
       | training set. That may limit its abilities against any random
       | sample that isn't included.
       | 
       | Then again, maybe not; OCR is one of the most worked on problems,
       | so the quality of parsing characters into text maybe shouldn't be
       | as surprising.
       | 
       | Off topic: it's wild to me that in 2025 sites like substack don't
       | apply `prefers-color-scheme` logic to all their blogs.
        
       | satisfice wrote:
       | The intractable problem, here, is that "LLMs are good historians"
       | is a nearly useless heuristic.
       | 
       | I'm not a historian. I don't speak old spanish. I am not a domain
       | expert at all. I can't do what the author of this post can do:
       | expertly review the work of an LLM in his field.
       | 
       | My expertise is in software testing, and I can report that LLMs
       | sometimes have reasonable testing ideas-- but that doesn't mean
       | they are safe and effective when used for that purpose by an
       | amateur.
       | 
       | Despite what the author writes, I cannot use an LLM to get good
       | information about history.
        
         | amelius wrote:
         | You __can__ get good information from an LLM, however you just
         | have to backtrack every once in a while because the information
         | turned out to be false.
        
           | userbinator wrote:
           | _however you just have to backtrack every once in a while
           | because the information turned out to be false._
           | 
           | The problem is, how do you know? I've seen developers go
           | completely off-course just from bad search engine results and
           | one did admit he felt something wasn't right but kept going
           | because he didn't know better; now imagine he's being told by
           | a very confident but incorrect LLM, and you can see how
           | hazardous that'll be.
           | 
           | "You don't know what you don't know."
        
             | sebmellen wrote:
             | Unless you have a very good understanding of the system
             | you're working on or the tools you're using, it's very
             | possible to get knee deep in crap without knowing it.
             | That's one of the biggest risks of using LLMs as
             | assistants.
        
             | simonw wrote:
             | You need to develop skills like critical thinking,
             | metacognition, analytical reasoning - being able to get to
             | a robust mental model from a bunch of different inputs,
             | some of which may even contradict each other.
        
             | amelius wrote:
             | In the case of software, you can ask the LLM to write a
             | test.
             | 
             | In other domains, I'm sure there are ways to verify
             | information.
        
           | mvdtnz wrote:
           | And therein lies the problem - if you're not already an
           | expert there's no way to tell when is the right moment to
           | backtrack.
        
           | nithril wrote:
           | The exact definition of a useful heuristic, "good enough"
        
         | simonw wrote:
         | This is similar to the problem with some of the things people
         | have been doing with o1 and o3. I've seen people share "PhD
         | level" results from them... but if I don't have a PhD myself in
         | that subject it's almost impossible for me to evaluate their
         | output and spot if it makes sense or not.
         | 
         | I get a ton of value out of LLMs as a programmer partly because
         | I have 20+ years of programming experience, so it's trivial for
         | me to spot when they are doing "good" work as opposed to making
         | dumb mistakes.
         | 
         | I can't credibly evaluate their higher level output in other
         | disciplines at all.
        
       | britch wrote:
       | Interesting perspective. I appreciate that it tests the models at
       | different "layers" of understanding.
       | 
       | I have always felt that LLMs would fall apart beyond the
       | summarization. Maybe they would be able to regurgitate someone
       | else's analysis. The author seems to think there's some level of
       | intelligent creativity at play
       | 
       | I'm hopeful that the author is right. That truly creative
       | thinking may be beyond the abilities of LLMs and be decades away.
       | 
       | I think the author doesn't consider the implications of broad use
       | of LLM societally. Will people be willing to fund human historian
       | grad students when they can get a LLM for a fraction of the
       | price? Will prospective historians have gained the training
       | necessary if they've used an LLM through all of school?
       | 
       | I believe the education system could figure it out over time. I'm
       | more worried that LLMs like this will be used as further
       | justification to defund or halt humanities research. Who needs a
       | history department when I can get 80% for the cost of a few
       | chatGPT queries?
        
       | simonw wrote:
       | I'd love to read way more stuff like this. There are plenty of
       | people writing about LLMs from a computer science point of view,
       | but I'm much more interested in hearing from people in fields
       | like this one (academic history) who are vigorously exploring
       | applications of these tools.
        
       | quantadev wrote:
       | American-made AIs are probably mostly good historians (other than
       | having Silicon Valley Left-wing progressive wokeness built in),
       | but DeepSeek, or anything from China is going to _not_ be a good
       | historian, but more of a propaganda tool, to further China 's
       | interests.
        
       | cyrillite wrote:
       | Now the question is how can I, someone without a PhD in history
       | but currently a PhD candidate in another discipline, use these
       | tools to reliably interrogate topics of interest and produce at
       | least a graduate level understanding of them?
       | 
       | I know this is possible, but the further away I get from my core
       | domains, the harder it is for me to use these tools in a way that
       | doesn't feel like too much blind faith (even if it works!)
        
         | kozikow wrote:
         | > the harder it is for me to use these tools in a way that
         | doesn't feel like too much blind faith (even if it works!)
         | 
         | I tend to ask multiple models and if they all give me roughly
         | the same answer, then it's probably right.
        
           | aquafox wrote:
           | > if they all give me roughly the same answer, then it's
           | probably right.
           | 
           | ... or they had a lot of overlapping training data in that
           | area.
        
           | energy123 wrote:
           | Also keeping context short. Virtually all my cases of bad
           | hallucinations with o1 have been when I've provided too much
           | context or the conversation has been going on for too long.
           | Starting a new chat fixes it.
           | 
           | You can see this effect in the ARC-AGI evals, too much
           | context impacts even o3(high).
        
         | aquafox wrote:
         | You ask them for references and check yourself. They are good
         | exploratory and hypothesis generating tools, but not more.
         | Getting a sensible sounding answer should not be an excuse for
         | you to confirm. Often, the devil is in the details.
        
         | simonw wrote:
         | I think the trick here is to treat everything these models tell
         | you as part of a larger information diet.
         | 
         | Like if you have a friend who's very well-read and talkative
         | but is also extremely confident and loves the sound of their
         | own voice. You quickly learn to treat them as a source of
         | probably-correct information, but only part of they way you
         | learn any given topic.
         | 
         | I do this with LLMs all the time: I'm constantly asking them
         | clarifying questions about things, but I always assume that
         | they might be making mistakes or feeding me convincing sounding
         | half-truths or even full hallucinations.
         | 
         | Being good at mixing together information from a variety of
         | sources - of different levels of accuracy - is key to learning
         | anything well.
        
       | option wrote:
       | Yeah, especially the ones from China /s
        
       | abathur wrote:
       | Someone who knows a lot of history is a history buff.
       | 
       | A historian works with (and may even seek out in musty rooms)
       | primary and secondary sources to produce novel research and
       | interpretation.
       | 
       | An AI is at best limited to ~reading sources that human
       | historians/archivists/librarians have already identified and
       | digitized.
       | 
       | Certainly value to be had here wrt to finding needles in and
       | making sense of already-digitized historical records, but that's
       | more like a research assistant.
        
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