AI makes the humanities more important, but also weirder
resobscura.substack.com
resobscura.substack.com
If college students are using AI to breeze through their work rather than doing the reading themselves, developing grit – I don't see how we can blame them rather than ourselves for the educational and career system we've created. This problem didn't happen overnight, and it's not just AI.
I'm not so sure about that: I have a feeling that at least the current trend in quite some jobs is that they are looking for two kinds of people:
1. beginners who know the basics and are cheap
2. deep experts; these are paid well
What is in-between gets more and more hollowed out.
Thus the people who follow your advice will mostly stay in the "cheap" pool - I wouldn't consider this to be desirable.
Cheap... but employed. Expertise is only valuable if its valued. That means you not only need to be an expert in the thing, but also the market for the thing, and that's a lot to ask.
Look, I would not want a doctor to perform my surgery who did not do a residency. I don't care if they carved up 1,000 cadavers in their free time. I want somebody where the board of their specialty has said "yup, this guys good". I'm not gonna spend the time to try to trust the doctor, because that's really really hard. I'm not a doctor, I don't know shit. I have to rely on institutions of trust to do that work for me.
And that's really what universities are at their core - institutions of trust. When you get a degree, there's trust you understand the material to an appropriate degree. When you pass a residency, there's trust you understand the material to an appropriate degree. If we lose that trust, such as by letting students cheat by AI, that is a big problem.
Could I hire someone who says they're an expert, with no degree, and just give them a leetcode problem? Sure. But if I hire someone with a degree, I have a much greater level of certainty they can actually code. Same goes for work experience.
There are so many better options than leetcode or degree.
I don't think it's likely that AI will obliterate the job category of "lawyer", but that's what its boosters are claiming, and people need to make a car to house sized investment at age 18 depending on how true that is.
Most people do not have the ability to adjust like that, for one reason or another
And even if you do, it still means your life is likely to hit an extremely rough patch while your adjusting catches up to where you were before
It won't be long before an impoverished criminal defendant will be able to chose between an AI that can spend practically unlimited time on his case and have perfect recall of any precident that might be relevant, or an overworked public defender who has 2 hours a week to spare in his schedule.
If you think SWEs that build the same CRUD apps every day are vulnerable but SWEs that do "real work" aren't, apply that logic to lawyers.
Except lawyers don't have an automated compiler to check for fabricated precedents as case law databases are monopolized by one company.
Software's golden goose is not letting people own things.
It's like a boat captain telling all his passengers to rush to one side of the boat. Any single side will tip the boat over.
Its all idiotic romanticisation. Thats why all the out-of-their-ass anecdotes involve someone who's more of an entrepreneur than a tradesmen as well.
Theres some bizzare analog of the noble savage myth, but applied to blue collar work.
Many years ago we had to deploy an HFT trading strategy on a specific hardware platform because that was the one that was (in this field) closest in network topology to the exchange. I just read the released docs for the platform, and watched a couple of videos where they hinted at certain architectural decisions and then you could work something out from there. Latency was reliable and our strats made money.
But this was public information and we were actually late to it. It had been released for 3 years at the time. And many people I talked to had told me that what they had was as good as it gets. But they were each just repeating what the other guy said.
Many of the things you see on Hacker News are just that: it's deterministic parrotry.
I am very sure that those jobs that have been existing for a long time will continue existing for a long time (and no: even if some disruption occurs, these jobs won't suddenly disappear, but will rather phased out slowly; you thus have sufficient time to make a decent plan for you).
In other words: in my opinion one can predict rather well many jobs that will be available in 5 to 10 years.
The "inconvenient" truth rather is that many high-paying jobs in the new economy sector don't satisfy this criterion of "existing for a long time". So by this criterion you might miss out some hard to predict high-earning opportunities. Thus, if you are the kind of person who tends to easily become envious if your friends suddenly experience a windfall, such a job perhaps won't make you happy.
Mostly which are that our system only rewards one thing in education: the grade. Not understanding, knowledge, intelligence, but instead a single number that is more easily gamified than anything. And this single number (your GPA) is the single most important thing for every level from middle school to college where it will unironically determine your entire (academic/academic-adjacent) future.
Capitalism is what has destroyed higher education in this country. The concept of going to school to get a job isn’t a failure of education but of economics.
AI is just another capitalist tool made to not only extract wealth out of you but something that they want you to rely on more and more so they can charge you even more down the road.
(there have been a few Communist revolutions against the concept of "university", for various political reasons, but China rebuilt theirs after the purges and Cambodia is a sad historical footnote)
- Yakov Smirnoff, probably
Also people did that to avoid Dedovshchina
Decoupling working from living: means only intrinsically valuable things get worked on. No more working a 9-5 at a scam call center or figuring out how to make people click on ads. There is ONLY BENEFIT (to everyone) from giving labor such leverage.
Not every job needs to or should even exist: everyone having a job isn't utopia. Utopia is being free to choose what you work on. This directs market value for labor to go up. Work that needs to get done will be aligned with financial incentives (farmers, janitors, repair industries would soar to new heights).
UBI is a necessary and great idea: A bottom floor to capitalism means we all can stand up and lift this sinking ship.
We've put into place a context for intellectual achievement at scale. Why shouldn't status be apportioned to someone who is recognized by a panel of peers and teachers to have useful insight into their field?
Because many "fields" in colleges are not useful.
Because modern life is radically more complicated than humans can naturally deal with.
Your average peasant for millenia didn't need to understand Information security to avoid getting phished, didn't need to understand compounding interest for things like loans and saving for retirement (they'd just have kids and pray enough of them survive), didn't need to have some kind of mental model for the hordes of algorithms deployed against us for the express purpose of taking all of our available attention (a resource that people before a couple decades ago had so much excess of that boredom was a serious concern) for the express purpose of selling it to people who want to extract any dollar you may have access to, did not need to understand spreadsheets(!), etc etc etc etc
Like, being productive in modern society is complicated. That's what education is for.
The problem with the modern educational system is that it isnt very efficient at this task. Instead, most of the value relies on the screening that took place before the students even entered the institution, not the knowledge obtained while there.
Today we simply use college as a proxy for intelligence, so people just like to go to the highest rated college they can to be viewed as intelligent. What happens in the four years at the college is secondary.
Hmmm… I would say college is a proxy for social currency, of which intelligence is one type. In most cases, intelligence is the least valuable (imho).
That can't be the only goal. We also need to transmit culture, values, and teach them to become citizens.
Doesnt that single point of failure indicate a weakness?
But a country without a culture and without shared values is a sled being pulled by dogs in different directions and not a real team (as many people would argue has been the case for quite some time).
You need common values to work together to achieve goals. That's what a country is, people working together. When you don't, you just become tenants with passports.
nor do our current institutions do a good job of what you describe.
there are like 4 factors besides ZIRP i've witnessed as a hiring manager
- Layoff or dont hire locals in favor of H1b/H4
- Layoff or dont hire locals in favor of Nearshore and Offshore
- Section 174 Tax code on software: https://blog.pragmaticengineer.com/section-174/
- More productivity via LLMs, Code Assist
... our system only rewards one thing in employment: the metric. Not understanding, knowledge, intelligence, but instead a single number that is more easily gamified than anything. And this single number (your metric value) is the single most important thing for every level from junior to principal where it will unironically determine your entire future.
I dont know man, you do it every time.
This rule is made explicit with copyright: derivative work is, by default, illegal. The only way that derivative work is allowed to be made is after making a contract with the rightsholder.
This system can only be enforced with incompatibility. You can't actually stop someone from making derivative work unless your help is actually required. The most familiar instance of this requirement is software: it's simply not pragmatic for someone to extend your code, when they only have access to a compiled binary. Software work can only be extended from a shared context: what you write must be compatible with what is written. That's generally unfeasible when what is written is a compile-time optimized binary executable.
Incompatibility is not a perfect barrier. It's possible to decompile software. It's possible to edit text, images, video, audio, etc. Copyright depends on incompatibility, and LLMs are simply the newest, most compelling way to call that bluff.
This one is really bad. I have waves of local grads begging for unpaid internships or work now. They all were AP students, good GPAs, good schools, "learned to code", took on 200k of college debt -- only to find the promised job is just not frigging there at the end of the line. Meanwhile, they are told there is a "massive shortage of coders" and see overseas workers hired into those same jobs. How do younger people trust the system anymore? Further, in light of this, why would any steel-worker (metaphorically speaking) want to retrain and learn to code if even the geeks learning to code face dismal outcomes?
> I am a grad student in the philosophy department at SFSU and teach critical thinking. This semester I pivoted my entire class toward a course design that feels more like running an obstacle course with AI than engaging with Plato. And my students are into it.
It would be interesting to take a class of students and set them an assignment to come up with assignments for their fellow students that could not be completed using ChatGPT.
About ten years ago I went to a BarCamp conference where one of the events was a team quiz where the questions were designed to be difficult to solve using Google - questions like "What island is this?" where all you got was the outline of the island. It was really fun. Designing "ChatGPT-proof assignments" feels to me like a similar level of intellectual challenge.
As a blind person I can't help but notice that this "innovative" question design is inherently inaccessible to people like me. Yes, I know I'm not the norm. However, I can't help but notice that this avoidance of text based assignments is making accessible teaching even more impossible. Say welcome to a new generation of Digital Divide.
Complaining about this is like me complaining about people drinking milk since I’m lactose intolerant.
While there are possibly noble goals behind your suggestion, in practise this puts anyone outside the mainstream in the category of “other,” people to be managed separately. I’ll leave to your imagination how much work is often put into supporting these “other” assignments and how up-to-date they’re kept va the mainstream.
> Complaining about this is like me complaining about people drinking milk since I’m lactose intolerant.
If this is genuinely your approach, you are being part of the problem; if taking a step back to reassess feels like too much work, I’d encourage you to explore why it feels that way, what emotions is this bringing up internally?
Are you just concerned about the administration side of things?
I think the GP here has a pretty reasonable outlook here
"Some people can't do some things the same way as others and that's ok, people are different"
Is the vibe I got from that post
On the other hand, how far can society tip-tap around such alternative takes? Could he go study in a field where hand writing is expected and society would still be forced to adapt?
So what ? This is literally the case. The commenter has to be managed separately
An example I have personally is when designing board games I now have internalised to never just use colour to communicate anything. Never solid colour which can be difficult to determine by the colour-blind, but different colours have different stripes or patterns embedded in them. So if you can't see the colour, you can recognise the stripe spacing, if you can't see the stripe spacing due to low visual-acuity, you can see the colour... and ideally different textures for the blind. (not pratical as it would wear off in the shuffling, but the idea is there).
I think the answer would be to make assignments multi-faceted that can be approached differently. Like instead of having students write a report on book they read, which priveledges the those with sight, non-dyselxics, and those that can type let them perhaps record a podcast, film a YouTube video, draw a webcomic etc that lets students show what they know. And then reflect on why does it have to be a book that's read? It could be a film, a mini-series, a radio-play, a graphic novel, a play. That allows people to approach it using their abilities instead of being hampered by disabilities such as blindness, deafness, ADHD, dyslexia, being non-verbal, etc.
It means you've distilled the assignment to it's core: can you summarise the plot, identify key moments, recognise themes and metaphors, and place the work within the historical context in which it was produced.
There you have an assignment that is much more accessible.
The tricky part is that marking them objectively is much more difficult because the criteria of evaluation are not necessarily monolithic but need to take into account the student and the mediums chosen.
...but it's still a single accessible assignment.
The problem with such assignment is it's very hard to balance the alternatives to be equal. Reading a book takes quite a bit longer than watching a film or even mini-series. IMO it's perfectly fine for someone blind to watch a film and then make a report on it. But how many healthy people would just go for a film since it's quicker? And reading a book is quite a bit different experience than a film due to much more space for imagination and interpretation in a book.
P.S. calling people with no disabilities „privileged“ is just... wrong. It's not a privilege to have a set of eyes/hands/etc.
How am I part of the problem? Do you mean I should make a fuss if I get limited options? Or have emotions towards what... My genetical makeup? All in all, I've zero emotions about my lactose intolerance. Being mindful about what I eat is just natural for me. Just like for other people with food allergies/intolerances.
> in practise this puts anyone outside the mainstream in the category of “other,” people to be managed separately
Is your goal to get everyone down to the same level by removing all learning material that may be inaccessible to somebody?
Should people just stop consuming anything with lactose to make it more universal for people like me? But then a friend of mine will ask to stop eating fish. Someone else will take away chocolate. At the end of the day all of us will be much worse off.
I think you're right to complain about the design of the question. It used Google's disadvantage in that it couldn't process visual information to add difficulty to the task.
However I'm pretty sure there's many of these challenges in an average stem subject. An example would be information dense diagrams which describe some chemical process.
I'm genuinely curious to understand how someone manages to understand these without sight. On my side, I can barely visualize so it was always extremely hard to decipher them and even worse remember them.
I wouldn't be surprised if a novel solution to the problem emerged from students with diverse abilities. I don't think that brute forcing the problem by comparing the image of every island on the planet vs the outline visually is the best path forward. Its probably something like, create a ratio of the size of each of the bays and then probe for values that fit those quantities on wikipedia.
Fortunately, my university has a good accessibility center that takes care of accommodation issues (large print versions of tests, etc.). I just send them my tests and they take care of it. It’s a great service, and absolutely crucial because I simply don’t have the time to customize assessments. I assume they would get in touch if they were unable to retrofit accessibility onto an assessment, but that hasn’t happened in my fifteen years of employment.
This is indeed true. But a challenge is that few professors are being given the time and training to help do this. When you are on a 4/4 and just keeping your head above water you don't tend to have enough time to adopt experimental pedagogies and completely replan your courses. And professors are largely being tasked with doing this independently rather than having universities offer training or support with adjusting methods to be more AI resistant. And unfortunately the fast speed of development of these tools is making good ideas obsolete quickly. I know some people who switch to having students make podcasts rather than writing papers as a final assignment and then we started seeing "create your own podcast" tools appear and made it roughly as easy to cheat on this assignment as a traditional paper.
> ... they keep some sort of overall concept of learning. This is a pretty god-of-the-gaps-ish hypothesis, and counterbalanced by ...
The author is really missing the obvious here. Learning difficult subjects fundamentally changes how you think about and approach things. People aren't born able to engage in critical thinking or being able to reason algebraically or with an ability to navigate formal logic. That doesn't mean school is the only way to impart such skills, but it is certainly one of the ways.
Of course if the metric you use is "ability to answer trivia" then you are going to fail to capture that aspect.
Citation needed on this. But even if I accept the premise, what percentage of school is leaning difficult subjects? For me it was <5% and the other 95+% was stuff that could be beaten easily with rote memorization. The only classes in that 5% were upper level courses that only students who want to be there take anyway.
Unfortunately any of the obvious metrics you might use to quantify this would seem to be hopelessly biased. The more advanced the degree someone holds the farther above average that individual tends to be in various ways. I doubt it would be possible to control for such large cross correlations.
Perhaps asking people who learn multiple languages could provide subjective evidence since that doesn't have nearly as much of a correlation with other abilities.
Why is this problem being fretted over? In-class written and oral tests should be fine to assess students. If AI helps them learn or even cram the material, great!
If they are just working from AI notes and improvising the conversation, arguably they are simply doing the work.
What I don't know is whether an instructor would be allowed to earnestly grade an hour-long podcast subjectively.
A lot of kids also suck at cheating so the small barrier of "ask ai to generate a script and then read it" appears to stop a bunch of cheaters.
There are limitations to timed evaluations such that oral exams or blue books are not panaceas.
That's teaching four distinct courses?
My professor often taught classes with a couple sections, I’d help out sometimes—even that was a ton of work, pretty hard to do the main job (research) during those semesters. I wonder if (given the demographics of the board) folks are suggesting things from a similar place of informed ignorance to me—coming from research oriented STEM universities. In that case it could be reasonable to say “well, the situation with our classes has gotten so dire with AI, it might make sense to sacrifice a semester of research to sort that all out.” Of course if you are already prepping for four classes, there is not much slack to sacrifice…
In that case a lot of us would be specifically more wrong than a random person plucked off the street, somebody who thinks the main job of every professor is teaching.
Is a military base the only place “no devices” can be enforced or something? How deep is this addiction? I’m scared to ask what the academic version of fizz-buzz would be at the end of a 4 year degree, “hey write one paragraph describing a simple paradox, an example of irony, or an example of a metaphor”.
I mean with the force of law, yea. Businesses get away with a little bit more in places because they pay you to show up.
But if you think anyone is going to university/college to have all their devices taken away all the time and pay for the privilege then you might be confused.
If taking away phones is what’s required to make that credential meaningful again, then the universities must do it.
I think of it like a personal trainer. Do you pay them to make you sweaty and sore? Not really, but sweat and soreness are consequences of doing what it takes to build muscle/endurance/etc.
No they don't, or at least a significant percentage of them don't. They pay the university because it is a paywall between them and even getting an interview in the first place.
So its in universities best interest to actually test for competence.
... In theory.
Even for exams I had my cellphone and backpack on me. You just weren't allowed into them. The only exception to that in my experience was exams proctored in a dedicated testing center where there are lockers, multiple human observers, and lots of cameras.
> The more I give my teacher-power to students and encourage them to take more responsibility for their own learning, the more they show me how to redesign my ways of teaching
"Everyone don't do X" runs into problems when there are clear incentives to do X. Like, say, grades which eventually will be used to determine who gets to graduate, who gets into which schools, who ultimately gets easier access to higher paying jobs. And simple convenience is an incentive in itself - if doing X saves time, it will be the default.
This same dynamic is why we still have a climate crisis, even though everyone has known about the problem for thirty years.
"Everyone just do Y" is what we call a collective action problem. When there are clear incentives to defect, it is also a free rider problem.
This is not to say that Plato didn't think critically. Of course he did, as do all (or most) philosophers. I'm just talking about university courses and textbooks.
Designing a "mostly ChatGPT-proof class" is in my opinion actually rather simple: just be inspired by the German university system:
Each week you have to complete exercise sheets which are often hard. But being capable of solving a certain quota of the exercises is just the beginning: this only qualifies you for being allowed to take the actual (oral or written) exam.
In this sense (as many professors will tell you), the basically sole purpose of the quota for solving (often hard) exercise sheets is actually preventing students from the "self-inflicted harm" of doing an exam that they are not yet prepared for.
And yes: while it is forbidden to "cheat" (e.g. ChatGPT) on your exercise sheets, this policy is typically not strongly enforced (you will nearly always just get a unequivocal, strongly worded oral reprimand by the tutor). Instead, if you did this, you will for sure not be prepared for the upcoming exam, and flunk it (and most students are very aware of this).
Oh yeah, I didn't mention yet that if you flunked the same exam typically 3 times (depending on the university), you have "finally failed" (endgültig nicht bestanden), and are not allowed anymore to study the same degree course at every German university.
When Europeans wonder why they are falling behind the United States both economically and technologically (Especially in the AI race), here's a perfect example of why. A culture that turns you into a some kind of a permanent failure because you failed to check a box some arbitrary number of times isn't one that produces innovation.
Concerning "next European country", on the other hand, keep in mind that in this country often a different language is spoken; in particular for your daily life, you cannot assume that everybody understands English or even your native language.
What a weird way to try and connect inter continental economics and private company valuation as a sole metric for success or achievement with test taking at a university level in Germany...
However you need to realize that the country you're holding up as a counterexample brands people as felons over some fairly absurd things and more generally has a remarkably dysfunctional justice system that exhibits precisely the same cultural failures that you're objecting to here.
Now the real question is the costs. In that, can you somehow make this system work at scale with the same profit as before? I know that the German system is a lot different than in the US, including things like tracking in 9th grade and below. But the real question is if the Universities make as much, if not more, cash. Because if the answer is 'no', then it's unlikely to be adopted.
> Oh yeah, I didn't mention yet that if you flunked the same exam typically 3 times (depending on the university), you have "finally failed" (endgültig nicht bestanden), and are not allowed anymore to study the same degree course at every German university.
That is an insanely awesome and clever idea. I love it. It puts real stakes there, if only perceived ones. I imagine that in the US if you flunk out of a major's classes twice or more, the number of students that continue on in that major is probably pretty low already though.
Doing that more than 3 times would be absurd, and anyway the sort of student who has 3 F's on his transcript within his chosen major is unlikely to be maintaining a GPA above the minimum for his program (or any program for that matter). Rather than transferring to another degree such a student is likely to be forced out of the university entirely in short order.
This often also holds in Germany. And indeed if you thus fail an exam, your degree is delayed and you might have logistical issues.
The moral of this: learn hard so that you don't fail exams. :-)
Granted, this is without consider the financial side of things.
For the last several years I've been allowing students (college sophomores) to do take home exams where they essentially have to build a networked system in C++. I tell them not to use AI but I have to assume they are.
Even still, the solutions are not all that great, despite unlimited time and resources, they still submit work that falls into a roughly B average. Which, if they didn't have AI, maybe that would be a C average, so perhaps the standards just need to go up. Still, it's not like they're all getting 100%.
AI is still really only as good as the person driving it, and it still, despite all the hype, hallucinates like crazy, such that if they don't pay close attention and constantly course correct, they can't expect the project to actually work.
Military officers study much history, but in a different way. They look for mistakes. Why did someone lose a battle or a war? Why did they even get into that particular battle? Why was the situation prior to WWI so strategically unstable that the killing of a minor player touched off a world war? The traditional teaching of history tends to focus on the winners, especially if they write well. Reading what the losers wrote, or what was written about them, can be more productive than reading the winners.
If you want to understand Cicero's era, for example, read [1]. This is a study of Cicero by an experienced and cynical newspaper political reporter. The author writes that too many historians take Cicero's speeches at face value. The author knows better, having heard many politicians of his own day.
This sort of approach tends to take one out of the area where LLMs are most useful, because, as yet, they're not that good at detecting sycophancy.
This is not what academic historians generally do. The study of history tells us about the story of humanity and exists for wider reasons than direct application to decision making today. This is even true for military history, which is among the slowest subfields at adopting new methods and practices.
I also learned to appreciate history on a fundamentally different level than I did, when I loved history as a subject in school. But that would lead too far out from this thread here.
I can relate to the original piece, because - while I use AI daily for work and in private life - I also see the dangers. Yes, it is a new medium - and I heard roughly the same critique about the internet, when I was at university - but I think it is quite a fundamentally different paradigm shift that we are living through.
I feel (used intentionaly here) it is more like the invention of the printing press (from an societal impact standpoint) than the dissemination of the internet into the wider society. But that is just my current working hypothesis.
If we don't learn from history, why do we do history? Is it a form of pure entertainment, i.e. of arts? If so, does that give more credence to White's argument?
I have had a PhD colleague who genuinely believed that history ought to be (in the philosophical normative sense) contributing to national propaganda, thus of national interest. By extension, this is why history departments should be funded by tax dollars.
They're academics, their job is to make true statements and maintain a culture that cares a lot about whether their colleagues can prove them false. Beyond that, it is hard to figure out what purpose they might be fulfilling.
Historians uncover and communicate the story of humanity in as rich and diverse of a way as possible. This is, in my mind, somewhat comparable to the process of doing pure math research or fundamental physics research. While there may be practical outcomes for today (either unexpected or intended as a goal of a particular research direction), we also understand that doing math for its own purposes is valuable.
The process of doing archival research, putting sources in dialog with other research, and even simply reading secondary source writing achieves some positive outcomes. It widens and deepens empathy for the rich diversity of human behavior. It builds skills for critical analysis of media and communication. It can provide narrative and argument for people advocating for change today (both good and bad). But these do not need to be the reasons why we embark on history research. They are side outcomes of undirected analysis.
I'll also add that concern about "history departments funded by tax dollars" is just factually unfounded. My wife is a history and the size of grants is hilarious coming from my background in CS. Like, a grant for $2,000-$5,000 would be considered chunky. And grants are often coming from weird places like random corporations or donor funding rather than from the government. The NEH was already basically dead before Trump 2.0 and now is dead and buried. People upset about academic history can rest easy knowing that there aren't historians living large on your tax dollars.
Historians, imho, serve a similar purpose for society at large. They digest the information of the past to make sense of it for today, and sometimes they build dams that redirect the informational flow of future history.
What's tricky is that indeed such stories need not be factual to be powerful, just as long as they resonate well-enough with the current "common-sense" and have some kind authority behind it giving it credence.
Historians do have an important responsibility here in making sure that people are aware of the real story so that they are not easily manipulated, just like journalists have a similar responsibility in a democracy, fourth estate and all.
This is true on an individual as well as a collective level, and goes well beyond academia. Consider genealogy & family history, local and regional culture and traditions, remembrance,... There is always a personal connection, and that tends to become extremely tangible in individual stories. Whether that's finding a lost relative, honoring one's culture, or just being able to empathize with the lives of people who are centuries gone and discovering that they weren't all that different from us today.
Historians do carry a big responsibility. That's why accountability is at the heart of anyone who does historical research on a professional level; or are motivated to spread their interpretation of the historical record well beyond a few listeners. That's why historians are instilled with a reflex to keep a pragmatic attitude and ask critical questions.
Your comment made me dig up "Historical text as literary artifact".
I have several thoughts on that, but one very important analogy stood out to me and is succinct enough to comment here. In statistics, one talks about the population, collecting data (sampling from the popluation), and building a model from the collected data. You may have guessed that the collected data alone does not typically make much sense, but for the patterns encapsulated by the model, which then has explanatory power; yet among the three classes I mentioned, it is the most fictitious and constructed for a particular goal, the most inauthentic.
History deals with very small, very heterogeneous datasets. Finding patterns in them (if they even exist) is very difficult, and it's why historical models and grand unified theories are so often bunk.
> deals with very small, very heterogeneous datasets.
The population itself is a very heterogeneous "dataset", that becomes (perhaps) apprehensible after you interrogate it with respect to the statistical question you have in mind. Let's not forget that the neatness of the data is constructed from the narrowness of the question asked of it, and even still the data is expected (in the colloquial sense) to take on a minimally-informative, max-entropy distribution, except in respect to the statistic of interest. The critical questions levied against historiography also apply here: perhaps the question you are collecting data for is not related to the population the way you think it is.
> why historical models and grand unified theories are so often bunk.
A lot of history practiced today are self-aware of just how much narrative has to be invented to "make sense" of historical events, and so historians value diverse perspectives. One understands that the same events may not hold the same meaning across communities, and so seeks to record and compare how they are perceived across communities or individuals; that perception in that community's narrative is at least subjectively authentic for that community or individual.
To the extent that the historical goal is to predict political/cultural/economic future, perhaps political/cultural theorists/economists are better positioned.
Amongst other things...
Because this isnt the goal of history. You cant use history to predict the future.
> If you want to understand Cicero's era, for example, read [1]. This is a study of Cicero by an experienced and cynical newspaper political reporter. The author writes that too many historians take Cicero's speeches at face value. The author knows better, having heard many politicians of his own day.
No they dont. This is yet another example of an outsider looking at another field, thinking he knows better and making a fool of himself. Also, why would you ignore 80 years of scholarship about Cicero and read a book from 1942???
I mean this statement is somewhat false.
If I show you a picture of a cup from 100 ms ago and it's in midair probability favors that the cup will be on it's way to the ground to its demise. Statistically this will be true.
History is filled with analogous times where by watching the present you can make predictions far better than flipping a coin.
How are those things dissociated?
I always saw history as a waht to explain "why things are the way they are". Whatever we are now, this amalgamation of good or bad things, is a consequence of what came before.
Is "studying the classics" from a historical standpoint even done for "appreciation"? I always presumed that one should do so critically, and that's more or less what I found from actual historians.
There’s interesting writing to be done in this mode but it is definitely not the primary mode.
Does it matter in order to explain how things came to be?
Understanding their motivations, the incentives that led them to do what they did, the sociopolitical context they were inserted into, the limitations of a historical perspective (quite often the accounts of past historical figures were written by people invested in portraying it in one way or another).
All those things would help, when looking at history critically, to make some sense of the present and where things might be going in the future.
In a sense, things that happened were inevitable because they came to pass. We are not talking about a possibility, we are talking about a certainty long after the fact. Understanding that it might have been avoided in some ways can be helpful, but also is an exercise in wishful thinking and guesswork.
Yes. Writing on historiography has been detailed about the ways that this sort of framing can be limiting.
A lazy humanities teacher can make every question a writing question in disguise. If a better spell checker will make a humanities assessment trivial, then maybe they need to teach humanities instead of testing essay writing.
I'm saying this in a kinda inflammatory way, but does the quality of ones ideas really correlate well with a well written essay?
Economic incentives are what this thread is about. If those are removed, some instances of cheating will subside.
Reputational incentives are similar and harder to address, but they are also less strong because the cheating has a much higher chance to backfire. If you are found out, your economic benefits might continue, but your reputation is immediately damaged.
Singleplayer games are an entirely different situation. There's clearly no economic incentive here, and reputational incentive only applies if you are looking to share your singleplayer result with other people, in which case I could argue it's no longer singleplayer in the game theoretic sense. If it's not that, the only remaining motivation to cheat at something like Sudoku or a singleplayer videogame is to learn or at least satisfy an itch or curiosity, which I think is a perfectly legitimate motivation.
You cannot remove economic incentives for the most part, 'economy' is attached to all facets of peoples lives, especially where rival goods exist.
The thinking _is_ the writing. To be able to write is to be able to think, and if you are surrendering the writing to a machine that’s not ultimately what you’re surrendering—you’re giving up independent thought itself.
But there is minimal institutional support for this. Everybody is going it on their own. And the ai tools are changing rapidly. Telling a ntt faculty member teaching a 4/4 that they just need to stop being lazy and redo their entire evaluation method is not really workable.
Iteration is also slow. You do a new syllabus to try to discourage cheating. You run the course for a semester. You see the results with now just a few weeks to turn around for your spring semester courses. At best you get one iteration cycle per six months. More likely it is one per year since it is basically impossible to meaningfully digest the outcome of what you tried and to meaningfully try something different mere weeks later.
I'm not sure they are analogous to LLMs, but a compelling argument at the time was that the students were going to use them in the field anyway. (That certainly seems to be the future for software engineering students.)
Instead of being about the consumption and production of texts -- texts which only the TA and maybe the prof will read ... ever -- the class should be more about the dialectical process of discussing the ideas in the texts and lectures the students consume.
An LLM will be able to easily rattle off an undergrad level paper. But it can't sit in the classroom and have an intelligent conversation with peers.
Of course none of this will happen because it doesn't scale economically nearly as well. It is far more labour intensive.
People get (rightly!) excited about decoding burnt scrolls in Herculaneum. But most don’t realize that less than 10% of Neo-Latin texts from the renaissance to the early modern period have been translated to English.
One example: Marsilio Ficino was a brilliant philosopher who was hired by Cosimo Medici to translate Greek texts (Plato, Plotinus, the Hermetica, etc) into Latin. This had a massive impact on the renaissance and European enlightenment. But many of Ficino’s own texts have not been translated to English!
LLMs will, of course, have a massive impact on this… but so can students! Any student can make a meaningful contribution if they care to. There is so much to be discovered and unpacked. Unfortunately, so much of the humanities in high school is treated as an exercise rather than real discovery. I judge my students now based on how much I learn from them. Why not?
We have no idea what happened over 500 years ago, but the idea of a brilliant scholar translating the Greek texts on behalf of the Medicis, shouldn't simply be accepted as stated. If you are running the world (like the Medicis did) history would be a lever of control. It seems inevitable that the stories should be directed (carefully) towards whatever ends.
History is actually a present day activity - it provides the backdrop to the present. Altering that backdrop has present value.
I can't see how ai will help us the endeavour of trying to get a better handle on what happened in the past. I do see how it would provide modern-day Medicis a way to change the backdrop more quickly.
Well, AI democratizes the power of translation (and interrogating texts). Before only a few specialists could go directly to the source. Now anyone can try to make sense of it.
If the source is corrupt - as I suggest and as is possible because the Medicis provided/sanctioned their version - all you have is interpretation based on flawed data. Endless production of information (by ai) based on flawed sources (this is our history) only serves to increase the haystack rather than helping you to converge on truth.
> Unfortunately, so much of the humanities in high school is treated as an exercise rather than real discovery.
I, too, find this exceptionally annoying.
Don't get me wrong. I'm sure that once fine tuned by a human for a specific language pair that such systems are better at performing literal translation. But the value proposition of deep learning here is that you don't need a large team of experts to laboriously train a given language pair, that the entire training process is largely unsupervised, and that the translations aren't hopelessly literal. The ML algorithms can pick up on idioms given a sufficiently large dataset.
There's a reason we needed the Rosetta stone to give as an in for translating Egyptian hieroglyphics. You can't just throw Big Data at the problem and expect it to give accurate results. Dedicated translation setups can get good results, but ChatGPT's ilk doesn't.
Convincing translations are not the same thing as accurate translations. RLHF optimises for convincing, not accurate.
The transformer architecture, later modified to create GPT models, was originally designed for translation. The modifications to make it do predictive text in a chatbot style make it much, much worse at translating: one of the biggest issues is that generative systems fail silently. Using the tech appropriately gives you things like Project Bergamot: https://browser.mt/.
However, I think the idea is that LLM technologies have improved considerably since then. Do you still feel that Claude or ChatGPT perform worse than DeepL? It would be really nice to have an objective benchmark for comparison
Responding to GP, I won't object that LLMs aren't optimized for translation but I would generally expect them to perform quite well at it given that it seems to come with the territory of being able to respond to natural language prompts in multiple languages.
> massive, overfit generative models are awful at translation
> part-of-speech classification + dictionary lookup + grammar mapping – an incredibly simplistic system with performance measurable in chapters per second – does a better job
Those are two distinct claims you made and I'm not inclined to accept either of them without evidence given how unexpected both of them would be from my perspective.
[0] https://github.com/mozilla/firefox-translations-models/tree/...
When considering these failure modes, which have come up every single time I've seen ChatGPT used for translation, it's clear that the simplistic system I described would work better. It'll output gibberish often (just as LibreTranslate does when given decontextualised Chinese and asked to translate to English), but that's better than a GPT model, which will just confabulate something in the same circumstance. The goal isn't "maximise the amount of successful translatedness": it's "reduce the language barrier as much as possible", something the benchmarks don't test.
That GPT models are bad at translation, and will always be bad at translation (while, perhaps, "improving" where they're overfit on specific benchmarks), is obvious to anyone with even a cursory understanding of how they work.
Claims Sonnet 3.5 wins
Perhaps so. But not in the (quasi-)academic sense that the author is thinking. It's not the lack of an engineer's academic knowledge in history and philosophy that makes an AI system fail.
> Then there’s the newfound ability of non-technical people in the humanities to write their own code. This is a bigger deal than many in my field seem to recognize. I suspect this will change soon. The emerging generation of historians will simply take it for granted that they can create their own custom research and teaching tools and deploy them at will, more or less for free.
This is the lede buried deep inside the article. When the basic coding skill (or any skill) is commoditized, it's the people with complementary skills that benefit the most.
I think that "knowing how to ask good questions" that you then solve has always been a valuable skill.
And they will spend 12 hours trying to figure out which is the fake python library and the citation that the LLM has hallucinated from the real one. Vibe coding is just WYSIWYG on steroids in good and bad. WYSIWYG didn't go anywhere.
Maybe you haven't used AI coding tools in a while, the latest ones can run build tools, write and run unit tests, run linters, and will try and fix any errors that may arise during those steps. Of course it's possible that a library may have been been hallucinated, but this will just trigger an error during the build job and the AI agent will go back and fix it. Same thing for failing unit tests.
Just last week I saw Copilot fixing a failing unit test, then running the test, then making some more changes and repeating the process until the test was running successfully. At some point during this process, it asked me if it could install a VS Code extension so that it could run the test by itself, I agreed then it went from there until the issue was resolved. This was with the bottom-tier free version of Copilot.
Of course there are limits to what AI tools can do, but they are evolving all the time and at some point in a not too distant future they will be good enough in most cases.
Regarding hallucinated citations, I imagine that the problem can be solved by allowing the LLM to access and verify citations, then the agent can fix its own hallucinations just like most coding agents already do.
Like MS Word?
These are pretty easy to solve problems tbh. LLM tools already exist that can work around “hallucinating libraries” effectively, not that this a real concern. It’s not magic, but these tired skeptic takes are just not based on reality.
It’s much more likely that LLMs will be used to supercharge visualizations with custom UIs and widgets, or in conjunction with things like MS excel for data analysis. Non-engineers won’t be vibe-coding a database anytime soon, but they could be making a PWA that marketing can use to add a filter on photos or help guide a biologist towards a python script to sort pictures of specimens based on an OpenCV model.
If you already know how to build software LLM are a godsend. I have actually had a quite a nice case recently when LLM invented some quite nice imaginary graphql mutators. I had enough experience in the field to not waste time debugging, a historian that hadn't shipped software before won't.
There were WYSIWYG before, before them was visual programming - we have tried to abstract that pesky complexity since forever. So far with no success. I don't see anything in LLM/Gen AI whatever that will change it. It will make good people more productive, it would make sloppy sloppier, it won't make people bad at solving problems good at it.
It's not that LLMs turn low skilled people into geniuses, it's that a large segment of even those with enough cognitive skills to work in software today will no longer have marketable skill levels. The experienced good ones will have some, but a lot won't.
The big challenge is getting very different people with ever growing different skillsets and interests to coordinate, stay in sync and row in one direction.
Hayden White's assertion that "history is fiction" was (and still is) a complex one, not intended to dismiss the factual accuracy of historical narratives (as it is more often than not portraied).
Instead, it highlights the interpretive nature of historical writing and the way historians shape their accounts of the past through literary and rhetorical techniques. White argues that historians, like novelists, use narrative structures and stylistic devices to construct meaning from historical events.
2. As an MA student I was solving semantic problems for engineers for analysis that they couldn't fathom. They were very smart at technical things (and great writers), but when language problems come up, it was a challenge. You can be a great communicator but not understand language itself.
3. Most people in positions for AI are being evaluated by things AI is good at. So as a candidate with a very good understanding of language, the AI wouldn't know how to evaluate my ability. I would really have to outline a problem in language AI has to face and explain it to a human. Then get them to understand it's value.
Funny story, a year or so after my quals I was at a conference and talking about it (at a lunch table, not a presentation). I was saying with one of these questions I answered it correctly and explained why what they were asking wouldn't work. One of the senior professors at the table chuckled and said that he was one of the committee members for one of the members of my committee and how my committee member fell hook, line, and sinker for one of these questions and wrapped himself in circles during quals.
I think a humanities person could tell you in an instant how that part of the system prompt would backfire catastrophically (in a near-future rogue-AI sci-fi story kind of way), exactly because of the way it's worded.
In that scenario, the fall of humanity before the machines wasn't entirely due to hubris. The ultimate trigger was a smarmy throwaway phrase, which instructed the Internet-enabled machine to gaze into the corporate soul of its creator, and emulate it. :)
Instead, it's a statistical model, and including that prompt is more like a narrative weight than a logical demand. By including these words in this order, the model will be more likely to explore narratives that are statistically likely to follow them, with that likelihood determined by the content the model was trained on, and the extra redistribution of weights via training.
We don't really need to worry about technically misstating our objectives to an LLM. It doesn't follow objectivity. Instead, we need to be concerned about misrepresenting the overall vibe, which is a much more mysterious task.
From this, I agree with the article - since educators now have to figure out another hook to hang evaluation on, the questions "what the hell does it mean to 'learn', anyway?" and "how the hell do we meaningfully measure that 'learning', whatever it is?" have even more salience, and the humanities certainly have something meaningful to say on both of them. I'll (puckishly) predict that recitations and verbal examinations are going to make a comeback - harder to game at this point, but then, who knows how long 'this point' will last?
Education will adapt.
And if your summary is correct, he was right. If you don't remember what you've learned (i.e. integrate it into your mind), you haven't learned anything. You're just, say, a book operator.
The particular problem here is the number of staff needed to actually administer and grade these kinds of tests. We're already talking about how expensive education is, just wait till this happens.
The real question is: if writing alone doesn’t prove learning, then what does?
Maybe we’ll see a return to oral exams or live discussions. Not because they’re perfect, but because they’re harder to fake.
In a way, AI didn’t ruin education it just exposed problems that were already there.
By obsessively structuring education around measurement, we have implied that what is taught is objective fact. That's always been bullshit, but - for the most part - it's been consistent enough with itself to function. The more strict your presentation of knowledge is, the more it can pretend to be truly objective. Because a teacher has total authority over the methodology of learning, this consistency can be preserved.
The reality has always been that anything written is subjective. The only way to learn objective fact is to explore it through many subjective representations. This is obvious to anyone who learns mathematics: you don't just see x^2+y^2=z^2, and suddenly understand the implications of the Pythagorean theorem.
Because objectivity can't be written, objectivity is not computable. We can't give a computer several subjective representations of a concept, and have it figure it out. This is the same problem as ambiguity: there is no objectively correct way to compute an ambiguous statement. This is why we write in programming languages: each programming language grammar is "context-free", which means that everything must be completely and explicitly defined. To write a computable statement, we must subject the abstract concept in mind to the language (grammar and environment) we write it in.
Most of the writing in our society is done with software. Because of this, we are implicitly encouraged to establish shared context. If what we write is consistent with the context of others' writing, it can pretend to be objective, and be more computable. Social interactions that are facilitated by software are also implicitly structured by that software's structure. There can be no true free-form dialogue in social media.
The exciting thing about LLMs is that they don't have this problem. They conveniently dodge it, by not doing any logic at all! Now instead of the software subjecting you to a strict environment, it subjects you to a familiar one. There is no truth, only vibes. There is no calculation, only guesses. This feels a lot like objectivity, but it's just a new facade. The difference is that the boundary is somewhere new and unfamiliar.
---
I think the death of objectivity is good progress overall. It's been a long time coming. Strict structure has always been overrated. The best way to learn is to explore as many perspectives as you can find. We humans can work with vibes and logic, together.
This may be true for you, but it certainly isn't generally true.
I haven't written anything substantial on paper in years, and I certainly have learned new things in that time.
I just asked get ChatGPT a question about use of language in a specific book (China Miéville's Kraken). It gave a plausible answer but used a common English word ('knackering') instead of the word 'knacking' that is actually used (the word 'knackering' isn't in the text). I then asked it to give me a quote using 'knackering' and it gave me a quote with the word 'knacking'. I asked it to put the quote into Harvard reference style which it did, but didn't provide a page number, which it said I'd have to look up myself.
I think relying on ChatGPT for an essay would be fairly frustrating, and if you used ChatGPT to develop your thesis, you could very quickly get a generic plagiaristic answer (based on the quotes everyone else used) rather than one than that captured your own response to the text, and which contained factual errors.
[Edit] It also said that "gods inhabiting USB sticks are presented matter-of-factly" in Kraken which is false (there are no mentions of USB). When I asked it for a quote to support its assertion, it replied "While the novel doesn't explicitly depict gods inhabiting USB sticks..."
Try it for a text that is in the training data, or the public internet, or can be put into the context window - then it might help.
My point was that I would be very hesitant to rely on ChatGPT as an assistant in a real literature task. Many of the texts on my Eng Lit course are in copyright, as is all of the module material (the OU's course-specific textbooks). The hallucinations are a real show-stopper.
Give me a break, it's a hammer. This is a perfectly normal "use" of ChatGPT and a good example of how a literature student may opt to try and use AI to make their work easier in some way. It also conveniently demonstrates some of the shortcomings of using a LLM for this sort of task. No need to call them a dumbass.
Indeed. I'm doing a close reading of Kraken and have been amazed at the number of 'weird' entities and plot events that Miéville introduces [0]. It would be very easy to hallucinate a few more.
There are more than 100 passages in Kraken where Miéville names people, places and events that occur in other media or culture. For example, in a list of people associated with submarine technology, he throws in the name of the underwater stuntman [1] who played the Creature from the Black Lagoon. Again, it would be easy to hallucinate additional content.
[0] For example, a secondary character who was originally an ancient Egyptian burial slave-statue who went on strike in the afterlife, and in modern London is now the trade-union convenor for the Union of Magicked Assistants.
[1] Ricou Browning, if anyone is interested.
To those that missed the joke - 'consuming' the classics is the antithesis of a liberal arts education. The value lies in the engagement, the debate, the Hegellian dialectic involved in arriving at a true grok level understanding of the text or topic.
It would be akin to reading the Sparknotes of Ulysses and being able to reference how it draws heavily on Homer's Odyssey, or utilises stream-of-consciousness narrative to great effect; and thinking that, as a result, you have the faintest understanding of the text, its conception, or its impact.
The OP almost hit on this with the 'Listen to all the online lectures from Oxford,Yale,MIT etc...'. Unlike coding bootcamps or similar, universities are not VOCATIONAL TRAINING - no matter how skewed towards that end-goal the American Economy is dictating such. As just about any Educator can attest, no amount of listening to youtube lectures will replace the University experience, nevermind the Oxbridge/Ivy League experience.
The pedagogical benefits are simply unrealisable from an AI prompt 'streamlining'- i.e. being forced to read and engage with topics outside of your comfort zone to maintain your GPA, engaging and working with people from a diversity of outlooks and backgrounds, benefitting from the 1:1 and small group sessions with the Academics who often wrote the literal book on the subject in question.
If the intersection of JSTOR and Machine Learning didn't reduce humanities to Cory Doctorow level script-kiddyism, the hoi polloi throwing prompts into a hallucinatory markov chain isn't likely to advance or diminish Academia anymore than the excess of 'MBA IN 5 DAYS!' or '...for Dummies' titles previously available.
Any conversations I've had with students or graduates of Arts, Literature, etc. indicates that their education was very much about consuming and regurgitating. Maybe the top 5% approach their studies the way you're describing but I've never seen anyone like that in the wild.
I don’t think you’d do well in 400-level classes this way. English Lit isn’t as much of a joke as STEM students make it out to be[1]: it gets a lot harder than the bullshit 101/201 courses everyone is required to take. You’re supposed to try to be original in your analysis, and it has to be rigorously proven within the text itself.
Probably as a grad student you’d start arguing against other critics points, but not undergrad. I think that would hold for almost all schools because no one at that level in that field wants to hear from someone who doesn’t know how to analyze a text in the first place. It’d be like a high school student trying to tell you about software (or systems, network, data, etc.) engineering.
For similar reasons, AI summarizations for past contributions wouldn't work, either. If you’re arguing someone else’s analysis is wrong, you’re going to need to read and understand the whole thing. And if you’re just copying from AI, you’ll have a hard time defending your position.
Although, man, if you can understand the subtext of a book from listening to an audiobook *while gaming*, AND you have time to watch all the online lectures about a book!? I need to talk to you about time management, my friend!
1 - I have been involved in so many forums and subreddits where people try to analyze books, comics, TV, or movies. Based on what I have seen come out of people there —- most of you MFers couldn’t pass 300-level classes.
People can’t analyze literature for shit, and I think it’s because everyone gets such a negative perception of literary analysis because high school and required college classes are junk. It’s actually really hard to read five novels in month, keep track of all the characters and plots and themes and so on, and understand all of them well enough to write a coherent argument. I saw so many kids in my major crying about their GPA getting tanked because they weren’t ready for rigorous analysis. FWIW, I was 25 as a Junior (third year of uni, in the US), and had spent the last few years reading exercise physiology papers while bored at work. Seeing real science changed my life, and I wanted to apply their level of rigor to my own analysis of any kind. It’s why I’m good at my job now, tbh.
QFT. It's like the Sparknotes scenario I outlined in my post above - what you get from this level of engagement isn't insight, least of all a debatable position, it's just a loosely cohesive bunch of table-quiz facts.
//People can’t analyze literature for shit, and I think it’s because everyone gets such a negative perception of literary analysis because high school and required college classes are junk.
Because most of what is being examined is passive/active voicings, brain-dead symbolism, and ham-fisted and dated metaphors as literary vehicles.
Even at University level there should be an emphasis on a 101 level course hammering home the importance of Critical Theory in Literary Criticism as a framework and approach for disseminating texts. Without a basic understanding of the cultural, historical, and ideological dimensions under which a text was conceived and published, you haven't a hope of climbing the foothills of Beckett, Camus, Dickens, Dostoevsky, Eliot, Joyce, Kafka, Shaw...
AI should also be able to help you gather evidence from the reference texts, because it can exercise reasonable judgement without any constraint on patience or access or time. Consider the recent social media sensation about the lady who got a PhD for analysing how smell factors into the fates of literary characters. AI can quickly find thousands of examples, and then filter them as desired.
You could even have the AI write essays for you - “analyse this novel through the lens of ____ theory” - where no literary criticism already exists to review. You could have it generate any number of such essays, applying theories/frameworks you might not even know, but want to understand better.
I think it’s possible to “read” an audiobook while doing something monotonous like walking, driving, or, yes, gaming. The lectures you probably have to treat like podcasts and just play them in the background and pick up some ideas.
I can't tell if you're serious or not, but this would be like saying you've "watched" a movie because you had it on your second monitor while you were playing counter strike. There's a fundamental difference in hearing a book read to you and actually listening and engaging with the audio on a meaningful level. The latter requires focus, and you're not going to be able to do that if you're gaming away at the same time.
Put another way, why would someone who presumably loves reading bother studying literature if they don't actually care enough to pay attention to the books they supposedly loved?
The reason to do this is that just sitting in a chair ploughing through books gets very unappealing after a while. And there’s a lot of books to get through.
I think a lot of people, including, I presume, most who willingly choose to study literature, enjoy reading as an activity unto itself and so don't feel the need to add additional distractions. Not everybody finds sitting down and "ploughing through" (how disdainful a phrase!) a book unappealing.
The reading (listening) of course is not “in the background”. Maybe sometimes you’re distracted and have to skip back 30s and re-listen. Fine. If the game is too distracting, fine, play something simpler, or watch soccer, do chores, anything where the moment to moment continuity does not require effort to track, but still gives you some benefit.
If the student's goal at any Ivy League college is to 'meet their partner and their co-founder' then attending social functions where they can expand their networks and meet new candidates for those roles will take precedence over spending three hours diligently studying difficult material for every hour spent in lecture.
Of course, computer science students and others in hard sciences have been gaming the system for decades, with many solutions to take-home programming exercises found in online forums, and there's always the option of paying a tutor to ease the way forward - and LLMs are essentially inexpensive tutors that vastly help motivated students learn material - a key aide when many university-level professors view teaching as an unpleasant burden and devote minimal time and effort to it, with little material preparation and recycling tests from a decade ago that are all archived in fraternity and sorority collections.
The solution to students using LLMs to cheat is obvious - more in-class work, more supervised in-section work, and devaluing take-home assignments - but this means more time and toil for the instructors, who are often just as lazy and unmotivated as the students.
[note the in-person coding interview seems to have been invented by employers who realized anyone could get a CS degree and good grades without being a good programmer via cheating on assignments, and this happened well before LLMs hit the scene]
> The machines best us across nearly every subject
This feels overstated, given the well-known limitations of AI in reasoning, factual reliability, and depth in specialized domains
Describing traditional scholarship as mere "archaeological artifacts" feels like prematurely dismissing the enduring value of books and other research practices
- The idea that AI offers "pure attention" seems to romanticize what is, in essence, statistical pattern recognition...potentially misrepresenting the nature of the exchange
> Factory-style scholarly productivity was never the essence of the humanities
maybe inadvertent, but devalues serious academic work that follows rigorous, methodical research traditions
Beyond that, there's a few claims that would benefit from some additional evidence:
- student paralysis rely heavily on anecdote; broader empirical data across varied institutions would strengthen the case - His comparisons between AI and human experts feel selective...would be interested to see a more systematic evaluation to see where AI meaningfully matches or falls short of expert performance
- I'm somewhat partial to the author's view, but in terms of long-term educational outcomes, no real evidence to show that AI integration improves learning or contributes meaningfully to human development - the idea of a "singularity of self-consciousness" is pretty... under-argued? - The supposed link between declining humanities enrollment and AI's potential lacks concrete data to support the correlation
There are lots of people who fail this test. Many of them are professional evaluators in the humanities. They should unquestionably lose their jobs as evaluators.
Finding something like this is difficult and requires reading the text closely. But with AI, you could get away by reading around the passages returned by AI.
Finding some yes it might well be quicker than a manual read.
So it depends on what the actual requirement is.
The friction is a feature, not a bug.
The friction means only wealthy people can do anything in a sphere.
Just to give some examples...
The Martian - Andy Weir
Wool (Silo TV series based on this) - Hugh Howey
The Long Way to a Small, Angry Planet - Becky Chambers
Like with everything one can see the positives or focus on the negatives. The Internet today has great, good, medium and bad content, just as before, what's different is the effort and excitement we used to have back then.
I remember going to museums and seeing all the modern art, and wondering why art went to such weird places compared to the realism of the 1600's, and my conclusion was that invention of photography made realism obsolete. I wonder if something similar will happen to the humanities.
It's already been the case for a long time, it's just going to get worse.
This sums up the problem. It's not fun and the only thing that matters is the credential anyway , so unsurprisingly students are outsourcing to drudgery to AI. In the past it was CliffsNotes. The business model of college-to-career needs to be overhauled.
The humanities are important, yet at the same time, not everyone should be req. to study them. AI arguably makes it easier to learn, so think this is a welcome development.
Giant investments are being made, and a lot of people's outcomes rest on them, which incentivizes them to become evangelists for the cause.
End-of-day it is a productivity boosting tool like a search-engine or a calculator - whats funny to see the human drama playing out around its adoption.
On the one hand, this guy is not wrong, from a personal perspective. On the other hand, guys like this are a total waste of time and space in the classroom.
Schools have always faced a fundamental internal conflict, i.e., dueling purposes, and recent developments such as the rise of ChatGPT and the rise of student loan debt may have finally brought the entire educational system to a crisis.
We like to think of education as the primary purpose of the educational system, hence the name. And education is indeed essential, not just for job training but also for the enrichment of human life, as well as the preservation of democracy and freedom. Arguably, the latter are more important. Yet we also rely on the educational system for social and economic sorting. It's a ranking system that has a monumental effect on the future prospects of students. And as the above quotation notes, it's a club, an exclusive club, where the lucky few get to meet the right people and enter into important social circles.
At the university level, things become even more muddled, because professors and scientists are performing important research that may have little or nothing to do with the education of undergraduate students. A lot of this research is important for society, and for industry, but it still comes into conflict with the other purposes of the university.
So how do we resolve the inherent conflict? Is there a way to split the educational system into separate entities that are truer to their individual purposes? Can we make a place for the social ladder climber that's separate from a place where real learning happens, where nobody is tempted to cheat because there's nothing to be gained from cheating? It should also be noted that not everyone is ready to learn. Our current educational system is designed like an assembly line, based on age and social promotion. Everyone of the same age is expected to follow the same track. I personally wasn't ready to study and learn when I was a teenager; it took several more years for me to mature emotionally, develop ambition and discipline. It's difficult to force-feed students: “Most assignments in college are not relevant,” he told me. “They’re hackable by AI, and I just had no interest in doing them.” Perhaps, though, there might be more motivation to learn if learning was not tied to future economic and social prospects. If students view school as merely a tool to achieve certain benefits, then of course they'll view anything else in school as a waste of time.
In a sense, our educational system finds failure to educate to be acceptable, even desirable, because failure fulfills the alternative purpose of social ranking.
I don't think so. Let me suggest a set of hypotheses:
- the social ladder always exists; it's basically fundamental to human existence, especially when trying to do anything (see tyranny of structurelessness)
- people are always trying to climb the hierarchy
- the examocracy(+) was introduced by ancient Chinese and/or Prussia in an attempt to bring actual competence into the social hierachy, in large part to help the leader fight wars
- if there isn't a "fair" route to the top, competent outsiders will resort to unfair ones, which can be remarkably lethal and destructive
- the university provides its own small academic and intellectual hierarchy, but this exists in dialogue with the needs of a wider society and its demand for non-academic intellectually specialized work. Whether that's priests, lawyers, doctors, army officers, weapons designers, civil servants, or programmers
- this comes down to: does the wider society demand human competence in intellectual operations still, or does ALL of that get AI-automated away? Do we get "humans, but with a smarter Clippy" or do we get "AI runs the world for billionaires and everyone else is surplus peasantry".
- the secret third, worse, case is that AI destroys the concept of competence and things stop working on a large scale.
(+) I do not want to have a huge fight over the word "meritocracy"
I'm imagining for example that all citizens are required to receive an education, and demonstrate the same level of mastery in the subjects taught as everyone else, without grades or rankings. You might call it "pass-fail", but I resist that idea, because I don't consider failure to be an option, except in rare cases of learning disability.
Depends if you want the people running the country to be competent or not.
In some sense, the goal of the educational system should be to make everyone competent. In any case, it's unclear what you mean by "running the country". Politically speaking, the people currently running the US are not competent, despite the fact that the educational system and the social hierarchy are inextricably entangled.
Whatever kind of -ocracy you're proposing (I'm personally not proposing here that we abolish democracy), I don't see any inherent reason why a social ranking system and the educational system can't be separate rather than combined into one.
When employers start looking the alma mater of applicants, their grades in school, and such (reportedly Mark Shuttleworth of Canonical is obsessed with high school!), that's when the entire educational system gets warped. Learning gets cast aside in favor of credentialism, and consequently, cheating to get ahead.
No. Of course not.
> 99% of people simply can’t learn the same level of mathematics that a pure mathematician does
Why would this be a requirement for all citizens? Perhaps you misunderstood "demonstrate the same level of mastery". I meant that there would be a specified minimum requirement, though we definitely shouldn't set the bar too low. What I would reject is social promotion, where students get to move along to the next level as long as they have a D grade or higher. This does not demonstrate sufficient understanding of the material taught.
Grades are for ranking. I'm suggesting that we ditch grades and simply demand that everyone learn what we expect them to learn. If students learn more than what's expected, good for them, that's not a problem.
> what happens in your system to people who would have been pure mathematicians
I'm not sure what you mean. How am I preventing people from becoming pure mathematicians?
To a large extent, it's self-filtering: who is going to voluntarily take advanced math classes except those who are intered in advanced math?
There are of course larger societal questions of how much schooling is funded by the government and how much needs to be self-funded.
I don't know if this is what you're talking about, but I had to take the Graduate Records Exam in order to get into grad school. But the GRE is not taught or administered by the university, so in that sense it's not part of the educational system. You don't actually have to be in the math department to take an advanced math class, though, and other students may take the classes as part of a PhD minor or just for some other interest.
The only thing I can think of is that you (mistakenly) assume that I'm suggesting all students must move at the same pace? But that would be a very weird interpretation of me, since I've already expressed strong criticism of that idea: "Our current educational system is designed like an assembly line, based on age and social promotion. Everyone of the same age is expected to follow the same track."
You seem to be assuming that "all students must meet these standards" means that all students must meet these standards at the same age and time, but I never said or implied that.
The concept here is mastery rather than grades. When a student has mastered a subject, they can move onto more rigorous subjects. If they haven't mastered a subject, then they need to continue studying that subject. When we socially promote students who receive a grade of D, C, or even B, I wonder, what is the student missing? Why are we giving up and moving on just because an arbitrary amount of time has passed? And if the student has failed to completely learn things at the current level, what's going to happen when the student moves on to higher, harder levels? That's a disaster waiting to happen, compounding ignorance over time.
It appears that the "answer" to these questions is that our society cares more about ranking students than it does about educating students. So we allow the education to be incomplete for many or perhaps most students, as long as we already have our ranking from "best" to "worst" (at a given age). This is, in my opinion, an unfortunate consequence of the multiple conflicting purposes of the educational system.
> (Similarly, later, how do you know which ones should get into the best universities? And so on)
I already talked about the GRE, for example, so I don't know why you're still confused about that. (I'm not actually defending the GRE, or the SAT, another standardized test, but there are clearly ways to evaluate people separate from schools and grades.)
I do have some problems with the inequality of opportunities implied by "the best universities", but that's a whole other discussion. I've already mentioned that the conflicting purposes of the educational system extend to the college level too, are arguably even worse at that level. Think back to the very first quote I posted, from the A.I. cheater for whom the point of an Ivy League university was not to receive an education but to make the right social connections. How is academic achievement even relevant there? To me, this is a sign that the current system is fundamentally broken.
No. It just steals them, whitewashes their copyright, then passes them off as a "machine creation." If there were no humans actively using language there would be no language models.
> Generative AI makes it harder to teach humanistic skills
Yea. That's what happens when you steal for a living.
> For this reason, it is vitally important that educators learn how to personally create and deploy AI-based assignments and tools that are tailored directly for the type of teaching they want to do.
All with zero evidence that this will improve outcomes for them. For this reason you should TEST YOUR HYPOTHESIS.
I hate AI hype.
It is kind of funny, since modern sociology and humanities are in a deep denial of theory of evolution, Darwinism and any of its implications.
> producing a generation of students who have simply never experienced the feeling of focused intellectual work.
This was already blamed on phones. Some study said like 30% of university graduates are functionally illiterate; they are unable to read book, and hold its content in memory long enough to understand it!