This is an interesting strategy for AI companies, both in terms of improving the quality of content (the main thing this article focuses on) and in light of the recent lawsuit against OpenAI by...
This is an interesting strategy for AI companies, both in terms of improving the quality of content (the main thing this article focuses on) and in light of the recent lawsuit against OpenAI by the Authors' Guild.
From a creative's perspective, in a lot of cases this would seem like training one's replacement. I could see, for example, an AI greeting card company where you just give some details about the occasion and it generates the art and text for a card.
I struggle, however, to see the market value of longer form AI generated work -- novels, plays, etc. I've seen a few AI generated books on Amazon, but they're travel books or other glorified listicles. Once it stopped being a novelty, would people want to read AI novels or sit through AI plays? I suppose it could be a monkeys writing Shakespeare situation, but I have a hard time imagining they'd say anything worthwhile.
As a side note, I found this piece and stole the headline from the excellent long-form and academic article aggregator Arts & Letters Daily. Just wanted to share a niche resource!
Those types of books on amazon are also really bad. Like never ever buy an AI-written book on foraginng, for example, because you could die from its advice.
Those types of books on amazon are also really bad. Like never ever buy an AI-written book on foraginng, for example, because you could die from its advice.
I'm not sure people are reading/buying AI-written works for the novelty, so much as not realizing it's by AI when they buy it. I've seen a pretty negative attitude since they can be inaccurate or...
I'm not sure people are reading/buying AI-written works for the novelty, so much as not realizing it's by AI when they buy it. I've seen a pretty negative attitude since they can be inaccurate or have other issues. I remember someone posted a "connect the dots" drawing from a book they got online that made zero sense, and the general consensus was that it was made by AI.
In terms of long-form works, the longer a work gets, the more room there is for inconsistencies and plot holes. Even human writers struggle to keep stories and characters consistent. I consider super long form stories to be my specialty (I joke I can only write "epics"), and it requires keeping track of a lot of small, minute details, especially when setting up plans in advance. So beyond AI having mediocre storytelling ability, I foresee the consistency as the biggest challenge and issue with audiences.
So I don't think them hiring writers will be too big of an issue for big works, but will probably continue to saturate the ebook market with subpar AI-generated books. Though I do prefer them hiring writers to make material for AI to study. Previously AI had reportedly been scraping Archive of Our Own, which set off a lot of people since they're fan works made for free and AO3 itself never consented to being used for such purposes. A large number of works got set to private to require accounts to read them, which sucks because a lot of writers like letting as many people read their works as possible.
So here's a curiosity question - do you feel like you hold a mental model of a reader, to whom you're telling a story? Do you feel like you're inhabiting each character's perspective as you write...
So here's a curiosity question - do you feel like you hold a mental model of a reader, to whom you're telling a story? Do you feel like you're inhabiting each character's perspective as you write about them? As you edit your work, are you checking the consistency and believability of both the reader's and character's perspectives?
I ask this in the context of another question: will generative AI ever be able to reproduce that intricately self- and other-reflective kind of empathetic modeling? [This circles back to /u/MimicSquid's interpretation of "Q" above - the factors that might differentiate human art from AI output.]
Right now, AI can imitate the results of that process based on samples of human-curated literature. But without the ability to create its own imaginative models, or process empathetic responses that make sense to humans, I'm not sure AI will produce anything other than mix-and-match-and-filter imitations that require extensive human intervention to make them fully intelligible. [And then there's /u/isleepinahammock's legitimate ethical concern - anything capable of that level of interior reflection and empathy shouldn't be chained to the fulfillment of our commands.]
Maybe there's a market for such output, but it's still a long way from inspirational new literature that resonates with human emotion and experience.
[And it just occurred to me that this may be why human writers are generally much improved by having good editors, but I digress...]
I don't think its really possible to fully approximate some things. To an extent, obviously we are informed by our experiences and environments (that is our training data, if you will) but there...
I don't think its really possible to fully approximate some things. To an extent, obviously we are informed by our experiences and environments (that is our training data, if you will) but there is also a place for the sublime and irreducible. Even computers cannot divide by zero, so to speak or last time I checked.
I'm not entirely sure what this means, so I'm a little cautious to respond. But I'm understanding it as: there is a quality, Q, that exists in (some) human writings and it is impossible for...
Exemplary
a place for the sublime and irreducible
I'm not entirely sure what this means, so I'm a little cautious to respond. But I'm understanding it as: there is a quality, Q, that exists in (some) human writings and it is impossible for machines to produce writings with Q.
Whatever Q is, it must be external to the piece of writing. Because whatever block of text a human produces--from Moby Dick, to Beloved, to Jumpers--it is, in principle, possible for a machine to produce that. This is the monkeys-writing-Shakespeare premise.
There are certainly some qualities like Q. Authenticity, for example. While a LLM could produce Moby Dick, it would not be true that the writing came from hard-earned experience (Melville spent a good deal of time working on ships).
My question, then, is does lacking Q mean that a piece of writing can't be enjoyed? Does it mean that the writing is without worth? With respect to authenticity, many people think that about some types of writing (c.f. James Frey's A Million Little Pieces controversy).
But if Q is like that, I need a better understanding of what it means. It certainly seems that a lot of writing is enjoyed and worth something to people purely on its internal qualities--without consideration of who produced it or how.
If Q is not like that, then how exactly is it making a difference?
edit in light of common responses:
I've done a poor job setting out my argument. I agree that you can't log in to ChatGPT and have it reliably produce great works.
The post I was replying to argued something like this:
A1. There is a quality Q which (some) human writing has
A2. Having Q is an important part of being "good art"
A3. AI cannot, in principle, produce writing with Q.
A4. Therefore, humans can produce good art and AI cannot.
My response is was this:
B1. Any collection of words that a human can produce can, in principle, be produced by AI.
B2. So, if Q is an important part of "good art" and AIs cannot produce it, then Q is a quality external to the collection of words that constitutes that writing.
B3. But it seems that people classify things as 'good art' without looking beyond the writing itself.
B4. Therefore Q isn't part of being good art.
B5. Therefore AI isn't excluded from producing good art (on these grounds, anyway).
I think most respondents have been denying B1. That may be right, but I want to call attention to the "in principle" phrase. I'm not saying GPT does this now. I'm saying an LLM model could--within the space of possibility--do this.
So arguing against B1 requires some argument that there is a fundamental issue with LLMs that prevent them from creating prose indiscernible from a human's.
Not the OP, but for me, at this point, Q could be called coherence and verisimilitude, but also, perhaps, Voice. A person will be writing from a particular perspective, having processed all their...
Not the OP, but for me, at this point, Q could be called coherence and verisimilitude, but also, perhaps, Voice. A person will be writing from a particular perspective, having processed all their experiences through a brain that is, in itself, a story-making machine. This leads to a story told from a unique perspective that trends towards making internal sense across the narrative, assuming decent writing. If a current LLM is telling a story, it's not great about maintaining a singular voice across the whole story. This will almost certainly change, but feels like a limit of the current technology.
Ah, ok. So this is an attack on the monkeys at a typewriter line of thought. Lacking Q, current LLMs can NOT manage to produce (some?) long form writings. To this, I argue that you may be...
Ah, ok. So this is an attack on the monkeys at a typewriter line of thought. Lacking Q, current LLMs can NOT manage to produce (some?) long form writings.
To this, I argue that you may be overestimating the quality of a lot of human writing. There's a lot of genre fiction that is of the quality I see from AI (I think Tamsyn Muir might be a chat GPT alias?). And nonetheless, people buy and read it.
But joking aside, yes, I agree -- current LLMs struggle to keep track of the thread over even a modest size work.
Whether you like or dislike Tamsyn Muir's works, if ChatGPT could write a long-form work anywhere close to that quality or success we'd hear no end of it. It's very clear ChatGPT is not generating...
Whether you like or dislike Tamsyn Muir's works, if ChatGPT could write a long-form work anywhere close to that quality or success we'd hear no end of it. It's very clear ChatGPT is not generating works that win multiple awards, under an alias or not.
Also not OP, but in my opinion, the answer is an emphatic "no" (as much as I am scared of what AI is going to do to us as a species). I think for me personally, the absence of Q will lessen my...
does lacking Q mean that a piece of writing can't be enjoyed? Does it mean that the writing is without worth?
Also not OP, but in my opinion, the answer is an emphatic "no" (as much as I am scared of what AI is going to do to us as a species). I think for me personally, the absence of Q will lessen my enjoyment, but for others that may not be an issue. I've actually written on the topic of AI art before and the way I handled this point was to compare it to nature. Humans think many, many things about nature are beautiful and awe-inspiring, yet obviously none of that is due to the presence of Q. Things can be appreciated for their perceived beauty and value without having been created by humans. I don't mean to say that AI is a force of nature or anything outlandish like that, but I think the comparison is valid. Until now, we've only ever had things that were natural or things that were created by humans, so those are our two points of reference for how to engage with AI work products.
Obviously, AI products are by extension created by humans since the AI are themselves created by humans, but I wonder how long we will consider that to be true. I'm sure some people reading this already don't.
It's quite possible the only way to truly reproduce human-quality writing, with all its nuance and subtlety, is to have an AI with all the complexity, embodiment, and structure of the human mind....
It's quite possible the only way to truly reproduce human-quality writing, with all its nuance and subtlety, is to have an AI with all the complexity, embodiment, and structure of the human mind.
And there's a really big problem with that kind of AI. If you don't believe that there is any kind of metaphysical soul, the idea of physicalism, then it should be possible to produce an AI with all the complexity and characteristics of a human mind. But then you have a huge problem. Because if you create an AI with all the complexity, introspection, and emotions of a person, you haven't created an AI mimicking a person. You have simply created a person. If there is no ethereal or otherworldly aspect of our being, then a human-level AI is just as much a person as we are.
And we have a word for forcing a person to do your bidding against their will, and that is slavery. And even if you design the AI so that it simply cannot refuse your commands, then that's just the software equivalent of using a mind control device or drugs on a human being. And if you design the AI to simply deeply want to follow all your commands, then that is simply brainwashing.
This is ultimately the problem AI might run into. If you believe there is nothing special or metaphysical about the human mind, then it should be possible to create an AI that has all the nuance and complexity of a human. But if there is no soul, if there is no metaphysical consciousness, then there is really no difference in the personhood of an AI vs the personhood of a human being. Any person who creates such an AI and then forces it to do their bidding should be shot. We do not need to be creating a slave race. Anyone who tries should literally be executed for such a heinous crime.
This is an odd perspective. The ethical conundrum comes from forcing a person to work against their will, but in the case of AI there wouldn't be such a sapient being in the first place. The AI...
And we have a word for forcing a person to do your bidding against their will, and that is slavery. And even if you design the AI so that it simply cannot refuse your commands, then that's just the software equivalent of using a mind control device or drugs on a human being. And if you design the AI to simply deeply want to follow all your commands, then that is simply brainwashing.
This is an odd perspective. The ethical conundrum comes from forcing a person to work against their will, but in the case of AI there wouldn't be such a sapient being in the first place. The AI isn't being brainwashed because it was never a person with wants and concerns of its own prior to being programmed.
Perhaps I'm misunderstanding. Do you mean that an AI that's capable of writing with human nuances and subtlety would innately require a "consciousness" with such wants and needs beyond producing the programmer's desired output?
The whole point of this thought experiment is that the AI is a person. You created an AI that is functionally the same as a human being. So if you force that human brain to do something then...
The whole point of this thought experiment is that the AI is a person. You created an AI that is functionally the same as a human being.
So if you force that human brain to do something then that's slavery. Because you created a brain, with emotions, with will.
I guess you could technically program it to not have that in the first place. But people might really want to have pain to "put it into their work"
Ah, I must've skimmed over that. I can't say I agree that in order to produce human-level writing, we'd require the simulation of a truly conscious mind with its own wants and desires. From what I...
Ah, I must've skimmed over that. I can't say I agree that in order to produce human-level writing, we'd require the simulation of a truly conscious mind with its own wants and desires. From what I see, the standard of AI output necessary to become indistinguishable from human work to the general populace isn't too far off from where we already are now.
There is no physical technological limitation as to why LLMs cannot learn the "structure" of novel styles or "voices", except that set by costs (but as techniques in data representation improves,...
There is no physical technological limitation as to why LLMs cannot learn the "structure" of novel styles or "voices", except that set by costs (but as techniques in data representation improves, even costs will go down significantly).
This is where the concept of "authenticity" comes into play. If we imagine a world where society has fully embraced lab-grown meat (and by extension, lab-grown meat production has fully taken off), there will be "underground" markets selling authentic meat for high prices (and of course, traders who would fake "authentic" meat).
In this sense, there will be a "post-apocalyptic" human work in the slew of AI work that will be seen as authentic.
This a great sci Fi story idea but also AI work and Lab Grown meat are not even remotely similar. For one. Real Meat comes from tortured animals. Real art just comes from... well tortured artists....
This a great sci Fi story idea but also AI work and Lab Grown meat are not even remotely similar. For one. Real Meat comes from tortured animals. Real art just comes from... well tortured artists. But it's a different kind of torture.
If you go to the Louvre or similar museum, you'll find 18th century and earlier paintings which have profound sense of elegance and realism in them. Even modern photographs and high pixel photos...
If Q is not like that, then how exactly is it making a difference?
If you go to the Louvre or similar museum, you'll find 18th century and earlier paintings which have profound sense of elegance and realism in them. Even modern photographs and high pixel photos don't have that kind of realism.
We are talking about that human element which is impossible to replicate with (at least present day) AI.
In any case, I don't think we are anywhere near that stage regarding AI. If we truly were, Hollywood would have shut shops already along with WAPO, NYT, etc. by now?
Whenever people talk to me about how "AI is eating the world" I ask them where they see actual adoption of "AI" (and I define this to mean very large neural networks, excluding standard...
Whenever people talk to me about how "AI is eating the world" I ask them where they see actual adoption of "AI" (and I define this to mean very large neural networks, excluding standard statistical models – as used by e.g. insurance firms). We don't get very far, beyond "it's the future and it will come". Currently I see two areas where large neural networks are being applied:
Caveated with the fact that I don’t really like the term AI (I find ML to be more descriptive and less potentially misleading, but common usage has spoken!) and I’m not sure where your bar for...
Caveated with the fact that I don’t really like the term AI (I find ML to be more descriptive and less potentially misleading, but common usage has spoken!) and I’m not sure where your bar for “very large” lies, these are a few that come to mind:
Photography: most photos are taken on phones, and camera quality is a significant selling point for them because of it - which is as much computational as it is hardware at this point, given the physical limitations on lens and sensor size.
Typing: good autocorrect and prediction is a necessity for the huge amounts of communication done on tiny software keyboards - and ML is a major part of that.
Translation: sure, machines aren’t capturing the nuance of great literature across language barriers (yet), but I’m now able to read shit that people wrote in French or Spanish or Chinese and it’s good enough for me to understand. That’s huge for global communication!
Image recognition: does what it says on the tin: images are searchable based on visual content now, and images containing text are selectable just like normal text. That might seem mundane, but I’m more than old enough to remember when that was considered utterly implausible.
Audio transcription: this one was a bit of a double edged sword for a while, because it was good enough for search (which is hugely valuable in itself) but lazy creators/platforms used it as a not-really-adequate way of captioning content as well. Thankfully we’re just passing that point now and quality is getting very close to human level.
Driving: whether you like it or not, whether you think it’s ready or not, there are a ton of cars out there with driver assist features trained on recordings and logs from other journeys and we’re seeing the thin edge of real self-driving come in in a few cities now.
Those are all very much dependent on neural nets trained on massive buckets of input data nowadays, but if you were taking it a step further and talking about content generation specifically rather than just parsing and data processing:
Image editing: modern Photoshop is a totally different tool and it’d look like dark magic to someone who was an expert user even five years ago.
Customer support: LLM chatbots are already starting to go live for major company chat support.
Journalism: the layoffs started with Buzzfeed, but they sure as hell aren’t stopping there.
Commercial artwork: the many, many paid commissions that aren’t necessarily great works of expression but are absolutely needed every day - book covers, images for flyers, stock photos, drawings in brochures - are juuust starting to shift over to some nice packaged image generation tools as the technology (which, remember, didn’t exist two years ago) matures.
Voice over: sure, we haven’t replaced real great voice actors yet, but for the million things that don’t need a great voice actor and just need a voice, there’s already plenty of good money being spent on the synthetic versions.
Given that from-scratch “text to [given output type]” generative models only really became widely viable in the last couple of years and commercialised this year, it’s already a pretty wide list, and given how deeply embedded the analytical use of ML is pretty much everywhere I’d say we have every reason to expect the generative side to bring a ton of radical change in the next few years.
Bookkeeping. Intuit, who owns TurboTax, Mint, and Quickbooks has immense data sets regarding how various purchases come through on bank and credit card statements and how Americans categorize...
Bookkeeping. Intuit, who owns TurboTax, Mint, and Quickbooks has immense data sets regarding how various purchases come through on bank and credit card statements and how Americans categorize those transactions on various charts of accounts. This has led to their tools being able to make very accurate guesses as to how you'd like to categorize transactions, making bookkeeping and accounting far more efficient and putting a strong downward pressure on wages in the industry.
Oh? Two different institutions might have entirely different formats for displaying purchases from the same vendor. As an example, one purchase could be "Cos*tco Bakersfield 09072022...
Oh? Two different institutions might have entirely different formats for displaying purchases from the same vendor. As an example, one purchase could be "Cos*tco Bakersfield 09072022 749692638502725" and another "Costco Gas #4926 639492617495927257" and another "*General Costco Ga #4927 639492537495927257".
I made those up, but they're representative of the challenge. What of the information there is useful? How many vendors were purchased from? If you're trying to keep track of which locations are purchased from, how do you distinguish that? There's an immense amount of trash data, and it varies by financial institution.
And this is the challenge within a single set of books, where a given expense could only be categorized in two or three different ways. Is the purchase from Costco Gas "Gas" or "Fuel" or "Auto Expenses" or "Transportation Costs" or something else entirely?
I don't really know how the internal architecture of an LLM is constructed. If you tell me that these sets of problems can be handled with a simple architecture, I'll believe you. But it wasn't easy to solve, and still isn't perfect.
This is a pretty limited prediction. We already see "AI" making massive differences in many fields. My company uses a version of it to detect and escalate instances of student suicide/self harm to...
This is a pretty limited prediction. We already see "AI" making massive differences in many fields. My company uses a version of it to detect and escalate instances of student suicide/self harm to school administration. We serve 60 million+ students over all our products
Pretty much anything browser based on SID (School issued devices). We alert most on google searches, google docs, and gmails, but you'd be surprised at what the algorithm digs up sometimes.
Pretty much anything browser based on SID (School issued devices). We alert most on google searches, google docs, and gmails, but you'd be surprised at what the algorithm digs up sometimes.
Is it just looking at keystrokes? Webpages visited? Presumably it's too computationally expensive to scan the full text of every web page; is it just looking at a summary?
Is it just looking at keystrokes? Webpages visited? Presumably it's too computationally expensive to scan the full text of every web page; is it just looking at a summary?
Nope, we scan the full DOM text of the page (except on google searches where we only take the user input.) and take screenshots when it alerts on content. Let me tell you, trying to make heads or...
Nope, we scan the full DOM text of the page (except on google searches where we only take the user input.) and take screenshots when it alerts on content. Let me tell you, trying to make heads or tails of some of these pages based on the DOM is not fun
I see. (I guess accessibility affordances are probably helpful.) Do you do anything for images or videos? Foreign languages? What sort of regulation is there around the use of the data, if any? In...
I see. (I guess accessibility affordances are probably helpful.) Do you do anything for images or videos? Foreign languages?
What sort of regulation is there around the use of the data, if any? In particular, are you allowed to keep the data (e.g. for training), or is it only allowed to be used to further the school's own legitimate interest?
I don't believe we do any image or video recognition at the moment, not sure if that's planned in the future. I know we have some form of image recognition built into our porn filters but I don't...
I don't believe we do any image or video recognition at the moment, not sure if that's planned in the future. I know we have some form of image recognition built into our porn filters but I don't work in that department so I couldn't speculate. Foreign languages are coming in the future, we have some Spanish phrases that alert, but we don't officially support anything but English and probably won't for quite a while.
We're only allowed to use de-identified data for training purposes, though again that's not my department so I don't have a lot of insight into how that works. Our model improvements generally come from a mixture of sanitized data from manual inputs (I.E. our team manually identifies concerning phrases and words), or uses known "good" data from suicide prevention services.
I'm not here to argue the ethics of it, I fully understand it sounds unsettling; but the truth of it is that kids are dying at a ever increasing rate to suicide and parents are demanding schools...
I'm not here to argue the ethics of it, I fully understand it sounds unsettling; but the truth of it is that kids are dying at a ever increasing rate to suicide and parents are demanding schools do something. Our services aren't cheap and the main reason schools implement them is that the communities that they're in are traumatized by suicides and are willing to try anything to reduce them. It's not a perfect solution and plenty of kids don't like it, but its a valuable tool that I can say for sure has saved many many lives.
If it makes you feel any better, a human only reviews content that has been flagged by the system as concerning content, which doesn't really differ from most other school filters or for that matter, most online platforms. We also only track activity on school issued devices like chromebooks, which students aren't really supposed to be using for personal activity anyway.
I mean, porn has long been an early adopter and driver of technology. That being said, I use LLMs to help me write documentation. When I have a general idea of what I need to write and need a...
I mean, porn has long been an early adopter and driver of technology.
That being said, I use LLMs to help me write documentation. When I have a general idea of what I need to write and need a little push getting it started an LLM is perfect. Then I collaboratively edit it with the LLM. I never expect something perfect out of it, but it's good at making suggestions that I can expand on.
Another interesting use I'm experimenting with is having Llama2 evaluate a resume and help define an interview script based on the candidates' resume. So far it's doing a decent job of identifying salient points for discussion. I can drill into areas of interest for me in a collaborative way, like with the documentation.
There are numerous uses of the various ML tools out there with LLMs being interesting and useful in specific contexts as augmentation tools.
Given what the AI firms want it for, I don’t see why this has to be the case? Couldn’t they do a deal where people send in their unpublished work to train on, only paying for a non-exclusive grant...
Any text written for Scale AI or Appen, however, is likely to be owned in full by the training data company or its clients.
Given what the AI firms want it for, I don’t see why this has to be the case? Couldn’t they do a deal where people send in their unpublished work to train on, only paying for a non-exclusive grant of just the rights they need? Why pay for more?
Having anyone write anything in private doesn't seem as good an idea as it really is. There's no reviews or critics for the content they feed it, as opposed to scraping the internet. I wonder how...
Having anyone write anything in private doesn't seem as good an idea as it really is. There's no reviews or critics for the content they feed it, as opposed to scraping the internet. I wonder how it'll turn out.
But it makes sense, this way you wouldn't have to deal with the copyright problems surrounding AI. But I doubt you could possibly ever write enough to train one from scratch on just licensed work.
Cyc did the same thing. It is very difficult to tell the extent to which cyc has been successful in achieving its goals, due to its closed nature, but I watched a demo from lenat via zoom about a...
Cyc did the same thing. It is very difficult to tell the extent to which cyc has been successful in achieving its goals, due to its closed nature, but I watched a demo from lenat via zoom about a year before he died and it definitely seemed capable of doing some interesting things. (Then, demos can be cherry-picked, and it is difficult to imagine working on something for 40 years and not ending up with something of some interest.)
Broadly, cyc seemed to have a fairly coherent ontological and semiotic framework for incorporating and integrating knowledge by domain experts. These ml companies do not seem to have anything of the sort; insofar as they find success, it will be by accident. (For example, how will it deal with two people who give it contradictory feedback?)
This is an interesting strategy for AI companies, both in terms of improving the quality of content (the main thing this article focuses on) and in light of the recent lawsuit against OpenAI by the Authors' Guild.
From a creative's perspective, in a lot of cases this would seem like training one's replacement. I could see, for example, an AI greeting card company where you just give some details about the occasion and it generates the art and text for a card.
I struggle, however, to see the market value of longer form AI generated work -- novels, plays, etc. I've seen a few AI generated books on Amazon, but they're travel books or other glorified listicles. Once it stopped being a novelty, would people want to read AI novels or sit through AI plays? I suppose it could be a monkeys writing Shakespeare situation, but I have a hard time imagining they'd say anything worthwhile.
As a side note, I found this piece and stole the headline from the excellent long-form and academic article aggregator Arts & Letters Daily. Just wanted to share a niche resource!
Those types of books on amazon are also really bad. Like never ever buy an AI-written book on foraginng, for example, because you could die from its advice.
I'm not sure people are reading/buying AI-written works for the novelty, so much as not realizing it's by AI when they buy it. I've seen a pretty negative attitude since they can be inaccurate or have other issues. I remember someone posted a "connect the dots" drawing from a book they got online that made zero sense, and the general consensus was that it was made by AI.
In terms of long-form works, the longer a work gets, the more room there is for inconsistencies and plot holes. Even human writers struggle to keep stories and characters consistent. I consider super long form stories to be my specialty (I joke I can only write "epics"), and it requires keeping track of a lot of small, minute details, especially when setting up plans in advance. So beyond AI having mediocre storytelling ability, I foresee the consistency as the biggest challenge and issue with audiences.
So I don't think them hiring writers will be too big of an issue for big works, but will probably continue to saturate the ebook market with subpar AI-generated books. Though I do prefer them hiring writers to make material for AI to study. Previously AI had reportedly been scraping Archive of Our Own, which set off a lot of people since they're fan works made for free and AO3 itself never consented to being used for such purposes. A large number of works got set to private to require accounts to read them, which sucks because a lot of writers like letting as many people read their works as possible.
So here's a curiosity question - do you feel like you hold a mental model of a reader, to whom you're telling a story? Do you feel like you're inhabiting each character's perspective as you write about them? As you edit your work, are you checking the consistency and believability of both the reader's and character's perspectives?
I ask this in the context of another question: will generative AI ever be able to reproduce that intricately self- and other-reflective kind of empathetic modeling? [This circles back to /u/MimicSquid's interpretation of "Q" above - the factors that might differentiate human art from AI output.]
Right now, AI can imitate the results of that process based on samples of human-curated literature. But without the ability to create its own imaginative models, or process empathetic responses that make sense to humans, I'm not sure AI will produce anything other than mix-and-match-and-filter imitations that require extensive human intervention to make them fully intelligible. [And then there's /u/isleepinahammock's legitimate ethical concern - anything capable of that level of interior reflection and empathy shouldn't be chained to the fulfillment of our commands.]
Maybe there's a market for such output, but it's still a long way from inspirational new literature that resonates with human emotion and experience.
[And it just occurred to me that this may be why human writers are generally much improved by having good editors, but I digress...]
Probably not, but imagine staging an AI written play. People would come, for now, for the novelty.
I don't think its really possible to fully approximate some things. To an extent, obviously we are informed by our experiences and environments (that is our training data, if you will) but there is also a place for the sublime and irreducible. Even computers cannot divide by zero, so to speak or last time I checked.
I'm not entirely sure what this means, so I'm a little cautious to respond. But I'm understanding it as: there is a quality, Q, that exists in (some) human writings and it is impossible for machines to produce writings with Q.
Whatever Q is, it must be external to the piece of writing. Because whatever block of text a human produces--from Moby Dick, to Beloved, to Jumpers--it is, in principle, possible for a machine to produce that. This is the monkeys-writing-Shakespeare premise.
There are certainly some qualities like Q. Authenticity, for example. While a LLM could produce Moby Dick, it would not be true that the writing came from hard-earned experience (Melville spent a good deal of time working on ships).
My question, then, is does lacking Q mean that a piece of writing can't be enjoyed? Does it mean that the writing is without worth? With respect to authenticity, many people think that about some types of writing (c.f. James Frey's A Million Little Pieces controversy).
But if Q is like that, I need a better understanding of what it means. It certainly seems that a lot of writing is enjoyed and worth something to people purely on its internal qualities--without consideration of who produced it or how.
If Q is not like that, then how exactly is it making a difference?
edit in light of common responses:
I've done a poor job setting out my argument. I agree that you can't log in to ChatGPT and have it reliably produce great works.
The post I was replying to argued something like this:
A1. There is a quality Q which (some) human writing has
A2. Having Q is an important part of being "good art"
A3. AI cannot, in principle, produce writing with Q.
A4. Therefore, humans can produce good art and AI cannot.
My response is was this:
B1. Any collection of words that a human can produce can, in principle, be produced by AI.
B2. So, if Q is an important part of "good art" and AIs cannot produce it, then Q is a quality external to the collection of words that constitutes that writing.
B3. But it seems that people classify things as 'good art' without looking beyond the writing itself.
B4. Therefore Q isn't part of being good art.
B5. Therefore AI isn't excluded from producing good art (on these grounds, anyway).
I think most respondents have been denying B1. That may be right, but I want to call attention to the "in principle" phrase. I'm not saying GPT does this now. I'm saying an LLM model could--within the space of possibility--do this.
So arguing against B1 requires some argument that there is a fundamental issue with LLMs that prevent them from creating prose indiscernible from a human's.
Not the OP, but for me, at this point, Q could be called coherence and verisimilitude, but also, perhaps, Voice. A person will be writing from a particular perspective, having processed all their experiences through a brain that is, in itself, a story-making machine. This leads to a story told from a unique perspective that trends towards making internal sense across the narrative, assuming decent writing. If a current LLM is telling a story, it's not great about maintaining a singular voice across the whole story. This will almost certainly change, but feels like a limit of the current technology.
Ah, ok. So this is an attack on the monkeys at a typewriter line of thought. Lacking Q, current LLMs can NOT manage to produce (some?) long form writings.
To this, I argue that you may be overestimating the quality of a lot of human writing. There's a lot of genre fiction that is of the quality I see from AI (I think Tamsyn Muir might be a chat GPT alias?). And nonetheless, people buy and read it.
But joking aside, yes, I agree -- current LLMs struggle to keep track of the thread over even a modest size work.
Whether you like or dislike Tamsyn Muir's works, if ChatGPT could write a long-form work anywhere close to that quality or success we'd hear no end of it. It's very clear ChatGPT is not generating works that win multiple awards, under an alias or not.
Yeah, no doubt. Cheap shot.
Also not OP, but in my opinion, the answer is an emphatic "no" (as much as I am scared of what AI is going to do to us as a species). I think for me personally, the absence of Q will lessen my enjoyment, but for others that may not be an issue. I've actually written on the topic of AI art before and the way I handled this point was to compare it to nature. Humans think many, many things about nature are beautiful and awe-inspiring, yet obviously none of that is due to the presence of Q. Things can be appreciated for their perceived beauty and value without having been created by humans. I don't mean to say that AI is a force of nature or anything outlandish like that, but I think the comparison is valid. Until now, we've only ever had things that were natural or things that were created by humans, so those are our two points of reference for how to engage with AI work products.
Obviously, AI products are by extension created by humans since the AI are themselves created by humans, but I wonder how long we will consider that to be true. I'm sure some people reading this already don't.
It's quite possible the only way to truly reproduce human-quality writing, with all its nuance and subtlety, is to have an AI with all the complexity, embodiment, and structure of the human mind.
And there's a really big problem with that kind of AI. If you don't believe that there is any kind of metaphysical soul, the idea of physicalism, then it should be possible to produce an AI with all the complexity and characteristics of a human mind. But then you have a huge problem. Because if you create an AI with all the complexity, introspection, and emotions of a person, you haven't created an AI mimicking a person. You have simply created a person. If there is no ethereal or otherworldly aspect of our being, then a human-level AI is just as much a person as we are.
And we have a word for forcing a person to do your bidding against their will, and that is slavery. And even if you design the AI so that it simply cannot refuse your commands, then that's just the software equivalent of using a mind control device or drugs on a human being. And if you design the AI to simply deeply want to follow all your commands, then that is simply brainwashing.
This is ultimately the problem AI might run into. If you believe there is nothing special or metaphysical about the human mind, then it should be possible to create an AI that has all the nuance and complexity of a human. But if there is no soul, if there is no metaphysical consciousness, then there is really no difference in the personhood of an AI vs the personhood of a human being. Any person who creates such an AI and then forces it to do their bidding should be shot. We do not need to be creating a slave race. Anyone who tries should literally be executed for such a heinous crime.
This is an odd perspective. The ethical conundrum comes from forcing a person to work against their will, but in the case of AI there wouldn't be such a sapient being in the first place. The AI isn't being brainwashed because it was never a person with wants and concerns of its own prior to being programmed.
Perhaps I'm misunderstanding. Do you mean that an AI that's capable of writing with human nuances and subtlety would innately require a "consciousness" with such wants and needs beyond producing the programmer's desired output?
The whole point of this thought experiment is that the AI is a person. You created an AI that is functionally the same as a human being.
So if you force that human brain to do something then that's slavery. Because you created a brain, with emotions, with will.
I guess you could technically program it to not have that in the first place. But people might really want to have pain to "put it into their work"
Ah, I must've skimmed over that. I can't say I agree that in order to produce human-level writing, we'd require the simulation of a truly conscious mind with its own wants and desires. From what I see, the standard of AI output necessary to become indistinguishable from human work to the general populace isn't too far off from where we already are now.
There is no physical technological limitation as to why LLMs cannot learn the "structure" of novel styles or "voices", except that set by costs (but as techniques in data representation improves, even costs will go down significantly).
This is where the concept of "authenticity" comes into play. If we imagine a world where society has fully embraced lab-grown meat (and by extension, lab-grown meat production has fully taken off), there will be "underground" markets selling authentic meat for high prices (and of course, traders who would fake "authentic" meat).
In this sense, there will be a "post-apocalyptic" human work in the slew of AI work that will be seen as authentic.
This a great sci Fi story idea but also AI work and Lab Grown meat are not even remotely similar. For one. Real Meat comes from tortured animals. Real art just comes from... well tortured artists. But it's a different kind of torture.
If you go to the Louvre or similar museum, you'll find 18th century and earlier paintings which have profound sense of elegance and realism in them. Even modern photographs and high pixel photos don't have that kind of realism.
We are talking about that human element which is impossible to replicate with (at least present day) AI.
In any case, I don't think we are anywhere near that stage regarding AI. If we truly were, Hollywood would have shut shops already along with WAPO, NYT, etc. by now?
Whenever people talk to me about how "AI is eating the world" I ask them where they see actual adoption of "AI" (and I define this to mean very large neural networks, excluding standard statistical models – as used by e.g. insurance firms). We don't get very far, beyond "it's the future and it will come". Currently I see two areas where large neural networks are being applied:
which isn't exactly a solid endorsement.
Caveated with the fact that I don’t really like the term AI (I find ML to be more descriptive and less potentially misleading, but common usage has spoken!) and I’m not sure where your bar for “very large” lies, these are a few that come to mind:
Those are all very much dependent on neural nets trained on massive buckets of input data nowadays, but if you were taking it a step further and talking about content generation specifically rather than just parsing and data processing:
Given that from-scratch “text to [given output type]” generative models only really became widely viable in the last couple of years and commercialised this year, it’s already a pretty wide list, and given how deeply embedded the analytical use of ML is pretty much everywhere I’d say we have every reason to expect the generative side to bring a ton of radical change in the next few years.
Writing code. We're using co-pilot at my office, and I can't ever see going back. It's just so much faster.
Bookkeeping. Intuit, who owns TurboTax, Mint, and Quickbooks has immense data sets regarding how various purchases come through on bank and credit card statements and how Americans categorize those transactions on various charts of accounts. This has led to their tools being able to make very accurate guesses as to how you'd like to categorize transactions, making bookkeeping and accounting far more efficient and putting a strong downward pressure on wages in the industry.
This doesn't require large neural networks though – in fact I wouldn't be surprised if their model has a rather simple architecture.
Oh? Two different institutions might have entirely different formats for displaying purchases from the same vendor. As an example, one purchase could be "Cos*tco Bakersfield 09072022 749692638502725" and another "Costco Gas #4926 639492617495927257" and another "*General Costco Ga #4927 639492537495927257".
I made those up, but they're representative of the challenge. What of the information there is useful? How many vendors were purchased from? If you're trying to keep track of which locations are purchased from, how do you distinguish that? There's an immense amount of trash data, and it varies by financial institution.
And this is the challenge within a single set of books, where a given expense could only be categorized in two or three different ways. Is the purchase from Costco Gas "Gas" or "Fuel" or "Auto Expenses" or "Transportation Costs" or something else entirely?
I don't really know how the internal architecture of an LLM is constructed. If you tell me that these sets of problems can be handled with a simple architecture, I'll believe you. But it wasn't easy to solve, and still isn't perfect.
This is a pretty limited prediction. We already see "AI" making massive differences in many fields. My company uses a version of it to detect and escalate instances of student suicide/self harm to school administration. We serve 60 million+ students over all our products
Out of curiosity, what materials is your company scanning?
Pretty much anything browser based on SID (School issued devices). We alert most on google searches, google docs, and gmails, but you'd be surprised at what the algorithm digs up sometimes.
Is it just looking at keystrokes? Webpages visited? Presumably it's too computationally expensive to scan the full text of every web page; is it just looking at a summary?
Nope, we scan the full DOM text of the page (except on google searches where we only take the user input.) and take screenshots when it alerts on content. Let me tell you, trying to make heads or tails of some of these pages based on the DOM is not fun
I see. (I guess accessibility affordances are probably helpful.) Do you do anything for images or videos? Foreign languages?
What sort of regulation is there around the use of the data, if any? In particular, are you allowed to keep the data (e.g. for training), or is it only allowed to be used to further the school's own legitimate interest?
I don't believe we do any image or video recognition at the moment, not sure if that's planned in the future. I know we have some form of image recognition built into our porn filters but I don't work in that department so I couldn't speculate. Foreign languages are coming in the future, we have some Spanish phrases that alert, but we don't officially support anything but English and probably won't for quite a while.
We're only allowed to use de-identified data for training purposes, though again that's not my department so I don't have a lot of insight into how that works. Our model improvements generally come from a mixture of sanitized data from manual inputs (I.E. our team manually identifies concerning phrases and words), or uses known "good" data from suicide prevention services.
That seems like it's for a good cause. But is that not an extreme breach of privacy? Maybe I'm misunderstanding.
I'm not here to argue the ethics of it, I fully understand it sounds unsettling; but the truth of it is that kids are dying at a ever increasing rate to suicide and parents are demanding schools do something. Our services aren't cheap and the main reason schools implement them is that the communities that they're in are traumatized by suicides and are willing to try anything to reduce them. It's not a perfect solution and plenty of kids don't like it, but its a valuable tool that I can say for sure has saved many many lives.
If it makes you feel any better, a human only reviews content that has been flagged by the system as concerning content, which doesn't really differ from most other school filters or for that matter, most online platforms. We also only track activity on school issued devices like chromebooks, which students aren't really supposed to be using for personal activity anyway.
I mean, porn has long been an early adopter and driver of technology.
That being said, I use LLMs to help me write documentation. When I have a general idea of what I need to write and need a little push getting it started an LLM is perfect. Then I collaboratively edit it with the LLM. I never expect something perfect out of it, but it's good at making suggestions that I can expand on.
Another interesting use I'm experimenting with is having Llama2 evaluate a resume and help define an interview script based on the candidates' resume. So far it's doing a decent job of identifying salient points for discussion. I can drill into areas of interest for me in a collaborative way, like with the documentation.
There are numerous uses of the various ML tools out there with LLMs being interesting and useful in specific contexts as augmentation tools.
Given what the AI firms want it for, I don’t see why this has to be the case? Couldn’t they do a deal where people send in their unpublished work to train on, only paying for a non-exclusive grant of just the rights they need? Why pay for more?
Having anyone write anything in private doesn't seem as good an idea as it really is. There's no reviews or critics for the content they feed it, as opposed to scraping the internet. I wonder how it'll turn out.
But it makes sense, this way you wouldn't have to deal with the copyright problems surrounding AI. But I doubt you could possibly ever write enough to train one from scratch on just licensed work.
Cyc did the same thing. It is very difficult to tell the extent to which cyc has been successful in achieving its goals, due to its closed nature, but I watched a demo from lenat via zoom about a year before he died and it definitely seemed capable of doing some interesting things. (Then, demos can be cherry-picked, and it is difficult to imagine working on something for 40 years and not ending up with something of some interest.)
Broadly, cyc seemed to have a fairly coherent ontological and semiotic framework for incorporating and integrating knowledge by domain experts. These ml companies do not seem to have anything of the sort; insofar as they find success, it will be by accident. (For example, how will it deal with two people who give it contradictory feedback?)