I'm looking for a way to protect my GPL/MPL/other code and CC game artwork against ML that would ingest it to produce other work. The only exception is when someone uses maps to train AI-driven bots - that's fine. So, I'm looking into some standardized way to tell my work is for human use only. Ideally, also in automated way, like prefixing headers with something like /* <NOML> */.
My rather unpopular view is that if its available for humans to read on the internet, there is nothing different than a machine reading it, other than scale. There is nothing stopping a human from reading your code and using it themselves, or at the very least adapting it for themselves. Unless its a copy or contains actual code you have written then Im not sure you can actually defend it....other than having it locked down on the internet. Of course none of this is tested in court, and my feeling is that once it is, we will end up with a system similar to the robots.txt or maybe even the ML companies forced to attribute work, which would be a major pain for them. Personally Im not sure where I stand with what is right or wrong as I can see both arguments...for example Artists regularly take inspiration from closely studying other artists, producing works from them which is often similar or the same style. Yet this is seen as perfectly ok in the Art world, as long as its not a copy, much of the time they dont even need to say who inspired them. How is this different from AI doing the same thing other than it not being human ? On the other hand someone sees a company making money from something that looks inspired from their art, with no credit, I can also understand how they might feel...its going to be very interesting how this plays out, and at this point either side could win
> there is nothing different than a machine reading it, other than scale
Copyright itself was introduced because of the scale of the printing press, which fundamentally changed the economics of publishing. Is it reasonable to assume that scale doesn’t change things?
With ML there's the "M", machine, and that machine (and its algorithms btw) is owned by someone. If we back away from general concept of intelligence a bit, that owner is who can be held accountable. Maybe that would get them motivated a bit.
And with the robots.txt approach, I understand, there'll definively be some rogue AI that would parse and process that on purpose :)
As for "doing the same thing", well, kind of, yeah, we're back to the thousands years old copycat problem. But this time art/code creators don't want others having machine that could recreate years of work in a minute with a push of a button. Also, artists usually acknowledge who did they learn from or who's style are they trying to recreate... but that's an ethic thing..
I agree on this. I don't see any difference between a human looking at my work and learning to imitate it, and some AI doing the same.. The AI will just be better at doing it.
Artists regularly take inspiration from closely studying other artists, producing works from them which is often similar or the same style
ML is only superficially using the same process. Behind the scenes the computer is not being 'inspired'; it's using the art from other people, along with metadata about it, as a data source to derive a new image using math. That isn't the same as seeing someone else's picture and using it for inspiration.
I do see your point on this, though not sure if you can use that differentiation between human inspiration and what a computer is doing, we take a mental image and interpretation could be seen as metadata. Just because the mechanics are different doesn't mean its not similar in process. I guess you could say the emotion is not there, but is that enough to differentiate ? Still a good point though , adds more questions to the mix
I wanted to say that the human still commands the genertor to make a form of art using prompt. But then I've got a shivering feeling that someone might connect generator (of prompts) to another generator to another... and then close the loop.
Anyway, I've always said (and keep saying) that art is what (visibly) distinguishes humans from animals. And machines.
The right to restrict learning from the literary work is not a right that is granted under copyright.
You can make your code something that cannot be _reproduced_ without a license, but you cannot stop someone from learning ideas from your published code. This does not require a license (only distributing, or making derivative works needs licenses).
Whether that learning comes via ML, or a real flesh human brain, i think, makes no distinction. You will need to lobby for an update to copyright laws to add a new right to be granted.
> The right to restrict learning from the literary work is not a right that is granted under copyright.
And yet, it's apparently perfectly legal to put DRM on books and control exactly when and how they are read [1] - by actual humans.
> Whether that learning comes via ML, or a real flesh human brain, i think, makes no distinction.
Strongly disagree here. Sure, ML shops would like that to be the case, but for now it's just muddying the waters by using anthropomorphizing language.
What you call "learning" is so far just scraping the data to adjust model weights using an algorithm in a machine. Contrast that with a human drawing knowledge or inspiration from a work they read before. Those two are different things, unless you want to assume that ML models have a conscious mind and constitute a person - at which point, you'll have much bigger ethical problems than copyright violations.
IANAL but copyright allows you to control the reproducing medium, in the case of DRM this would be the digital files. It doesn't allow you to control the ideas presented in the medium, so copyright alone cannot restrict you showing the page you're reading in your e-book to your friend or friendly AI. If you publish on the internet you can by copyright restrict someone else from downloading your work and putting it up somewhere else, but you cannot restrict who views it if you put it in a public place. There are other license agreements for that of course but then you'd have to force people to agree to it in order to view your blog post or fan art first. Nothing is stopping gated community sites that require an account to view stuff to require a suitable license agreement. I'm pretty sure it would restrict the views though..
Regarding "just scraping the data to adjust model weights using an algorithm", all research so far shows that the brain does just this, even though the full details of the algorithm are unknown and all the places the weights are encoded are not known in full.
> you cannot restrict who views it if you put it in a public place
actually, public display is one of the rights that the copyright holder can control too. Private display, on the other hand, is not. So you can show it to your friend, or AI in private, but not project it in a public place unless the copyright holder agrees.
What I meant was, if the copyright holder puts it in a public place, copyright won't hinder others from viewing it, I'd hope at least... which is analogous to putting your .jpg on your web page for general consumption.
this is, unfortunately, a right to distribution and display. It is most definitely not learning.
> Contrast that with a human drawing knowledge or inspiration from a work they read before.
But neural networks is mimicking a human's brain function in simplified form. The requirement for consciousness is not needed. If the argument is that humans' brains do something so special that a machine cannot be made to reproduce it, then you have an argument; but i do not believe it to be true.
Using a machine created algorithm to extract ideas, knowledge, structure and form from a literary work is exactly what i would call learning.
Imagine, as an example, i learnt how to make/cook new recipes by looking at existing recipes. Is the knowledge gained from doing so a derivative work of the existing recipes?
What if i wrote a machine and parsed these recipes, extracted all of the forms/patterns, and used it to reproduce new recipes? How is the outcome any different from above?
One huge difference is scale and effort, which have much larger implications than whether something is “learning”. When a human learns a work of art, it is a single human that took weeks, months, or even years to accomplish a similar work. Only that single human is incremental to the market for that product. Furthermore, that human can improve upon or create an entirely new field or style of work.
With machines, this process is replicated instantly and becomes pervasive, resulting in elimination of many humans performing the work. This can destroy the potential creativity that was possible from the replaced humans within that specific trade. The machine learning of today is stupid and simple with no creativity, only copies or amalgamations of existing works. The end result is the death of progress within that trade and potentially stagnation of the human race as it perfects the use of the tools (e.g. prompt engineers, glorified button pressers) and ceases to move things forward.
While I agree with the dystopic projection, I strongly disagree with your notion that the AI image gens are not creative. I've used them for more than 6 months and am amazed every day I use them what creativity they display. I don't do anything generic, I usually push them to do odd things and I can guarantee they are not doing copies or amalgamations. They do understand the gist of most styles and objects and can combine everything in novel ways just like a human artist would.
People who claim they copy/paste stuff and can't be creative have clearly not used them very much.
> This can destroy the potential creativity that was possible from the replaced humans within that specific trade.
You could argue the same from any introduction of technology that replaces humans. If the output of the machine is of sufficient quality to replace humans, then they should be replaced.
If the fear is that those displaced humans will no longer be useful, then society will need to subsidize their existence, or find a way to make use of those displaced humans (such as retraining). It is an unrelated problem to copyright, and copyright should not be used to ensure some group of humans do not get displaced.
> only copies or amalgamations of existing works.
Not that i agree with the premise of machines lacking creativity, but many of today's human created content is of such level as well.
But without a legal precedent in place and an official standard, web scraping to use for machine learning purposes can't tell the difference, and frankly shouldn't have to.
Reproduction of the original data is one problem, but if we create restrictions around using data for training purposes I believe this is a huge impediment to human progress.
I would imagine that the state of the art in foreign language translation (Google translate, etc) would fall significantly behind for example.
courts don't create new rights, they interpret existing laws.
I can't really see how the existing copyright laws can be interpreted such that a distinction could be made between a machine learning and a human learning.
The fact that you can't see it doesn't mean others can't. The difference is blindingly obvious to me.
Courts do indeed interpret existing laws. The question of whether current laws regarding human learning apply equally to machine learning is one of interpretation, precisely the sort of thing that is ultimately resolved by court decisions, including appeals potentially up to the supreme court, establishing precedents. Until that process takes place, your interpretation is just your interpretation, not the interpretation.
It's not a right of the machine we're talking about, but the rights of the copyright holder that is purporting to claim that ML models trained with their works is a derivative of their works, and thus can claim copyright over the ML model.
I do not believe such rights exist under current copyright laws. Others argue that it does (or ought to exist).
Exactly. The current laws were made based on typical human capabilities. Since the level of remembering content that some of these AIs now do is different (potentially more accurate and maybe faster) it would make sense to treat them accordingly.
Additionally there is something to be said for overfitting: On one end of a spectrum I could have a well trained AI and on the other end I could have a lookup table of the training data and somewhere in the middle maybe a model that overfits a lot and produces something close to the original content. How about that? I think there are a lot of interesting questions here.
I believe trying to achieve this result misses the point in the long term. What are you going to do once a model reproduces your code/art without ever seeing it?
Well, I've just thought of something: what if I replace the term "learning" with "parsing", or, better, "processing"? That, of course, rises some ambiguities too, but keeps away from rabbit hole of "learning".
If we define "learning" as automatic processing in an intent to accumulate data and logics vital to reproduction of similar work... (not compilation, though) But I'm lost in thoughts )
At least I could prevent machine parsing... probably.
* 1. Right to control the reproduction of the work
* 2. Right to control the making of derivative works
* 3. Right to control the distribution of the work
* 4. Right to control the public performance of the work
* 5. Right to control the public display of the work
* 6. Right to perform a sound recording publicly by means of digital audio transmission
The closest is the right to make derivative works - is the ML model a derivative work of the training data? I guess this would need to be tested out in court.
Note that number 6 is a special case that clarifies based on a technology. What’s stopping the creation of another clarification based on this technology like “The right to control the use of the work for generating artificial generators.”
The fact that there is no legal concept that limits using a work as machine training data has no relation to the fact that there is a word "learning" in ML though. I would suggest stopping referring to "learning" in this context.
Yes, i think this is the fundamental question (or disagreement). Is the right to using the work as training data something that needs to be granted by the copyright holder, or is implicit when granting the right to view the work?
My argument is that it is implicit - a human viewing the training data is allowed to learn from it. There's no reason to differentiate a human brain from a machine "brain" in this context.
You insist on using the word "learning" to refer to completely different concepts as if you don't read anything I write.
On the off chance you do: it's not about some a "need" to differentiate or not. They are just completely different, unrelated in all ways concepts. Are you familiar with cases where a single word is used for unrelated things as a metaphor?
A machine does not learn in human sense because it lacks and will always lack consciousness. If you want human rights to apply to machines you first have to prove they have consciousness. If you do that (let's pretend), the subject of this thread stops being an issue, because once a machine has human rights no one is able to use it to make unlimited copyright-violating works without paying equivalent human wage, making the entire point of ML acting as copyright laundering tool moot.
> You insist on using the word "learning" to refer to completely different concepts as if you don't read anything I write.
i read it, and i disagree that they are completely different concepts. I am describing the action of "extracting information, structure, ideas and form" from a literary work. I used the word "learn" as a shortcut.
A consciousness is not required to perform the action above. Human rights also does not apply to a machine - we aren't talking about sentient ai being given rights that would normally be reserved for humans.
The right to "learn" from literary works is not an exclusive right granted by the copyright law to the holder. A tool would only launder copyright if the tool was used to reproduce the literary work, or a derivative of said work. But if the tool is producing new works, but expresses similar ideas (which is what a lot of the ML models allow you to do), then those expressions should not violate copyright.
As for the model itself, i also argue that it does not constitute a derivative work of the training dataset. I am comparing it to a human brain, which itself is not a derivative work of the training that went into producing it (e.g., the authors of all of the books said human brain read does not have a claim on the brain itself).
Of course, society could opt to change this - specifically add a clause to the copyright law to grant an extra right to the holder regarding ML consumption of their literary work. This has not happened yet, and i sincerely wish it does not. It merely stifles progress.
The law does not limit what you can do with my work within your human mind, but that's it. I don't think there needs to be a separate license simply because basic "all rights reserved" copyright by its spirit already precludes use as training data. The letter may need to be clarified to avoid people drawing these parallels between human mind and silicon thinking it grants some extra rights, but we'll see what the courts say.
I think it's more likely media giants will reinforce copyright. Once companies like WB etc catch on that we can nearly generate unlimited art in their style, stuff that they charge us for normally, they'd put an end to this
And if OpenAI training data excludes their artwork from training data then the answer is obviously that copyright matters and they only exploit small artists unlikely to sue (which would make openai legally liable)
The legal theory used by ML companies that allows them to use any and all data a crawler can reach on the internet rests on the idea that training ML models with data is always fair use. ML companies thus argue they are entitled to ignore such directives, as those would be based around copyright licensing, and according to their own legal theory that's unnecessary for them.
And just to be clear, a theory is all this is. It has never been tested in court.
At least I could try writing something future-proof, in case this uncertainty changes. No one can be "entitled to" access everything they stumble upon. E.g. accessing restricted government resources is prohibited. I'm myself not a lawyer by any means, all I can do now is write something "Stop right there, machine scum!" in hope in the future this will do something.
Or we could agree on some industry standard for now, like robots.txt... which doesn't, of course, guarantee anything.
I didn't work on the AI policy stuff at EFF, but the last time I remember this question explicitly coming up was in the Google Books case, where Google cited language model training as an example of a fair use of book scanning (more than a decade ago, when it wasn't yet obvious how powerful language models would become). I don't recall if EFF specifically endorsed that example, but we did support Google's overall position.
I'd estimate a decent chance EFF will say that there isn't a right under existing copyright law to restrict machines from learning from copyrighted works. Remember that EFF usually does not want copyright rights to be stronger. (Probably the most general way to put it is that EFF basically always wants new uses of creative works made possible by technology not to be governed by copyright -- to have their benefits accrue to users.)
(I worked at EFF from 2001 to 2020.)
Edit: you could look at Jaron Lanier's stuff for the opposing view; I don't know if he has any specific technical or legal proposals.
>E.g. accessing restricted government resources is prohibited.
Do you have that problem? That your code/art is accessible to the wider world when it shouldnt be? In that case it sounds more like a task for somebody with a security background then for someone with knowledge of copyright.
The truth is... .gov data is leaking here and there, but, if it's not the access that is punished, then it's the distribution... or knowledge. Which brings us to a VERY sensitive topic of knowledge. And thought crimes. /(o_o)\
I have zero compassion for attempts to push the ball down this spectrum. If you miss configured your server the answer isnt criminalizing more and more stuff. Its fixing your server config and access policy. Your configuration, your problem. There is nobody else to blame once you know its leaking.
While I can understand what you mean, that paves way to a different extremity: basically, "it's your fault your toaster was stolen - you didn't build safe enough house" argument.
What I am trying to assess, though, is the fact that "there's something that is not yours and the owner decides if you can have/copy/ML it". Not the fact that someone did. Or, if did, what would the consequences be.
If you leave it in front of your property next to the trash can without a pricetag then yes it absolutely is. Because people rightfully assume you are giving stuff away. We are not talking about "not safe enough", we are talking about you giving a copy to anyone who wants one. Nothing is stolen, you are handing stuff out and dont bother to check who you give it to.
Trying to skip over the admin to fix this missconfiguration and going straight to the lawyer is the attempt to externalize costs. Which is where the lack of compassion comes in. This is a shitty thing to do.
This is not a lawyer problem, nobody broke in, nobody took anything. You are giving stuff away. Go talk to an admin on how to only give your toaster to the people that you want to give it to.
You say that accessing restricted government resources is prohibited, but even this restriction has caveats. Famously, (New York Times Co v. United States) the federal government could not stop newspapers publishing stories based on classified documents they had obtained.
If they're restricted than how did a data crawler find them?
But that doesn't matter. For this topic we only care about the materials that are intentionally published to the open web, and the different ways those materials can be licensed.
This is completely different from piracy which is enabled by a distributed network of individuals who have strength in numbers, it would be impossible to prosecute them all. On the other hand copyright laws are extremely effective in stopping legal entities from distributing copyrighted content without repercussions.
These advanced AI models will be trained and licensed by current and future corporations. A law or judicial precedent that denies "fair use" when it comes to machine learning would stop OpenAI and GitHub Copilot dead in their tracks. I'm not that worried about Billy's home-brewed AI model, it's just something we'll have to accept, but stopping exploitation on the scale of $billions would get us 99.9% of the way there.
> In my opinion: Copyright is a failure and the absolute best move, with the advantage AI has given to everyone, is to abolish copyright.
I agree with this. I fundamentally disagree with the idea of introducing 2 different sets of rules which completely correlate with wealth; companies being allowed to bypass copyright laws to train their models and make money from "our" work, while retaining copyright over their software and trained models.
I might agree with machine learning using "fair use" as a defense iff the datasets, trained models, and all accompanying software are released into the public domain. This way everyone gets to benefit from these technological advancements.
Probably, yes. But I'm not really trying to put up a copyright barrier to enforce or sue people. I at least want to have a way of telling AI developers "please don't do that".
The <NOML> tag is a nice idea, maybe #noml social networks. But its efficacy depends on the good will of those who create the datasets. Another approach could be a NOML registry for art and code.
But practically what you need to do is to stop crawlers from reading your code/art by robots.txt or captcha. If your works don't get into CommonCrawl and similar datasets they won't be used for model training. I think you can still enable Google Bot while rejecting AI data collectors on your sites.
<rant>
I think copyright refers only to expression, not the ideas themselves. So training on copyrighted code and art should be ok as long as expression is not copied.
In these cases where an AI developer wants to train on the ideas without learning the expression they can re-generate the data using the "variations" method, works both in image and text. This will create substitute data, like anonymising PII.
</>
I also want my work protected from being used to train models that will produce code where my attribution and redistribution conditions are not respected. In particular, I don't want my work to help building proprietary software. Or I want to at least be paid for this. I explicitly use (A)GPL so people need to make their work available to their users, with the relevant rights to adapt and redistribute, if they want to use mine.
However, I'd rather not see a separate license / mechanism for this, because now we would have people who'd be fine with their work being used this way, people like us who are not fine with this and people who don't know / care. And mixing code from people of these different groups, which the licenses you cited allow, is going to be a mess.
I also would like that this not be opt-out, but opt-in.
Eventually, we need the legal system to do its work quickly and tell us if fair use can be used to train ML models and in which conditions, so we can build a strong defense.
The stated purpose of copyright law is to promote the Progress of Science and the Arts.
Congress decided to grant limited "rights" to copyright holders as incentives for them create, not to protect their work forever, but in exchange for it to be widely available and eventually in the public domain.
That these incentives take the form of limited protections is a side effect. That the original purpose is often corrupted and delivered ham-handedly has more to do with politics than purpose.
If we argued from first principles, we could invent a better system, but that system would undoubtedly allow for ingestion and manipulation by AI.
If you put code online publicly-readable then there is a signicant probability that it is allowed to train ML on it. So the first step you need to take is not doing that. You must ensure that anyone that reads your code has first signed an agreement not to train ML on your code.
If like GPL you want to allow people to share your code further, and make derivative works, then you must ensure that those people lock such works behind restrictions in the same way, such that derivative works can also only be read after signing the license.
Basically, what GPL and variants of CC do. Ideally, I'd want some universal addendum to whatever license I choose for my work. But, again, I'm no lawyer, and that could be hard to create.
You can obfuscate your codebase, forcing the ML to generate endless amounts of intangible boilderplate.
You can add malevolent code to your code base, which allows at best for the ml project to gain self-awareness (copilot "shodan") and at worst to just add maleware. Of course you then
Dont forget to remove the evil pre-compilation. If you do art, i think the best think to throw AI would be fractal details, aka your picture never ends upon zoom in, but just becomes more art. That or you try to throw the weights in another way.
Heh-heh... Now you made me want to add some unused crashy-washy honeypot functions to my libraries :)))) This thought kinda sliped into my mind not long ago. But that won't work with the art. You can't put "unused pixels" into your picture. :D (but what about steganography, though?... I wish I could do a science paper on this)
You can do horrendous things. All it takes one ground truth provider to not sanitze the input, and meta being trained in. Imagine hosting images, that are poisoned to corrupt training data:
I wonder if you could add api calls that are billed per call to your open source project and let copilœdUpCode accumulate tremendous bills before sending them at the end of year.
Imagine you can get it to do it in useless loops async. I just realized, im watching the "capitalist software revolution eating itself" stallman always prophesized live. Allmende public thrust is being eaten up and all that remains is a dark forrest, stalked by parasite riddled hunters and prey.
That is until humanity rebels and dissolves all companies larger then 100 people.
I don't get your comment about copilot code, it's not a zip bomb, when you use copilot or any other type of coding assistant, it just auto completes your code. any reasonably proficient software developer is going to sanitize and proofread appropriately. It's an LLM - not a sandbox to compile and execute code.
Same thing applies to the idea of self similar imagery, a.k.a. a fractal. Once you rasterized it, it's by definition no longer recursive in nature.
I mean people have had this idea "poisoning the well" for over a year now, but it's nothing more than a thought exercise, since even a whiff of what effectively amounts to malware would completely destroy your reputation as a software developer.
Yes, the proof... Actually, there must be some diff tool to compare models before and after processing some source? I'm not sure, but it must be possible to detect pieces of come ingested data in the model itself. I've seen the famous "wolf misdetection" investigation screenshots, when the AI, apparently labeled a dog as a wolf because there was snow around on the picture.
For Stable Diffusion I think the average number of bits in the model compared to the number of training images is in the order of 6-8 bits per image. There is no "storage" of the training images. It's 250 TB data in, and 1.4 GB in the weight file or so depending on the precision.. I think those 250 TB are compressed as well, so maybe 25,000 TB raw data in distilled down to 1.4 GB. I fairly certain you could never prove an AI saw your image. You'd have to sue the company and by discovery look at their training data.
There are probably pathological cases where a repeating image is more strongly overfit in the training data and could be reproduced in much more detail than this average though. But the systems learn similar to the human brain, they learn the gist of a style or scene and how it relates to words. It's not a search engine, it doesn't copy/paste any block of pixels...
One interesting example is that since SD's original training set included some stock photo watermarked images, it learned that there was a concept of watermark, which can end up in the middle of generated images. Not in an intelligible way, but you can see roughly how it interpreted this detail. And in those cases you DO have a very very repeating similar pixel bitmap in the training data.
This comment is such a shallow dismissal of a good post that brings up a genuine and legally complex question that many readers of HN care about.
Are you trying to be clever? Because this comment is anything but clever. It is not hard to define humans. The humans are biologically animals and have a certain set of properties that can be easily searched online. For instance https://en.wikipedia.org/wiki/Human
And no you cannot just weasel your way into somehow fooling us or a jury that machines and AI algorithms that exhibit similar properties are also human! I frankly don't understand the point of your comment.
Well while I see your eagerness to defend the definition of human, it may for futures sake be a very valid question. It may not be too far in the future here we will see brain enhancements, or maybe even ocular implants which a "human" will read with but extra processing takes place elsewhere by machines. What if its a blind human, using machine assisted reading, what if humans are reading and inputing data into the machine ? All these questions and more should be asked now....so we can plan for the future. Right now is a great example, we are beginning to see the explosion of AI creation, yet nothing to govern it. Dont be so quick to smack down questions until you consider the broader implications is all I am saying
> I see your eagerness to defend the definition of human
I am not eager to defend the definition of human. Your comment has interesting points that could start an interesting discussion in its own thread. I see you do have a separate comment thread about it. So that's all good and fair.
But in this comment thread, you are completely missing my point! The OP has a very specific question that many HN readers care about. The question is complex and there aren't any easy answers for the question. My point is that the OP does not deserve shallow dismissals. Heck, no post deserves shallow dismissals. If a post is so bad that it should not be on HN, flag it and move on!
So my point is not to defend any definition or any particular school of thought or any particular view of AI. My point is to defend the OP from shallow dismissals. I am seeing these shallow dismissals more and more often these days and it makes reading HN comments a chore sometimes.
Your first paragraph: This comment is such a shallow dismissal of a good post that brings up a genuine and legally complex question that many readers of HN care about.
My first thought when looking at this thread was: I wonder if someone will try to claim their robot is a man and that it has been created. What might that imply?
> My first thought when looking at this thread was: I wonder if someone will try to claim their robot is a man and that it has been created. What might that imply?
It implies that they are wrong, and raises no interesting legal or philosophical questions.
Come back in a couple decades and we can check if we're getting closer.
A tangent to pondering the sci-fi future isn't entirely unwarranted, but it should be presented as a hypothetical and not as if it's a practical barrier to OP's question. "What if some day an AI approaches being human?" or something.
On the other hand if the meaning was supposed to be about human assistance, it would help to specify that and also talk about what kind of assistance might present meaningful trouble.
Or maybe they meant something else too. Such a wide breadth of topics being gestured at with only two words is not a good way to get a point across.
I disagree. I think the brevity was warranted and beneficial to the message. I think it is easy to link the logic and thus contributing to the conversation in a meaningful way has a lower barrier for entry.
I don't think attacking people for asking questions is contributing anything at all however.
Your response to my immensely simplified question with "they are wrong" fails to acknowledge a potentially real problem. A problem where too late is immediately followed by a successful attempt.
I see a lot of this today, much more so on HN lately too. I see people failing to be creative and resorting to some kind of "pics or it didn't happen" stance.
The idea that an AI that might be pushed through a legal challenge related to the constitution isn't far fetched in the slightest. It is guaranteed to occur. Not preparing for it is expected and while I love the feeling I get every time I predict the obvious but I would rather it stop occurring. It's short lived and the consequences have been growing.
You think AI is 20 years off. I happen to know for a fact it is already here.
Out of the entire thread, it was the only question I found that was worth reading. Pity people had to go and take issue with it instead of engaging properly and as the guidelines suggest.
These topics don't get much time before whatever force is at play flags them out of view.
Perhaps humans are well-defined, but are the OP's requirements so well defined? If I train a chimpanzee to complete `foo = "` with `bar"`, is that in the spirit of the OP's wishes?
> Perhaps humans are well-defined, but are the OP's requirements so well defined?
And that would be a good and insightful question and make an interesting discussion. Posting a two word comment like "Define human." without substantiating it as if the two words are supposed to communicate something very clever is not! It is lazy and presumptuous.
>>Their initial response was not lazy. Yes it was, it didn't consider what could have been meant and instead of asking they presumed the worse and attacked. Yes the initial comment was short, but also a very valid question even if it was lazy as well. If one wants to critisise, it should not be done by doing the same as what the criticism is about...in my opinion of course
They didn't presume the worst. They called it a bad comment because it's a fast dismissal that also basically forces you to presume to get any meaning from it. The two words reference a handful of arguments, specify none, and don't make a case for anything.
Not wanting to play "guess the deeper argument" is not laziness. And they wrote a perfectly reasonable length response to get across their entire point, which is also not lazy.
