But that’s my point, not everyone agrees with that assessment.
Well people can’t even agree on who won the last election or even if the world is round, so I can only speak to my point of view on things.
The problem is there’s things like code completers, that predate AI, and no one ever had a problem with those even though presumably they were also taking work from other people. So how much AI can be used before AI becomes unacceptable. You can set the bar at zero, but then you start getting problems of defining what even constitutes AI.
To me it’s very clear that the heart of the problem is not in “AI” or “machine learning” itself, but the way that almost all of the large AI models have been trained on work which has been scraped from other people without even so much as basic consent–to say little about licenses or payment. Consent is pretty massively important factor here. After all, I think most of us can agree on the fact that consent is the difference between “borrowing” and “theft”, the difference between “sex” and “rape”, and the difference between “employment” and “slavery”.
Is it possible to make an ethical AI?
Of course it is. But I feel that it would require an AI that was developed in a non-exploitative way, trained on data that has been legitimately acquired, licensed, public domain, cc-0, or otherwise “fair use”. Almost nobody is doing that, to my knowledge. Maybe someone in the open source world is working on it, and if so, kudos to them, but certainly none of the big AI corporations are.
So I agree there is a nuanced discussion to be had, but most of the time we are not talking about simple, small code completion tasks (like asking your IDE to create an empty definition of a method in the .cpp file or whatever). We are generally talking about people using large model AI systems to generate the actual “business logic” of a program, seemingly out of thin air (as long as you pay no attention to the man behind the curtain).
Part of having a real discussion is opening our eyes to the darker side of the AI industry and acknowledging the fact that the intellectual labor of working people and the creative class are being exploited at a truly unprecedented scale.
At any rate, I’m more than happy to have the conversation, even if I don’t have infinite time to dedicate to it.
Well people can’t even agree on who won the last election or even if the world is round, so I can only speak to my point of view on things.
I don’t think these are the best examples to use for your case here, giving both touch on matters of fact that are only questioned by fringe conspiracy theorists that the rest of the world regards as absolutely crazy, without any basis in reality. Yes, people do passionately believe them, but that doesn’t make them anyore true. It’s like trotting out the conservative chestnuts that evolution is just a theory, or that anthropogenic climate change hasn’t been the consensus position amongst scientists and framing it as a quack theory that some evil, socialist scientists have politicized because they hate US oil barons making money.
That aside, any serious discussion of AI’s inevitability needs to involve a feasible roadmap to making it sustainable at a material level. I won’t fully discard the possibility, as there’s no telling what the future may hold, but I haven’t seen any indication that there is a viable way to make these systems run with performance comparable to what they currently offer, without requiring several planets’ worth of water, hardware and power capacity. They can only do their “move fast and break things” schtick for so long before people get sick of it, and you’re already seeing people sour on data centers, as well as AI more generally.
The idea that AI will always be here, in something approaching its current state, now that we’ve invented it is just groundless, in my opinion. Yes, local LLMs will continue to exist, but they will have trade offs that I don’t see being palatable for the broader market. Using AI to make a quick meme based on a prompt doesn’t have the same draw when it takes 40 minutes to finish what the current money pit versions of AI will do in seconds.
I think it’s fair to assume AI will be around in some capacity, but will likely be far different from what we currently have, and restricted to domains where it actually makes sense to use, like some medical applications for analyzing patient imaging to suggests issues that humans might overlook. As companies are currently learning, though, the math just doesn’t work out on trying to replace human workers wholesale, and this is while the price still doesn’t accurately reflect the cost of running these models as services.
Given all this, plus your remarks on the ethical side of the training material, it just doesn’t make any sense to discuss the inevitability of AI existing in some capacity in the future as a reason not to offer blanket opposition to the tech as it currently exists. None of these companies can currently turn a profit just on the basis of their hardware and energy costs, so how likely is it they could offer reasonable compensation for training materials without this price becoming even more unreasonable?
I think drastically reducing these costs and ironing out the wrinkles should have been done before they ever rolled these systems out to the general public. Now, they’re up against a wall, trying to find a way to do so before the backlash becomes so severe, they can no longer find steady streams of investors willing to sink money in an increasingly toxic product.
Well people can’t even agree on who won the last election or even if the world is round, so I can only speak to my point of view on things.
To me it’s very clear that the heart of the problem is not in “AI” or “machine learning” itself, but the way that almost all of the large AI models have been trained on work which has been scraped from other people without even so much as basic consent–to say little about licenses or payment. Consent is pretty massively important factor here. After all, I think most of us can agree on the fact that consent is the difference between “borrowing” and “theft”, the difference between “sex” and “rape”, and the difference between “employment” and “slavery”.
Is it possible to make an ethical AI?
Of course it is. But I feel that it would require an AI that was developed in a non-exploitative way, trained on data that has been legitimately acquired, licensed, public domain, cc-0, or otherwise “fair use”. Almost nobody is doing that, to my knowledge. Maybe someone in the open source world is working on it, and if so, kudos to them, but certainly none of the big AI corporations are.
As for where we draw the line of what is or isn’t OK, in the US at least, “fair use” law is the mechanism that we have historically used to determine which particular unauthorized uses of other people’s copyrighted work are OK. And there are many factors that are considered for determining whether some kind of use is or isn’t fair.
So I agree there is a nuanced discussion to be had, but most of the time we are not talking about simple, small code completion tasks (like asking your IDE to create an empty definition of a method in the .cpp file or whatever). We are generally talking about people using large model AI systems to generate the actual “business logic” of a program, seemingly out of thin air (as long as you pay no attention to the man behind the curtain).
Part of having a real discussion is opening our eyes to the darker side of the AI industry and acknowledging the fact that the intellectual labor of working people and the creative class are being exploited at a truly unprecedented scale.
At any rate, I’m more than happy to have the conversation, even if I don’t have infinite time to dedicate to it.
I don’t think these are the best examples to use for your case here, giving both touch on matters of fact that are only questioned by fringe conspiracy theorists that the rest of the world regards as absolutely crazy, without any basis in reality. Yes, people do passionately believe them, but that doesn’t make them anyore true. It’s like trotting out the conservative chestnuts that evolution is just a theory, or that anthropogenic climate change hasn’t been the consensus position amongst scientists and framing it as a quack theory that some evil, socialist scientists have politicized because they hate US oil barons making money.
That aside, any serious discussion of AI’s inevitability needs to involve a feasible roadmap to making it sustainable at a material level. I won’t fully discard the possibility, as there’s no telling what the future may hold, but I haven’t seen any indication that there is a viable way to make these systems run with performance comparable to what they currently offer, without requiring several planets’ worth of water, hardware and power capacity. They can only do their “move fast and break things” schtick for so long before people get sick of it, and you’re already seeing people sour on data centers, as well as AI more generally.
The idea that AI will always be here, in something approaching its current state, now that we’ve invented it is just groundless, in my opinion. Yes, local LLMs will continue to exist, but they will have trade offs that I don’t see being palatable for the broader market. Using AI to make a quick meme based on a prompt doesn’t have the same draw when it takes 40 minutes to finish what the current money pit versions of AI will do in seconds.
I think it’s fair to assume AI will be around in some capacity, but will likely be far different from what we currently have, and restricted to domains where it actually makes sense to use, like some medical applications for analyzing patient imaging to suggests issues that humans might overlook. As companies are currently learning, though, the math just doesn’t work out on trying to replace human workers wholesale, and this is while the price still doesn’t accurately reflect the cost of running these models as services.
Given all this, plus your remarks on the ethical side of the training material, it just doesn’t make any sense to discuss the inevitability of AI existing in some capacity in the future as a reason not to offer blanket opposition to the tech as it currently exists. None of these companies can currently turn a profit just on the basis of their hardware and energy costs, so how likely is it they could offer reasonable compensation for training materials without this price becoming even more unreasonable?
I think drastically reducing these costs and ironing out the wrinkles should have been done before they ever rolled these systems out to the general public. Now, they’re up against a wall, trying to find a way to do so before the backlash becomes so severe, they can no longer find steady streams of investors willing to sink money in an increasingly toxic product.