Comment The rationale for objecting to LLMs/genAI (Score 1) 34
Much of the present-day debate regarding the use of LLMs and generative AI centers around topics such as necessity, accuracy, intellectual property rights, utility, efficiency, economics, worker protections, environmental impact, and future developments. But very little, it seems, is focused on what I think is really at stake, which is the centralization of authoritative truth.
If we regard such models and algorithms as "tools," then yes, there are advantages as well as disadvantages. We can discuss the benefits in productivity/efficiency/knowledge synthesis/discovery as much as we can discuss its impact on the labor market. We could also add in the context of where the training data came from, and whether the originators of such data possess rights to its use in this manner. We could talk at length about how data centers impact the environment in which they are built as well as the energy demands they make. We could endlessly speculate on various predictions for this technology as it might impact the human civilization long-term.
But what I would like to do is make a simpler statement, which is that at its core, these models--and in particular, the way they are being commodified and therefore utilized--represents a fundamental regression of the democratization of human knowledge. Some may say that, by assembling such vast quantities of information in this manner and then making it accessible to the world through the internet, we are improving access. After all, people who are not artists are using it to generate "art"; people who are not programmers are using it to "vibe code" computer applications; and in general, people who are not previously taught in a domain of knowledge through traditional means are using it to appear to attain a certain degree of competency. This is a seriously flawed argument; one that does not become more persuasive if the LLMs become more accurate, more knowledgable, or more capable.
What I mean by "democratization" is not simply about access to knowledge. It is about who controls that access, who curates it, who says it is the truth, who is accountable for the consequences of its use, and who teaches the critical thinking skills that facilitate its interpretation. In all these respects, the entities who have created and commodified these models are failing miserably, and if we look at their behavior, all of the evidence very clearly points to sinister motivations--that is, the failure is intentional. These people do not want you to think and reason and learn for yourselves, because that threatens their ability to sell that capability to you, and more importantly, to be the ultimate arbiter of truth.
It's a red herring to argue that individual humans are more fallible in their judgment, less objective, less knowledgeable in scope; thus are more prone to believing lies. The accuracy argument is misdirection. The point is, if we don't have the capability to interrogate and question, if we leave that to the machine, who is pulling the levers on that machine? And in a rather frighteningly perverse way, it may actually be preferable to have a human in control of that, as megalomanical, authoritarian, and evil as they may be, than having the machine in control. But this is my point--we shouldn't be letting this kind of centralization of power to occur in the first place. I don't want a dictatorship of knowledge, whether or not an oligarch trillionaire or the machine itself is in command of it.
So yes, I object to this technology, in as much as I object to, say, making nuclear weapons. People can point to "positive" examples of the technology--we've heard the arguments that these weapons keep us safe through a policy of mutually assured destruction; or that the underlying physics have given us nuclear energy, therapeutic radiation for treating cancer, and all kinds of other knowledge about the universe we live in. But will any of that matter if those weapons are used? Now ask yourself who has the power to use them, and what their motivations might be. When faced with the evidence, should we not be similarly skeptical of LLMs/genAI?
