I was amused by “AI” when it took off in the winter of 2022-2023. My friends and I took turns generating comedic images, probing our imagination for the most incongruous prompts to see what humor could manifest. More than one year later, I’ve developed a distaste for generative technology, but more than that a sense of foreboding. I doubt that I have any new opinions here but I find it worth writing down anyway.

I’m generally optimistic about new technology, and I enjoy the advances made since I was a boy. Having my PC boot in a few seconds flat still produces the computational equivalent of a new-car-smell. Watching computations work at super speed at my job is incredible and awesome (duckdb is an achievement). I continually appreciate the speed of gigabit internet.

The progress made in the space of deep learning is monumental as well, and I laud the intellectuals pushing boundaries here. But with everything else, it seems, the grasping hands of profiteers corrupt the space, and I don’t think we have the right social structures to integrate well with generative tech. Much of my opposition comes from the severing of epistemological heuristics we’ve relied on in society, and the need for new ones. Other opposition comes from concerns of labor and art. Ultimately my judgement is that the benefits of generative tech do not outweigh the drawbacks.

Knowing things⌗

Perhaps my greatest fear is the widespread supplantation of trust in knowledge; or more specifically, a weakening of our foundation of how we know things, our epistemology. I probably don’t have to, but I’ll link the rat penis research AI controversy. When we’ve allowed artificial knowledge into the places supposed to be dedicated to human knowledge, I think that’s a problem.

None can research all things with sufficient depth, so there are areas we have to delegate trust to others. The problem is – how can we trust others now, if we don’t even know if what they produce is genuinely a product of their own thought?

Regardless of how well generative technologies operate, their mere existence sows mistrust in other people. At best, generative technologies exceed the capabilities of the person using it giving anyone an unearned air of expertise. While the knowledge they “produce” may be correct, they are not a part of the equation any longer – why would anyone trust or confer any value to anything they say, when everyone has the same tools to create the same knowledge? Knowledge-bearers are made completely fungible.

More likely, generative technology produces poor and incorrect output, but the mass adoption of it makes it increasingly difficult to find good and genuine knowledge, and casts doubt on the output of your abilities; was it you, or was it produced by this flawed utility? How can we know? Worse yet, if you are supposed to be an expert in your field, how many others are there who can judge this? In either circumstance, the esteem that knowledge-bearers once held is eroded and hidden among noise, their legitimacy decimated.

Video generation has gotten to the point where historical document is now questionable. Before generative technology was a thing this was posted to Reddit. It shows a gaggle of children ogling a newfangled thing called a camera, as some passersby obliviously go about their day. It has the same sort of aimlessness that generative videos often produce, and in viewing a single frame for too long one might begin to identify false positives of generative hallucination due to artifacts from the overly compressed format and limitations of the clearly old video technology. If you didn’t know that this pre-dated generative tech, how certain would you be that this was a historical document?

I believe a trend of anti-intellectualism and mistrust in institutions of knowledge will accelerate with generative technologies.

Learning things⌗

It shouldn’t be controversial to say that generative technology is disrupting education right now, and not in a good way. Go on /r/Teachers and witness the debates being held around how best to incorporate generative technology in the classroom – or else ban it. Hear the distress of teachers in Australia, saying that they "[suspect] plagiarism for about 40% of their cohort this year (2024)".

You might say, generative technology is used in the workplace, why not allow students to become accustomed to using it now? You might say, the calculator is the same idea and you use a calculator at work, don’t you?

I say, we’ve missed the whole point of education. School and universities should never have become a hand-out for businesses to receive trained labor for free. The point of a higher-education degree should not be a conversion to future profits. The classic joke is underwater basket-weaving, but in my view the purpose of higher education should not about making money or your future prospects for the type of servitude you will submit to businesses! It should be to learn, for learning’s sake. If you want to learn underwater basket-weaving, then you should have that opportunity. If businesses want trained labor they should pay for it, either by funding your education in a specific field, funding education in general, or doing their own training. There is no culture of teaching in corporations, all knowledge is expected to be had before you walk in the door (I am too young to know if there ever was).

The act of learning is a foundationally human activity, and a technology that reduces the need for this reduces our humanity and potential. Yes I was allowed to use a calculator in university, but they weren’t testing for arithmetic in calculus class, they were testing for our understanding of derivatives, integrals, and limits. Obviously we weren’t allowed to use Wolfram Alpha during our tests despite its availability. I’ve always been poor at arithmetic, but while calculators aren’t helping me get better in that regard, I do understand how it works because I was taught how to do it without one.

But I’m not sure that lower education students will, if they conceive of generative tech as an all-knowing oracle that they can use to submit math problems to (and you know they’re doing it). From the perspective of a lower-education student who can apparently get all answers to any question without effort, and who does not have the discernment to distinguish output quality – why bother learning anything? I would hope that the innate curiosity wins out but now that we’ve converted schools to capitalist training programs there is zero incentive to try hard especially if there won’t be any value returned to you at the end.

Working on things⌗

I’m no economist and poorly read in these areas so obviously take whatever I say with appropriate skepticism.

From the perspective of the ownership class, the most efficient organization of production is the one which minimizes the cost of labor – or perhaps eliminates it outright. It is a machine so effective that the owners can operate it themselves, producing all of the value with none of the cost of labor. Rarely do we witness such a machine, but it is the logical conclusion of efficiency in business.

I predict that generative technologies will only serve to diminish the value returned to labor and funnel more value to ownership.

Companies will write platitudes like “We will never replace employees with AI! We use AI to help our employees serve our customers better”. But replacement should not be the only concern, and not even the first.

If generative technology is better than you, then what separates you from anyone else? Why should companies pay you more? If generative technology is flawed, how can a business tell you’re not one of the ones using the flawed tech? Why would they pay you more when there is such risk involved? The very existence of the technology excuses erosion of the value returned to the laborer.

The common rebuttal is that the world did not end from efficiencies achieved in the past, but rather innovation opened up other opportunities for labor to retrieve value. Instead of toiling in fields, labor moved to work in factories; instead of factories, labor moved to work in offices.

The efficiencies and innovations sought previously allowed us to transition from using our bodies for labor to using our minds, different applications of our human adaptations to produce value for others. But I state that the difference now is that the efficiencies sought by adopters of generative technologies seek to erase even the use of our minds for labor. And not only labor, but art.

There are a few things that we cherish as a higher-order intelligence on this planet (or ought to). A record of historical tradition, and dissemination of history and knowledge. A pursuit of creation and ideas, and finding emotional connections to others through these. We see combinations of these in art, in science, in storytelling, in history, and among teachers and students.

One wonders why the facets of human life that make it special and unique are also the ones that we’ve allowed to be compensated so little.

Nevertheless, the way generative technologies are used today by the money-grubbers target these crucial and quintessentially human pursuits; it’s no longer a question of whether people will find other applications for their labor, but whether the faculties that we exercise to find meaning in our lives will be taken from us and converted into cash for the ownership class.

The images above were generated with Bing Image Generation technology ca. November 2023.