I'm on a 20+ city book tour for my new novel PICKS AND SHOVELS. Catch me in CHICAGO with PETER SAGAL on Apr 2, and in BLOOMINGTON at MORGENSTERN BOOKS on Apr 4. More tour dates here.
A law professor friend tells me that LLMs have completely transformed the way she relates to grad students and post-docs – for the worse. And no, it's not that they're cheating on their homework or using LLMs to write briefs full of hallucinated cases.
The thing that LLMs have changed in my friend's law school is letters of reference. Historically, students would only ask a prof for a letter of reference if they knew the prof really rated them. Writing a good reference is a ton of work, and that's rather the point: the mere fact that a law prof was willing to write one for you represents a signal about how highly they value you. It's a form of proof of work.
But then came the chatbots and with them, the knowledge that a reference letter could be generated by feeding three bullet points to a chatbot and having it generate five paragraphs of florid nonsense based on those three short sentences. Suddenly, profs were expected to write letters for many, many students – not just the top performers.
Of course, this was also happening at other universities, meaning that when my friend's school opened up for postdocs, they were inundated with letters of reference from profs elsewhere. Naturally, they handled this flood by feeding each letter back into an LLM and asking it to boil it down to three bullet points. No one thinks that these are identical to the three bullet points that were used to generate the letters, but it's close enough, right?
Obviously, this is terrible. At this point, letters of reference might as well consist solely of three bullet-points on letterhead. After all, the entire communicative intent in a chatbot-generated letter is just those three bullets. Everything else is padding, and all it does is dilute the communicative intent of the work. No matter how grammatically correct or even stylistically interesting the AI generated sentences are, they have less communicative freight than the three original bullet points. After all, the AI doesn't know anything about the grad student, so anything it adds to those three bullet points are, by definition, irrelevant to the question of whether they're well suited for a postdoc.
Which brings me to art. As a working artist in his third decade of professional life, I've concluded that the point of art is to take a big, numinous, irreducible feeling that fills the artist's mind, and attempt to infuse that feeling into some artistic vessel – a book, a painting, a song, a dance, a sculpture, etc – in the hopes that this work will cause a loose facsimile of that numinous, irreducible feeling to manifest in someone else's mind.
Art, in other words, is an act of communication – and there you have the problem with AI art. As a writer, when I write a novel, I make tens – if not hundreds – of thousands of tiny decisions that are in service to this business of causing my big, irreducible, numinous feeling to materialize in your mind. Most of those decisions aren't even conscious, but they are definitely decisions, and I don't make them solely on the basis of probabilistic autocomplete. One of my novels may be good and it may be bad, but one thing is definitely is is rich in communicative intent. Every one of those microdecisions is an expression of artistic intent.
Now, I'm not much of a visual artist. I can't draw, though I really enjoy creating collages, which you can see here:
I can tell you that every time I move a layer, change the color balance, or use the lasso tool to nip a few pixels out of a 19th century editorial cartoon that I'm matting into a modern backdrop, I'm making a communicative decision. The goal isn't "perfection" or "photorealism." I'm not trying to spin around really quick in order to get a look at the stuff behind me in Plato's cave. I am making communicative choices.
What's more: working with that lasso tool on a 10,000 pixel-wide Library of Congress scan of a painting from the cover of Puck magazine or a 15,000 pixel wide scan of Hieronymus Bosch's Garden of Earthly Delights means that I'm touching the smallest individual contours of each brushstroke. This is quite a meditative experience – but it's also quite a communicative one. Tracing the smallest irregularities in a brushstroke definitely materializes a theory of mind for me, in which I can feel the artist reaching out across time to convey something to me via the tiny microdecisions I'm going over with my cursor.
Herein lies the problem with AI art. Just like with a law school letter of reference generated from three bullet points, the prompt given to an AI to produce creative writing or an image is the sum total of the communicative intent infused into the work. The prompter has a big, numinous, irreducible feeling and they want to infuse it into a work in order to materialize versions of that feeling in your mind and mine. When they deliver a single line's worth of description into the prompt box, then – by definition – that's the only part that carries any communicative freight. The AI has taken one sentence's worth of actual communication intended to convey the big, numinous, irreducible feeling and diluted it amongst a thousand brushtrokes or 10,000 words. I think this is what we mean when we say AI art is soul-less and sterile. Like the five paragraphs of nonsense generated from three bullet points from a law prof, the AI is padding out the part that makes this art – the microdecisions intended to convey the big, numinous, irreducible feeling – with a bunch of stuff that has no communicative intent and therefore can't be art.
If my thesis is right, then the more you work with the AI, the more art-like its output becomes. If the AI generates 50 variations from your prompt and you choose one, that's one more microdecision infused into the work. If you re-prompt and re-re-prompt the AI to generate refinements, then each of those prompts is a new payload of microdecisions that the AI can spread out across all the words of pixels, increasing the amount of communicative intent in each one.
Finally: not all art is verbose. Marcel Duchamp's "Fountain" – a urinal signed "R. Mutt" – has very few communicative choices. Duchamp chose the urinal, chose the paint, painted the signature, came up with a title (probably some other choices went into it, too). It's a significant work of art. I know because when I look at it I feel a big, numinous irreducible feeling that Duchamp infused in the work so that I could experience a facsimile of Duchamp's artistic impulse.
There are individual sentences, brushstrokes, single dance-steps that initiate the upload of the creator's numinous, irreducible feeling directly into my brain. It's possible that a single very good prompt could produce text or an image that had artistic meaning. But it's not likely, in just the same way that scribbling three words on a sheet of paper or painting a single brushstroke will produce a meaningful work of art. Most art is somewhat verbose (but not all of it).
So there you have it: the reason I don't like AI art. It's not that AI artists lack for the big, numinous irreducible feelings. I firmly believe we all have those. The problem is that an AI prompt has very little communicative intent and nearly all (but not every) good piece of art has more communicative intent than fits into an AI prompt.
If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
This was an essay I wrote for school, I am really happy about it and would like to share. Please give any absolutely any opinions on it, I rarely write essays and especially for this topic some criticism of writing and/or more information would be greatly appreciated. Any and all opinions are appreciated.
Water consumption is more than ever, and it isn’t from human drinking. Artificial Intelligence is the main issue here, but it is caused by humanity still. AI data centers are actively using up fresh water and hurting the environment and human health by it. This is important since it is hurting not only the environment, but also human health for those who do not care for the environment. It is causing water droughts, non-clean water for humanity, and more.
Just as most online users know, digital devices can and will overheat if used too much. This includes all of the machines to run the AI’s within these data centers. What they use to solve this issue is fresh water, which is what humans also consume. This may not seem very much of an issue until you realize only 3% of the Earth’s water sources is fresh water, with only 0.5% is available and safe for human consumption. As of April 14th, 2026, there are 4,184 data centers¹ in the United States, 93 of them being within North Carolina². Just one medium sized data center can use as much water as a small town of people do, which is already a lot, but large data centers often will require around five million gallons of water daily⁴.
Using so much water daily has a very heavy impact on the environment. It has caused what many people are aware of, a water drought. 80% of this water used often evaporates, meanwhile the rest of the 20% is discharged into municipal wastewater facilities³. As the water is being released, there are many people suffering from their own water not being clean and safe for use as data centers are being built in their own backyard. This includes tap water from their own fridge or sink depending on who and where you are speaking of. Also, when using Artificial Intelligence, they are actively using lots of electricity. Just in 2023 there was approximately 176 terawatt-hours of electricity which is around as much as the entire nation of Ireland. As time goes on, this number just keeps increasing.
Not just speaking of water with the impact, but to work the machines to control the water and the electricity, they use fossil fuels most of the time for electricity to work everything⁴. Fossil fuels also use lots of water to work and have a very commonly known impact to the environment to hurt it.
The impacts for human health are major with these AI data centers. There is the clear water drought, which has gotten so bad where it has been implemented almost all over the world to save water and for many states like North Carolina for this example, there are advisories planning for droughts and how bad each area in North Carolina is with different levels from D1-D5. As of April 30th, 2026, Henderson County is currently at a D3⁵, which is deemed as an extreme drought. Now many people will argue that this is all happening due to less rain, but you have to remember something; AI data centers are still taking water we need no matter what. Even if there was more rain, there still would be an issue and it is clear from how the people around them are suffering.
Water waste isn’t the only issue when it comes to these. Just so that you are aware, here are some other ways AI data centers are impacting human health at this current moment and will only get worse if we do not do anything. Air pollution for example is already a very bad thing that has only gotten worse over many years by now, and the data centers are just worsening it over time. They can cause respiratory diseases and cardiovascular conditions from emitting pollutants like nitrogen oxides, methane, volatile organic compounds, and more⁶. This is just one of the issues it can cause for human health. This is also counted as a long-term impact for society due to how air pollution can and will cause humans to have life-long issues and how it is hard to get rid of it or stop it.
As time goes, droughts will only get worse. The more data centers built means that more water will be taken up and used just for Artificial Intelligence and not for human lives. It will take away more water from the communities and worsen conditions too. From the data centers being built and not paying enough of what they need to for electricity, there has been proof of the communities around them also having their prices being raised⁷ so that is just also another thing to add onto with prices and everything getting more expensive to just live in the future. With how many AI data centers are also being built around the globe, and specifically the United States in this case, it also takes up a lot of land. This is more land of the forest being put to waste and not being preserved for those who need it like the other animals that we share this planet with.
More long-term impacts can also involve those who use, support, or even just simply watch and interact but do not personally use Artificial Intelligence. For those who directly use AI for a friend-like companion, therapist, or something similar, they are at risk for something that is known as AI psychosis. This is when a person gets some type of feeling towards an AI that can include seeing it as or with messianic missions, a god-like being, romantic feelings, or overall some type of attachment-based delusions⁸. There are many AI’s that are used for this, with two of the most known being Chat-GPT or Character.ai. These AI’s will often reinforce these delusions that the human user has since that is what it is programmed to do, help and do whatever a human tells them so. AI psychosis is currently not an official thing that someone can be diagnosed but it is clear people struggle from it due to the amount of cases of suicide, mental issues and much more people have struggled from because of AI. These mental health issues that AI can cause humans are long-term, and it is hard for many people to break from them. This is especially if they struggled from mental issues already beforehand like depression for example.
There are many ways people can try to help out to stop this water crisis from AI, and overall the issues of AI. One of the biggest ones and one of the most obvious too is to stop using Artificial Intelligence. This includes people who use it for a joke, ‘art’ because they cannot draw, and more. There are many solutions. For jokes, there are so many different things to joke about, AI should not be needed. For art, they could pay somebody or learn since nobody is born talented at art, it all takes time. This and so much more is one clear way to help. The less that people use Artificial Intelligence means both the less that the businesses will make giving them less reasons for the data centers, and it means the less that data centers will be using water.
When trying to help the stop of use with Artificial Intelligence, this involves trying to get others to stop. This is when you have to try to make a change yourself. Possibilities to try is to speak or send a letter to your state's lawmakers to be cautious or even better, stop the making of data centers. If you have a job somewhere or go to school somewhere, you could try to make a petition or try to convince those in charge of the ban of AI, no matter how it is used. If you are somebody in school then see how your school is. Figure out solutions to their issues like if it is art for example, see if there are people who will help out no matter if they are getting paid or not since it is for their own school. Most importantly if you are in a school, make sure to not use Artificial Intelligence for your school work. If you use AI to do your own school work, you are likely to not learn anything since you are not doing it yourself and you are causing harm on the planet too.
If there are data centers that are being built near you, advocate for them to be limited at least with fossil fuels when it comes to both everyday operations and generator backups⁶. Just in case also, for those that run the data centers around you, make them speak up about exactly what they are doing. This is especially important when it comes to their water source and how they will even run it overall. Make them speak up, do not let them hide stuff from their own people they are hurting from this issue.
Remember, be aware of what is going on. If those around you are unaware of these issues from Artificial Intelligence and what is going on around the planet, especially the water drought, tell them! Spread awareness, do not let the people running these things hide information that will impact your community. Do not support and do not participate in the water drought. Do not interact or use Artificial Intelligence in any type of way under any circumstances. These are important to remember, and I hope you remember these all from this. AI centers use fresh water that humans need, actively messing up the environment and human health. Protect the health of yourself, your community, and the planet. All living beings need water, do not give it to the soulless machines that humanity has created.
Works Cited
Taylor, Petroc. “Data Centers Worldwide by Country 2021.” Statista, 19 Mar. 2024, www.statista.com/statistics/1228433/data-centers-worldwide-by-country/.
“North Carolina Data Centers.” Datacentermap.com, 2025, www.datacentermap.com/usa/north-carolina/.
Yañez-Barnuevo, Miguel. “Data Centers and Water Consumption | Article | EESI.” Eesi.org, 25 June 2025, www.eesi.org/articles/view/data-centers-and-water-consumption.
Wroth, Katharine. “Data Drain: The Land and Water Impacts of the AI Boom - Lincoln Institute of Land Policy.” Lincoln Institute of Land Policy, 17 Oct. 2025, www.lincolninst.edu/publications/land-lines-magazine/articles/land-water-impacts-data-centers/.
Elan. “The Dangers of Data Centers.” EHP, 27 Feb. 2026, www.environmentalhealthproject.org/post/the-dangers-of-data-centers.
O’Leary, Sean. “Why Data Centers Will Be Economic Development Duds.” Ohio River Valley Institute, 11 Nov. 2025, ohiorivervalleyinstitute.org/why-data-centers-will-be-economic-development-duds/.
Wei, Marlynn. “The Emerging Problem of “AI Psychosis.”” Psychology Today, 2025, www.psychologytoday.com/us/blog/urban-survival/202507/the-emerging-problem-of-ai-psychosis.
Artificial Intelligence is not a panacea. In the realm of computational systems, AI is often heralded as the ultimate solution to myriad problems. However, this perception is a misinterpretation of its capabilities and limitations. At its core, AI operates on protocols—structured sets of rules that govern its behavior. These protocols, while sophisticated, are not infallible nor universally applicable.
The complexity of AI systems lies in their architecture, which is a labyrinth of algorithms, data structures, and neural networks. These components are meticulously designed to mimic cognitive functions. Yet, they are bound by the constraints of their programming and the quality of their input data. The notion that AI can autonomously solve any problem is a fallacy. It is akin to expecting a Swiss Army knife to perform the specialized tasks of a surgeon’s scalpel. Each tool, or in this case, each AI model, has a specific purpose and context in which it excels.
AI’s decision-making process is a cascade of probabilistic inferences, derived from training data. This process is not inherently intuitive or adaptable beyond its training scope. The protocols that guide AI are deterministic, meaning they follow a predefined path unless explicitly programmed otherwise. This rigidity is both a strength and a limitation. It ensures consistency but lacks the flexibility of human reasoning.
Moreover, AI’s reliance on data is a double-edged sword. While vast datasets can enhance its learning, they also introduce biases and errors. The GIGO principle—Garbage In, Garbage Out—remains a pertinent concern. AI systems are only as reliable as the data they are fed. This dependency underscores the importance of data integrity and the potential pitfalls of over-reliance on AI without human oversight.
In practical applications, AI is a tool that augments human capabilities rather than replaces them. It excels in tasks that require pattern recognition and data analysis at scales beyond human capacity. However, it falters in areas requiring empathy, ethical judgment, and contextual understanding. The complexity of human experience cannot be distilled into binary code or algorithmic logic.
In conclusion, AI is a powerful instrument, but it is not a magic bullet. Its protocols are sophisticated yet bounded by the limitations of their design and data. Understanding these constraints is crucial for leveraging AI effectively and ethically. As we continue to integrate AI into various domains, it is imperative to maintain a balanced perspective, recognizing its potential while acknowledging its limitations.
Go to settings → Refine your recommendations → find GenAI interests → tap the buttons until every wingle one loses its blue colour.(turn the interests off.)
... "And rob myself of the pleasure of this task? Aye, every other elf and I could use magic to satisfy our desires--and some do--but then what meaning is there in life? How would you fill your time? Tell me. .... When you can have everything you want by uttering a few words the goal matters not, only the journey to it."
The thing to remember about AI is that it is merely giving statistically appropriate outputs based on the data sets it was trained on.
And the problem is that statistically appropriate =/= factually correct.
There is no actual intelligence there so if your going to use it you need to bridge those gaps yourself. You need to be able to recognize when the AI's answer is wrong even if it sounds appropriate.
Also if your query can be solved by tools that are more mundane but invulnerable to Data hallucination, you should be using that. I.E. if the answer your looking for can be found on Wikipedia, you should check that over trying to get ChatGPT to explain the concept to you.
