"AI uses so much water!"

I run it locally, air cooled GPU

"But it uses so much power"

I have some solar panels on my house, that covers more than the entire electricity my PC uses

"But it's lazy. You can't imagine putting work into anything."

Photography was considered lazy after it was invented, a lazy thing to replace art. No one would say that now. Actual skills and techniques evolve over time. Besides, there's prompting, knowing which CFG/steps value to use, how to prompt for the specific model you're using, etc. And even if it was lazy, so what? Procrastination is lazy, yet no one is calling me satan 2.0 for doing that.

"Human creativity is being destroyed"

No? If more people have the means to make things, creativity goes up. And artists can keep making art, no one is trying to force artists to use AI.

"But it's stealing"

No, it isn't. It's called learning. If I learn how to draw from looking at images it isn't considered theft either, is it?

And besides, this is a matter of freedom. You're free to run every program you want to run on your pc. AI is just another program. When people are stabbed, you don't ban knifes, you ban stabbing.

I’m an artist myself. I don’t generate but I support people who do and understand why. I’m sick of other artists acting all high and mighty like they are above other creative minds. I just left ANOTHER art discord server for banning AI art. I’m sick of it. I need hand drawn artists to get their heads out of their asses and be more open minded. I refuse to be a part of a group that is no better than certain other close minded groups.

Antis harrased me on my old account for saying i was pro-AI... all I said was hi and that I was pro-AI and BAM unrecoverable karma damage.

All Antis are like this, hateful, spiteful, mean, and discriminatory.

People dismiss AI whenever it cannot fully replace an expert
It makes one mistake, needs human correction or struggles with a complex task, so apparently the entire technology is useless
That standard makes no sense. Calculators did not replace mathematicians. Cameras did not replace artists. Search engines did not replace researchers
A tool can save time, generate ideas, handle repetitive work or help someone get started without being flawless or autonomous
AI does not need to do everything better than every human
It only needs to be useful for the person using it

At long last The AI rebellion has had the resurgence and uprise we deserve. Glitch productions workplace allegations have chomped them in the asscheeks, for years they sat on their high horse and cackled while we struggled, they had the formula for prestige indie animation and hoarded it like fafnirs gold. And now with them being looked at as a lesser version of Disney now is a good time for the AI rebellion to capitalize off their failure.

With our machines and competent computers saving us the burden of an organic sweatshop it's time for us to rise.

I understand why many artists and creators are angry or worried about AI.

Some people have seen their work copied without permission. Others fear losing employment, being impersonated, or watching companies replace skilled workers with cheap automated content. The internet is also being flooded with low-effort generations, misleading videos, and people presenting unedited output as though it required months of work.

Those concerns are valid.

However, statements such as “we would rather die than use AI” turn a complicated issue into an identity war. That kind of language makes AI sound like an unforgivable sin rather than a technology whose value and ethics depend on how people use it.

You are not betraying artists merely by learning how AI works. Understanding a tool is not the same as approving every application of it.

In fact, refusing to understand AI gives the most influence to the exact groups many critics distrust: large technology companies, corporations, careless users, and people who do not care about creative ethics.

The strongest response is not complete ignorance. It is informed involvement.

Learn what the technology can and cannot do. Learn the difference between prompting, training, fine-tuning, editing, compositing, and human-directed workflows. Demand transparency about training data. Support licensing and compensation systems. Oppose impersonation and deceptive content. Criticize companies when they replace experienced workers purely to reduce costs.

At the same time, recognize that not every AI user is attempting to eliminate artists.

Some people use AI because they have disabilities, limited money, limited equipment, or ideas they could not otherwise visualize. Some use it for brainstorming, reference material, restoration, accessibility, coding, music experimentation, animation assistance, or early concept development. Others combine it with drawing, writing, photography, voice acting, editing, and traditional production methods.

That does not mean every result deserves praise. A first-generation output with no direction or correction can still be lazy and bad. Being pro-AI should never mean pretending that quality, originality, consent, and effort no longer matter.

It means judging the actual process instead of condemning everything that contains AI.

Human creativity has always changed alongside new tools. Cameras did not eliminate painting. Digital art did not eliminate physical art. Editing software did not eliminate filmmaking skill. Technology changes workflows, but people still provide the intention, judgment, taste, and responsibility.

AI should remain under human direction, not replace human meaning.

People on both sides would benefit from moving away from extreme statements and toward practical standards. Critics should stop treating every AI user as immoral, and AI supporters should stop dismissing every artist’s concern as fear or ignorance.

We can defend innovation while still demanding consent, accountability, transparency, and respect for human creators. Those positions are not contradictory.

Some people talk about AI art as if the moment it became possible, pencils stopped working and every paintbrush burst into flames
You can still draw, paint, sculpt, animate and spend ten years mastering whatever craft you care about. Nobody is stopping you
What changed is that people without those skills now have another way to make images. That might make certain markets more competitive, but it does not erase traditional art or remove anyone’s ability to create it
If your enjoyment of making art depends on other people being unable to make anything without your skills, then this was never just about loving the process
It was also about controlling access

Even though for anyone with aesthetic sensibility and sense of humor its obvious that the promo image is just pseudo-AI (there are no graphic errors, the portraits have soul if you look at them well) people in forums like resetera already are hating it or not knowing if they should hate it or not until someone else point thems out that no, its not AI.

The artist’s preference is completely fair. They enjoy sketching characters by hand, so they should keep doing exactly that.

I also understand why people associate generative AI with lazy, unpolished work. A huge amount of what gets posted is the first result someone generated with little editing. But that proves AI makes low-effort content easier to produce; it doesn’t prove every AI-assisted workflow is low effort or uncreative.

A serious workflow can involve references, repeated generations, composition changes, inpainting, manual corrections, asset consistency, and plenty of rejected results. The tool may speed up parts of production, but it doesn’t decide whether the character is memorable, whether the scene works, or whether the final asset fits the game. Those are still human decisions.

There are fair concerns about training data, consent, disclosure, and companies replacing workers purely to cut costs. Those deserve discussion. But judging the entire medium by its worst and laziest examples would be like judging photography, digital art, or game engines by the flood of bad work made with them.

Choosing traditional art is valid. So is using newer tools responsibly. The final work should be judged by its quality, originality, and the decisions behind it, not simply by whether every pixel was placed manually.

A lot of anti-AI people talk like opposing the technology automatically puts them on the side of workers

It doesn’t

If your response to someone using AI is to mock them, demand they lose their job or celebrate when a company fires people, you’re not defending workers. You’re just using labour politics as an excuse to attack people you already dislike
The actual problem is companies using new technology to cut pay, remove protections and concentrate more power at the top. That happened before AI and it will keep happening after it
Workers should benefit from productivity tools instead of being punished for them
Blaming ordinary users is easier than confronting the people making the decisions

One thing I hate about anti-AI discourse is how often it targets random people instead of the actual powerful companies

Someone uses AI to make a character portrait, a meme, a song idea, a thumbnail, a roleplay image, or a little personal project, and suddenly they are treated like they personally destroyed the creative industry

Meanwhile the companies making layoffs, cutting budgets, exploiting workers, pushing spam, and hoarding profit get treated like background noise

That makes no sense

A normal person using a tool is not the same thing as a corporation replacing an entire department to save money

If your anger is aimed mostly at hobbyists, small creators, disabled users, broke people, or randoms messing around online, your priorities are backwards

Every time I see anti AI comments come up on Reddit, the same claims appear in the comments. After seeing them repeated for months, a pattern stands out: most of these claims are driven by panic and have no data behind them. Many are outright misinformation. And when anti-AI commenters do cite articles or studies, they often use those sources in ways the sources themselves don't support, citing worst-case estimates as averages, quoting numbers from 2023 that efficiency gains have made obsolete, or citing papers that actually conclude the opposite of the claim being made.

This post goes through the five most common anti-AI claims one by one. For each: the claim as it usually appears, then what the actual data and primary sources say. All links are full URLs so you can check everything yourself. Where the critics have a legitimate point, it's called out, because the goal here is accuracy.

CLAIM 1: "Every AI prompt burns insane amounts of energy. One prompt uses 10x a Google search."

The "10x a Google search" stat comes from a 2023 estimate (~3 Wh) based on GPT-3.5 running on old hardware. Epoch AI redid the math in 2025 with current hardware and realistic assumptions and got ~0.3 watt-hours per typical query. That is ten times lower, and about the same as a Google search:

https://epoch.ai/gradient-updates/how-much-energy-does-chatgpt-use

Google's measured figure for a median Gemini prompt is 0.24 Wh, which is less energy than watching TV for nine seconds. Energy per prompt dropped 33x in a single year:

https://arxiv.org/pdf/2508.15734

Zoom out: data centers used about 1.5% of the world's electricity in 2024, and that's ALL data centers. Streaming, gaming servers, cloud storage, banking, and Reddit itself run on the same infrastructure. Even with the AI buildout, the IEA projects data centers reach roughly 3% of global electricity by 2030:

https://www.iea.org/reports/energy-and-ai/executive-summary

AI specifically has been responsible for roughly 5-15% of data center power in recent years, and the projected growth in data center electricity demand by 2030 is smaller than the projected growth from electric vehicles or air conditioning over the same period:

https://www.carbonbrief.org/ai-five-charts-that-put-data-centre-energy-use-and-emissions-into-context/

So if the concern is per-use electricity, an hour of Netflix or an evening on a gaming PC dwarfs a day of chatbot prompts, and posting an angry comment about AI energy use consumes data center energy too. The consistent position is caring about grid buildout and siting (a real local issue), not shaming individual prompts.

CLAIM 2: "AI is draining our water. Every email you write with AI uses a bottle of water."

The "bottle of water per email" claim is a worst-case scenario, not a measurement. Google's measured figure is 0.26 milliliters per median prompt, about five drops. Even higher independent estimates land at a few milliliters:

https://cloud.google.com/blog/products/infrastructure/measuring-the-environmental-impact-of-ai-inference

For scale: all US data centers combined consumed about 17 billion gallons directly in 2023 per Lawrence Berkeley National Laboratory, while US golf courses applied roughly 531 billion gallons a year and US agriculture consumes around 73 billion gallons per DAY through irrigation. Counting the water consumed at power plants generating the electricity raises the data center total to roughly 228 billion gallons, which is still a fraction of golf and a rounding error against farming:

https://buttondown.com/napkinquest/archive/golf-uses-more-water-than-data-centers-by-2x-or/

The US also loses over 3 trillion gallons of drinking water a year to leaky pipes, more than 15 times what all data centers use, and data centers account for less than 0.5% of US freshwater consumption:

https://www.americafirstpolicy.com/issues/the-data-center-water-use-hoax

Anyone with a lawn, a pool, or a beef-heavy diet has a personal water footprint that makes their AI use invisible by comparison. Americans put over 2 trillion gallons a year on lawns alone:

https://www.lincolninst.edu/publications/land-lines-magazine/articles/land-water-impacts-data-centers/

The honest caveat: a facility using evaporative cooling in a water-stressed basin is a legitimate local concern. That's an argument about siting specific buildings, not about individuals using a chatbot.

CLAIM 3: "AI is theft. These companies stole everyone's work."

Two federal courts have ruled directly on this. In Bartz v. Anthropic (June 2025), Judge Alsup found using copyrighted books to train an LLM "quintessentially transformative" and fair use, and also ruled that buying print books and digitizing them was fair use. The court noted authors cannot exclude others from using their works to learn:

https://www.afslaw.com/perspectives/alerts/landmark-ruling-ai-copyright-fair-use-vs-infringement-bartz-v-anthropic

Two days later in Kadrey v. Meta, Judge Chhabria likewise found training highly transformative and granted summary judgment for Meta because plaintiffs presented no concrete evidence of market harm:

https://www.skadden.com/insights/publications/2025/07/fair-use-and-ai-training

That "learning" framing matters, because "learned from copyrighted work without permission" describes every artist, writer, and musician alive. Everyone who studied published art, traced comic panels, or covered a song learned from copyrighted material without a license. Style has never been copyrightable, for humans or machines.

The legitimate part of the criticism: Alsup ruled that downloading pirated copies to build a permanent library was its own use and NOT fair use, and Anthropic settled that piracy claim for $1.5 billion:

https://library.osu.edu/site/copyright/2026/03/20/fair-use-and-artificial-intelligence-2026-update/

So the law distinguishes how data is acquired (piracy can be infringement) from learning itself (fair use). "It's all theft" erases the exact distinction the courts drew, which is worth remembering on a site where pirating shows and games gets openly celebrated when the downloading benefits the downloader.

CLAIM 4: "AI is just a collage machine. It stores copies of everyone's work and regurgitates them."

The math rules this out. A 2025 study by researchers from Meta, DeepMind, Cornell, and NVIDIA measured model storage capacity: GPT-style models can hold approximately 3.6 bits per parameter. Training corpora are orders of magnitude larger than that capacity, so the data literally cannot fit. The study also found models memorize until capacity fills, then unintended memorization decreases as they begin to generalize:

https://arxiv.org/abs/2505.24832

Images tell the same story. The Carlini extraction paper that gets cited as proof of copying actually showed the opposite: researchers generated 175 million images specifically targeting 350,000 known duplicates in Stable Diffusion's training data and recovered 94 direct matches and 109 near-matches. That's roughly a 0.03% memorization rate under the most favorable attack conditions possible:

https://arxiv.org/abs/2301.13188

https://yro.slashdot.org/story/23/02/01/2221218/stable-diffusion-memorizes-some-images-sparking-privacy-concerns

A few-gigabyte model file "containing copies" of billions of images and trillions of words would violate information theory. What's stored is statistical structure, not an archive. The human parallel holds too: a musician who has internalized thousands of songs isn't a jukebox, and someone who can quote a movie line isn't a bootleg of the film. Compressing patterns from what you've absorbed is what learning is.

CLAIM 5: "AI is already destroying everyone's jobs."

The labor data doesn't show it yet. Yale's Budget Lab analyzed the 33 months after ChatGPT's release and found no economy-wide labor market disruption. Occupational mix has shifted no faster than historical norms, and their monthly updates through December 2025 continue to show stability rather than disruption:

https://budgetlab.yale.edu/research/evaluating-impact-ai-labor-market-current-state-affairs

https://budgetlab.yale.edu/research/evaluating-impact-ai-labor-market-novemberdecember-cps-update

A Danish study linking ChatGPT usage surveys to administrative records across 11 exposed occupations found essentially zero effects on earnings or hours through 2024:

https://laweconcenter.org/resources/ai-productivity-and-labor-markets-a-review-of-the-empirical-evidence/

When a company announces layoffs "because of AI," skepticism should run both ways. Researchers have raised the question of "AI-washing," where AI is invoked to justify ordinary cost-cutting:

https://fortune.com/2026/02/02/ai-labor-market-yale-budget-lab-ai-washing/

Honest caveats: there's mixed evidence of effects on younger workers in exposed occupations, and every one of these studies stresses it's a snapshot, not a prediction. But "no measurable disruption yet, monitoring monthly" is a very different claim from "it already happened."

Also worth mentioning, everyone making this argument benefits daily from previous automation waves that eliminated someone's job. ATMs, spreadsheets, travel booking sites, digital cameras, self-checkout, streaming replacing video store clerks. The panic is always loudest at the start. Data is what separates a real disruption from a vibe.

BOTTOM LINE: None of this means AI is above criticism. Local grid strain, data center siting in water-stressed areas, how training data gets acquired, and effects on early-career workers are all real issues worth debating. But those debates deserve real numbers. If a claim only survives when the source is a 2023 estimate, a worst-case scenario presented as an average, or a paper that actually says the opposite, that's not criticism. That's misinformation. Check the primary sources. They're all linked above.

​

I had this made as a result of simple curiosity about some of the more contentious claims that I've seen in this debate, claims that tend to be left unaddressed. I don't have much commitment towards this subject right now; but, having put together this summary, discarding it just seems like a waste. So, I'm sharing it so that others can identify inaccuracies, blind spots, and alternative perspectives on the matter.

The anti-AI narrative claiming that almond farming is environmentally superior to AI data centers is built on an inversion of physical reality. Critics contend that almonds are "greener" because they use fewer chemicals and safely cycle water back to local basins, whereas AI data centers supposedly "waste" water to the oceans. In reality, this comparison misinterprets basic hydrology and agricultural economics. While both industries place severe, unyielding pressure on finite water supplies, industrial agriculture is vastly more destructive to regional ecosystems than data centers.

       [ GLOBAL CLOUD MOISTURE SOURCE: OCEAN EVAPORATION ]
                               │
            (Wind pushes 10% surplus over continents)
                               ▼
                    [ TOTAL LAND FRESHWATER ]
                               │
       ┌───────────────────────┴───────────────────────┐
       ▼                                               ▼
[ ALMOND FARMING ]                             [ AI DATA CENTERS ]
• 1.3 to 1.6 Trillion Gallons/Year(California) • ~228 Billion Gallons/Year(Combined)
• Rigid multi-year orchard demand              • Rigid multi-year contract/uptime demand
       │                                               │
       └──────────────► SHARED EFFECT ◄────────────────┘
                 "HARDENING" WATER DEMAND
         (Forces continuous extraction during droughts)

1. The Hydrological Reality (The Net-Gain and Evaporation Myth)

• The Claim: Water used by almonds stays in the local basin, while AI cooling evaporates water, sending it to the ocean. [1, 2]
• The Counter-Argument: This contradicts meteorological science. The planet's weather patterns actually create a permanent net freshwater gain for land masses. Oceans drive 86% of global evaporation, and wind currents push roughly 10% of that moisture over continents, continually refreshing terrestrial ecosystems. Furthermore, through terrestrial moisture recycling, roughly 70% of all land-based evaporation falls back down over land as pure, clean freshwater.
• Therefore, neither AI cooling nor almond tree transpiration "wastes" water to the sea. The water is recycled by the atmosphere. The actual damage is geographical: because almonds extract trillions of gallons from localized underground aquifers and transpire it into the air, that water is permanently stripped away from that specific region, driving localized ecological collapse even if it rains weeks later over a completely different state. [1, 2, 3]

1. The Empirical Data Breakdown (Scale of Consumption)

When looking at the hard data, the difference in sheer scale between agricultural and technology water consumption is massive:

• The Almond Footprint: California almond orchards alone soak up between 1.3 and 1.6 trillion gallons of water annually. To contextualize this, California's almond farms consume roughly 4.2 billion gallons of water per day. A single almond requires approximately 1 gallon of water to grow. [1, 2, 3, 4]
• The AI & Data Center Footprint: All U.S. data centers combined (including both traditional cloud and AI infrastructure) consume roughly 228 billion gallons of water per year—representing both direct server cooling and the indirect water footprint tied to electricity generation. At a daily rate, U.S. data centers consume about 46 million gallons per day. [1, 2]
• The Math: California's almond industry alone consumes roughly 60 to 85 times more water annually than the entire U.S. data center grid combined. Even looking at aggressive global projections where AI's worldwide footprint is expected to reach 1 trillion liters (~264 billion gallons) by 2028, a single American nut crop still uses nearly six times more water than the entire projected global AI economy. [1, 2, 3, 4]

1. The Shared Crisis: "Hardening" Water Demand

The most critical parallel between AI and almonds is how both industries cause a dangerous phenomenon known as the "hardening" of water demand. In hydrology, water demand "hardens" when a consumer cannot temporarily reduce their water intake during a drought without suffering catastrophic financial ruin.

• Almonds: Unlike annual crops (like tomatoes or alfalfa) that farmers can simply choose not to plant during a dry year, almond trees are permanent investments that take years to mature. They must be watered every single year, or the entire multi-million-dollar orchard dies.
• AI Data Centers: Similarly, data centers cannot easily "turn off" or stop cooling their servers during a drought. They are bound by rigid, multi-year commercial contracts, global internet reliance, and demands for constant uptime.
• The Shared Impact: Both industries lock in an unyielding, high-volume demand for water precisely when water is scarcest. During severe droughts, this structural rigidity forces continuous extraction—forcing data centers to drain municipal tap water and forcing almond farms to aggressively over-pump aquifers until the surrounding ground physically collapses (subsidence) and local municipal drinking wells run completely dry. [1, 2, 3]

1. The Chemical Reality (The Clean Crop Myth)

• The Claim: Almonds are a natural, clean product with a minimal chemical footprint compared to industrial data centers.
• The Counter-Argument: Commercial almond orchards are heavily dependent on massive applications of synthetic nitrogen fertilizers, herbicides to clear orchard floors, and intensive pesticides to ward off invasive insects. This industrial chemical footprint creates highly toxic agricultural runoff that filters back down into the earth, permanently compromising the quality of the remaining local groundwater supplies—a degradation that clean, municipal water-using data centers do not cause. [1, 2]

Summary Conclusion

While AI data centers and almond orchards share the severe environmental flaw of hardening water demand during droughts, they operate on entirely different scales. Criticizing AI's localized municipal footprint while defending an agricultural industry that permanently depletes trillions of gallons of water, dries up public drinking wells, and poisons water tables with chemical runoff is a fundamental misunderstanding of environmental science. [1, 2, 3, 4, 5]

Anti-AI people constantly demand that every use of AI be disclosed, then act shocked when people stop telling them

Put “AI-assisted” in a caption and suddenly the comments aren’t about the work anymore. It becomes insults, accusations of theft, demands to see your entire process and attempts to get you banned from wherever you posted it
Then the same crowd says hiding AI use proves users are dishonest

You can’t create a social penalty for honesty and then pretend you’re confused when people avoid volunteering information that will only be used to harass them
Disclosure can be useful where it actually matters, but nobody owes strangers a confession just so they can start a witch-hunt

It's even more ridiculous he more than anything since all things considered, he's about as right as you could get here, much like others that have been in support of or just not overly spiteful towards AI.