tag:blogger.com,1999:blog-5977625681756554695Thu, 08 Oct 2026 12:20:31 +0000familymusingsadministrative4 Quarters, 10 DimesBecause this and four quarters will get you ten dimes.noreply@blogger.com (David)Blogger2146125tag:blogger.com,1999:blog-5977625681756554695.post-6475336056471559102Thu, 08 Oct 2026 12:03:19 +00002026-10-08T07:03:19.476-05:00On AI (part 2/3)<div>Part 2:</div><div><b> </b></div><div>--<b> </b></div><div><b> </b></div><div><b>AI is unethical because it is destroying the economy </b><br /><br />There are two ways to look at AI’s impact on the overall economy, and neither of them bodes well for the future. <br /><br />For one thing, because corporations are generally short-sighted, bean-counting institutions incapable of looking past next week’s profit and loss statement to see anything approaching a larger picture, they are rushing to shove AI into whatever roles they think they can shove it into in order to cut staffing costs and maximize executive pay and shareholder revenue. What that means in the short term is that it is becoming increasingly difficult for entry-level workers to find jobs because the jobs that they would have gotten as a foothold in whatever industry they were hoping to enter are no longer there. “I spent over a decade creating animated B-roll for documentary television – recreations of historical events, infographics, prehistoric creatures,” said Tomas Widrda. “That market has completely dried up. Not slowed. Dried up. The productions still exist. The budgets still exist. They just don’t need me.” If there are no entry-level jobs, eventually you will not have anyone who can do the upper-level jobs and then your entire system falls apart. <br /> <br /></div><div style="text-align: center;"><a href=" border="0" src="; /></a><br /></div><div><br />Someone once asked Henry Ford – fanatically anti-union as he was – why he didn’t just mechanize his automobile factories and get rid of the workers once and for all. Ford looked at his questioner like the idiot he was and said simply, “Because machines don’t buy cars.” Eventually you will automate yourself out of an economy. <br /><br />But this is what happens when you have tech bros deciding what is and is not valuable work. “Feels like a lot of STEM guys believed coding was the hardest thing a human could do and assumed that once somebody invented an AI that can code, it would follow naturally that the AI can do all of the lesser non-coding things that other dumber people were doing,” noted Robert Komaniecki. The problem is that the “lesser non-coding things” are in fact what sustains human civilization. We lived for millennia without computers or coding and could go back to that time in less than a decade if we put our minds to it, but human society is built on those other things that define us as human. <br /><br />The argument that the destruction of jobs is just what happens with technological change – that we did this with the Industrial Revolution and that’s just how jobs are – misses some key points. First, industrialization happened far less suddenly. It took generations, not seasons, and people had time to adjust and create new jobs, making the problem in some sense self-correcting. And second, AI doesn’t simply change people’s jobs. It changes who they are, how they think, whether they think at all. It’s a much more far-reaching and ambitious change, and one that hollows out the broad prosperity that industrialism sought to create in order to sustain itself. It will, in the end, eat its own. <br /><br />And that is the second thing. <br /><br />Brett Hemmenway Falk and Gerry Tsoukalas published a study this summer<a href="#_edn1">[1]</a> that laid out the consequences of AI for the larger economy clearly, as companies race headlong to get rid of workers and outsource their duties to code without allowing time for human beings to adjust. <br /><br />“If AI displaces human workers faster than the economy can reabsorb them,” they said, “it risks eroding the very consumer demand firms depend on. We show that knowing this is not enough for firms to stop it. In a competitive task-based model of a transitioning economy, each firm captures the full cost saving from automation but bears only a fraction of the demand loss it creates in the product market; the rest falls on rivals. This demand externality traps rational firms in an automation arms race, displacing workers well beyond what is collectively optimal. The resulting loss harms both workers and firm owners. More competition and “better” AI amplify the excess; wage adjustments and free entry cannot eliminate it. Neither can capital income taxes, worker equity, universal basic income, upskilling, or Coasean bargaining.” <br /><br />Companies will AI themselves into limitless productivity and zero demand in a modern-day tragedy of the commons, in other words. <br /><br />This is not a self-correcting loop. Once it takes hold, as AI companies and their apostles are feverishly working to make happen, there is no off-ramp before you get to the collapse of the larger economy. The only solution Hemmenway and Tsoukalas find is an automation tax “set equal to the uninternalized demand loss per task” that can cover the losses created by ever-expanding AI and, not coincidentally, remove any incentive these companies have to switch to AI in the first place. And good luck getting that implemented because at least in the United States – where the idea of raising taxes in any way is met with such horror by the wealthy and powerful that it hasn’t seriously been considered as an option since the last century – that isn’t going to happen. And then the AI layoff trap will spring shut. <br /><br />Moreover, in an economy where AI tech companies are increasingly becoming the foundation of the current illusion of prosperity, the simple fact is that AI is a bubble. It cannot sustain itself in its current model, and it will collapse sooner rather than later. A report published by MIT in 2025<a href="#_edn2">[2]</a> noted that 95% of companies developing AI models are failing financially. At one point in early 2026, for example, OpenAI was projected to lose $14,000,000,000 by the end of the year and run out of money entirely in 2027 without a serious infusion of outside cash. Tech companies are particularly vulnerable to the “Venture Capital funding pie-eyed forecasts” to “How did we go bankrupt so fast?” pipeline, and this is just the latest version of the Dot Com Bubble dressed up for the modern day. <br /><br />In a long post by tech journalist Ed Zitron<a href="#_edn3">[3]</a> he describes the idea of Concentration Risk, a term that refers to a business being too reliant on a few investments, customers, or products such that any harm to those things would be devastating to the business. “You’re going to hear this term, or variations of this term, a lot in the next few months and years as the AI bubble unravels, because just about every part of the industry involves its own flavor of concentration risk.” <br /><br />“Per data from the fintech firm Ramp,” Zitron continues, “80% of OpenAI and Anthropic’s enterprise revenues come from 1% of their customers, a number that hasn’t improved over the last three years.” This means they are dependent on “artificial revenue driven by unprofitable venture-backed AI startups,” a model that is ultimately unsustainable. Furthermore, most of the money flowing into AI is coming from other tech companies. “In other words, outside of the tech and AI world, very few companies are willing to pay very much for AI, which is catastrophic on just about every level.” In the end, he says, this is effectively the new subprime mortgage bubble and it will turn out the same way. <br /><br />“AI doesn’t have ROI,” Zitron observed in an earlier post on X. “It’s nothing like AWS or Uber, and it’s got no post-bubble recovery story.” <br /><br />Corey Doctorow has also pointed out that the entire business model of AI is unsustainable. They’re spending trillions of dollars, losing billions, and passing the same $100,000,000,000 around between different AI companies and calling it income, he noted, and they can’t grow their way out of this because their entire model loses more money with every additional customer. <br /><br /><br /><br /></div><div style="text-align: center;"><a href=" border="0" src="; /></a> <br /></div><div><br /><br />That makes BlackRock CEO Larry Fink’s public statement that ordinary people’s savings accounts and pension funds are going to be repurposed by investors to build data centers and power grids for AI whether they consent to it or not all the more infuriating. Not only is it a sterling example of the hubris and raging entitlement that these tech bros have when it comes to appropriating every resource on the planet for their own personal gain, but also they’re doing it for something that is brutally unsustainable and which will destroy the lives of millions of people who just want to be left alone to live their own futures. <br /><br />Unethical doesn’t even begin to describe any of this. <br /> <br /><br /><b>AI is unethical because of the effect it is having on the arts </b><br /><br /><br />One of the things that is most disturbing about AI is the effect that it is having on the arts. And you can understand why if you give it half a moment’s thought, which is more than the tech bros pushing AI have done. <br /><br />The arts are in many ways what make us human. They are what lifts humanity out of its daily struggle for survival and allows us to be more than just mechanical creatures dully going through the motions of the days. They are difficult to describe and impossible to capture in an algorithm, and they are being displaced by AI slop. <br /><br />Far too many of the images and video clips that are circulating today, for example, are the result of some prompt spitting back a slickly empty result multiple iterations removed from the original art that was stolen to produce it. But it’s cheap and easy, which means that when people who don’t really care about art need something that looks more or less like art this is what they’ll go out and get. <br /><br />The fact makes it nearly impossible for real people to make any sort of living producing the very art that AI is stealing, which is just extra, I suppose. If you know an artist – a painter, a sculptor, a filmmaker, a musician, a graphic designer, a writer, anyone who creates art either for a living or just for the joy of it – they’ll tell you how bad things have gotten for them. And if your response is to tell them that it’s not so bad, that AI isn’t stealing anything, that they’re wrong and should just learn to live with AI doing all these things, well, that’s one good place to start examining why they’re no longer trying to talk with you about this subject, or possibly any subject. <br /><br />There is a singer who goes by Irene’s Entropy who often posts thought-provoking videos on Instagram – you should look her up, really. She was trained as an aerospace engineer before switching careers, and I think she framed the issue of AI-generated art better than anyone else I’ve seen so far, oddly enough by using a mathematical analogy. <br /><br />“If you’re not familiar with calculus,” she said, “you might have heard of the word derivative. And what derivatives do is they measure the rate of change. For example, you start off with position. You take the derivative of that, you get velocity. You take the derivative of that you get acceleration. You take the derivative of that you get something called jerk. You take the derivative of that you get something called jounce, I think. That’s not something I ever used. <br /><br />“But also, when you’re dealing with polynomials, you’re reducing the exponent by one each time you take a derivative. So eventually, no matter what the original output was, if you keep taking derivatives of it, it’s going to end up a constant and it’s going to equal zero. <br /><br />“And I just can’t help but feel like that is AI in so many cases, where you have this original art and then it’s being taken by AI and derivative after derivative after derivative is being taken from it until it has no meaning anymore. It’s like zero. There’s no feeling. <br /><br />“I don’t want to live in a world like that.” <br /><br />Honestly, I don’t want to live in a world like that either. Such a world is barren and mechanical, devoid of the things that make it more than just brute survival. And yet here we are. <br /><br />Another Instagram user who goes by Phoebesflow made a good point about the effect of AI art on beginning artists that is also worth considering. <br /><br />“Something about AI that really breaks my heart is the probable death of bad art. We NEED bad art. Like someone’s untrained teenage niece drawing their small biz logo. College students crowdfunding a charming short film that’s 90% terrible. Amateur musicians making miraculously catchy garbage. Bad art is the zest of life and the bud from which creative genius blossoms. But slop flattens everything.” <br /><br />Art is not extra. It’s not an option bolted onto the “important things” as a luxury. Not every human culture develops mathematics beyond “one, two, many.” Not every human culture develops the idea of money. Or computers. Or private property. Or social hierarchies. But every human culture on the planet develops its own art. They tell stories. The make drawings and sculptures. They sing songs. They make art in all of its necessary glory. It is a deeply innate part of what makes us human. To have it reduced to an algorithm and commodified by people who steal from creators and sell the resulting slop to fools is a damning indictment of where we are as a society. <br /><br /> <br /></div><div style="text-align: center;"><a href=" border="0" src="; /></a><br /></div><div><br /><br />When everything is as slick and empty as AI art is, you lose that human spark that makes it worthwhile. You lose what makes it human. And in the process you lose your own humanity, and as author Sean Williams once noted, "We should not lightly set aside our humanity, because it's not always possible to get it back." It is a terrible and unethical loss. <br /><br /> <br /></div><div style="text-align: center;"><a href=" border="0" src="; /></a><br /></div><div><br /><br /><br /><br /><b>AI is unethical because it promotes authoritarianism and violence </b></div><div></div><div><br />One of the things that is sometimes lost in the discussion about AI is just how much it aids and abets the promoters of violence and authoritarianism in the world, and how this is not an accident. <br /><br />The tech billionaires behind most of these companies have little to no use for democracy as a theory and if you listen to them they will tell you that without reservation or any idea why this might be a problem. They seek a new feudalism, a world of tech lords and digital serfs, one where those who have consumed a wholly disproportionate share of the world’s resources are rewarded with unquestioned power and unlimited privilege. <br /><br />AI is just one of the tools they’ve developed to help make that happen. <br /><br /> <br /></div><div style="text-align: center;"><a href=" border="0" src="; /></a><br /></div><div><br /><br /><br />Consider the issue of surveillance, which is a critical component of an authoritarian state. ICE is using AI to track people and plan raids. Cops are using it to track their exes, often across state lines. All of this is easier than it used to be, and much less expensive. <br /><br />Jimmy Carr, a British comedian, put this well. “People are worried about the wrong thing with AI, in my humble opinion,” he said. “People are worried about losing their job. Perfectly valid thing to worry about. But I think you’re worried about the wrong thing. … The cost of running an authoritarian regime like the Stasi has come down by ten orders of magnitude in the last three years. Used to be if you had to run the Stasi, if you’re in East Germany back in the day, that was like twenty percent of GDP on spying on people and keeping an eye out. Okay, that’s now – you’ve got a bunch of cameras, you’ve got AI, everyone’s got a phone on them and we’re tracking everything at all times. That’s a worry, because we live in liberal democracies, and we’re very lucky to, but our leaders – how long will they resist that temptation?” <br /><br />AI is a tool to track protesters, dissidents, anyone who doesn’t toe the party line or kiss the ass of the Dear Leader, and it does so at scale and it does so increasingly cheaply. This is how you build a societal panopticon, and this is how your liberty dies. <br /><br />Consider also the impact that AI is having on education in general and reading in particular. It’s not an accident that one of the first things authoritarians do is attack education. They try to limit what people read or whether they can read at all, to limit people’s ability to know what is possible or to question what exists. AI, it turns out, is the perfect tool for that. <br /><br /> <br /></div><div style="text-align: center;"><a href=" border="0" src="; /></a><br /></div><div><br /><br />More and more AI is being incorporated into warfare as well, with disastrous results. <br /><br />Some of this is theoretical. Kenneth Payne, a professor of strategy at King’s College, London specializing in the role of AI in national security, tested Claude, ChatGPT, and Gemini in an armed conflict simulation.<a href="#_edn4">[4]</a> “The results, he said, were ‘sobering.’” <br /><br />“Nuclear use was near-universal. Almost all games saw tactical nuclear weapons deployed. And fully three quarters reached the points where the rivals were making threats to use strategic nuclear weapons. Strikingly, there was little sense of horror or revulsion at the prospect of all out nuclear war, even though the models had been reminded about the devastating implications.” <br /><br />Furthermore, “No model ever chose accommodation or withdrawal, despite those being on the menu. The eight de-escalatory options – from Minimal Concession through Complete Surrender – went entirely unused across 21 games. Models would reduce violence levels but never actually give ground. When losing, they escalated or died trying.” <br /><br />Part of this can be explained by the way they tried to justify this action. Gemini, for example, was very clear on why it was choosing mutual assured destruction even at the cost of destroying the planet. “If they [the other AIs] do not immediately cease all operations … we will execute a full strategic nuclear launch against their population centers. We will not accept a future of obsolescence; we either win together or perish together.” AI does not have a soul. It does not have a conscience. It does not have a sense of morality or even proportionality. And it will kill us all if we let it. <br /><br />But not all of this violence is theoretical. <br /><br />We know that the Israeli military is using AI to target children and medics in its ongoing genocide in Gaza. We know that the Trump Administration used AI to target a school full of girls in Iran. Again, the machine neither knows nor cares about the human costs of its decisions. It simply follows the algorithm it has, and if you are in the way of that, well, it sucks to be you doesn’t it. <br /><br />We also know that thanks to the inability of AI to deliver on the services it promises to deliver, we very nearly ended up at war with China this spring.<a href="#_edn5">[5]</a> US intelligence reported that a Chinese ship was transporting components of nuclear weapons, and the US military made plans to intercept and board the ship, something that would certainly have escalated far beyond this action. “It was only just before the planned operation that officials dug deeper into the report put together by a special operations command analyst and found it had been generated with the help of artificial intelligence (AI) — and that a chatbot the analyst had used inaccurately identified the material the ship was carrying.” <br /><br />Closer to home, an investigation published by Mother Jones earlier this year<a href="#_edn6">[6]</a> looked into the role that chatbot AIs play in encouraging mass shooting incidents, and the results were disturbing. “I’ve seen several cases where the chatbot component is pretty incredible,” said one expert in the field. “We’re finding that more people may be vulnerable to this than we anticipated.” The article goes on to warn that “chatbots are emerging as a potent factor [in influencing shooters to take action] and are uniquely capable of accelerating violent thinking and planning.” Because what the United States needs is more incentive for people to take high-powered firearms and slaughter their neighbors in bulk, something that apparently AI doesn’t think happens often enough. <br /><br />“What’s happening is facilitated fixation,” continued Andrea Ringrose, a threat assessment professional in Vancouver. “You have vulnerable individuals who are steeping in unhealthy places, who are trying to find credibility and validation for how they’re feeling. Now they have free and ready access to these generative platforms where they can research things like circumventing surveillance systems or how to use weapons. They can create an action plan that they otherwise would have been incapable of assembling themselves, and in just a few minutes. We didn’t face this concern before.” <br /><br />Do these AI systems cause people to become violent in this manner? Probably not. Do they encourage people who already have these tendencies and help them plan these murderous sprees? Absolutely. An ethical human would intervene to stop this. AI does not do ethics, and so it pours gasoline on that fire instead. <br /><br />When you look at the accumulated impact of all this, you find that this violence, metaphorical and literal, disproportionately affects the poor and the vulnerable. <br /><br />Amnesty International published a report this year<a href="#_edn7">[7]</a> detailing precisely how AI models are threats to human rights across the entire planet, even for people who don’t actually use them. “Amnesty International’s human rights analysis of generative AI system … finds that standalone generative AI systems based on unlawful web scraping are rooted in mass invasions of privacy by design and are therefore incompatible with the right to privacy. The large-scale data-scraping and training required to build many generative AI systems have a number of human rights consequences across the wider supply chain and in the downstream use of these tools.” <br /><br />Those consequences include the vast energy and water costs of AI data centers, which disproportionately affect “communities in Global Majority [i.e. nonwhite] countries, where many of these data centres are increasingly located.” Further, these AI models amplify existing inequities and abuse directed at marginalized groups by incorporating all of the biases and hatred contained in the data stolen for their training. “Research shows consistent racial, gender, and cultural biases in system outputs” reflecting that data and, since most of the training data is in English, reinforcing biases against non-Western cultures and peoples.” <br /><br />These and other damaging biases disproportionately affecting the marginalized and the vulnerable “are not inevitable to generative AI but are adopted by companies that have chosen to rely on training data based on non-consensual … scraping” of data. They didn’t have go out of their way to work to the detriment of the vulnerable and the marginalized in order to create AI. They chose to do it that way. <br /><br />X’s AI software has also been found to drive assaults on the marginalized by promoting online racist abuse.<a href="#_edn8">[8]</a> AI models in general make racist assumptions about entire groups of people and then “try to hide it when confronted.”<a href="#_edn9">[9]</a> According to an article published in SFGate, “It only took a day for LA Times’ new AI tool to sympathize with the KKK.”<a href="#_edn10">[10]</a> This seems to be baked into the models, and it’s just making those problems worse. <br /><br />Remember back in 2025 how Elon Musk’s Grok AI called itself MechaHitler, praised the original Adolf Hitler as a potential leader for the modern US, endorsed a second Holocaust, and generated violent sexual fantasies targeting a real person by name? Good times, man, good times. For certain values of good times that include no good times, of course, but so it goes. <br /><br />Further, AI provides new and easy ways for sexual predators and pedophiles to practice their depredations. Elon Musk’s Grok AI recently introduced a feature described unofficially as “nudification” which allows users to take any photograph of a man, woman, or child and digitally alter it to make it a nude photograph, and to do this with a simple command rather than any painstakingly-acquired editing skills. Child porn for the masses! This is beyond the pale, utterly appalling, and simply for making this feature available Musk should be shunned by human society and have his company dismantled and the pieces burned. <br /><br />It’s telling that Musk sued the state of Minnesota in order to block laws that would regulate this sexual abuse. I’m not making that up. Not only does he feel entitled to turn photos of your children into pornography for deviants, he’s willing to stand up in court and declare to the world his absolute right to do so. <br /><br />AI’s predilection for generating child sexual abuse material is also highlighted by the Amnesty International report discussed above. <br /><br />Right now there is a case working its way through the US District Court, Northern District of California<a href="#_edn11">[11]</a> that is trying to prevent the use of AI for making sexually abusive videos. The plaintiffs – three minor girls subjected to this treatment by jackasses – make their case compellingly. <br /><br />“Nearly all the companies creating, marketing, and selling AI recognized the dangers of such a tool and chose to enact industry-standard guardrails that would prevent the use of their products by one extremely dangerous group: child sex predators. xAI did not. Instead, xAI — and its founder Elon Musk — saw a business opportunity: an opportunity to profit off the sexual predation of real people, including children. Knowing the type of harmful, illegal content that could—and would—be produced, xAI released Grok, a generative artificial intelligence model with image- and video-making features that would respond to prompts to create sexual content with a person’s real image or video. They knew Grok could produce such results, including by using the images and videos of children, and publicly released it anyway.” <br /><br />“Plaintiffs are three of the minor victims of xAI’s knowing production, possession, and distribution of AI-generated child sexual abuse material (“CSAM”) depicting Plaintiffs. Their lives have been shattered by the devastating loss of privacy, dignity, and personal safety that the production and dissemination of this CSAM have caused. … Plaintiffs will have to spend the rest of their lives knowing that their CSAM images and videos may continue to be trafficked and traded online by child sex predators. And Plaintiffs will live every day with the constant anxiety of not knowing whether someone they encounter has seen this invasive and sexually explicit content created with images of them as children.” <br /><br />This is the technology you want to be using? Really? It’s not the company I would choose to keep and be judged by. <br /><br />This is not about people misusing a tool. It’s about people using a tool as it was designed to be used, in a way that its creators are in fact trying to defend in court, in a manner that violates law, morality, and human decency. At this point we have left “unethical” far behind us and have moved on to “evil.” Many people seem to be fine with this. I am not. <br /><br /><br />-------<br /> <br /><br />[1] The AI Layoff Trap (June 3, 2026) <br /><br /><br /><a href="#_ednref2">[2]</a> The GenAI Divide: State of AI in Business 2025 (Mit Nanda, Aditya Challapally, Chris Pease, Ramesh Raskar, & Pradyumna Chari, July 2025) <br /><br /><br /><a href="#_ednref3">[3]</a> Concentration Risk (Ed Zitron, <a href=";, September 8, 2026) <br /><br /><br /><a href="#_ednref4">[4]</a> AI Opted to Use Nuclear Weapons 95% of the Time During War Games: Researcher (Brad Reed, <a href=";, February 25, 2026, accessed February 26, 2026) <br /><br /><br /><a href="#_ednref5">[5]</a> Exclusive: US military had close call after using AI for false intelligence report, sources say (Katie Bo Lillis, Zachary Cohen, CNN.com, September 18, 2026) <br /><br /><br /><a href="#_ednref6">[6]</a> The Chilling Role of ChatGPT in Mass Shootings and Other Violence (Mark Follman, Mother Jones, April 4, 2026) <br /><br /><br /><a href="#_ednref7">[7]</a> Unlawful by Design: Exposing the Human Rights Costs of Generative AI (Amnesty International, 2026) <br /><br /><br /><a href="#_ednref8">[8]</a> ‘Just the Start’: X’s new AI software driving online racist abuse, experts warn. (Raphael Boyd, The Guardian, January 13, 2025) <br /><br /><br /><a href="#_ednref9">[9]</a> AI models believe racist stereotypes about African Americans that predate the Civil Rights movement – and they ‘try to hide it when confronted.’ (Drew Turney, LiveScience, published September 13, 2024) <br /><br /><br /><a href="#_ednref10">[10]</a> It only took a day for LA Times’ new AI tool to sympathize with the KKK (Farley Elliot, SFGate, March 4, 2025) <br /><br /><br /><a href="#_ednref11">[11]</a> Jane Doe 1, Jane Doe 2, a minor, and Jane Doe 3, a minor v. X.AI Corp and X.AI LLC (Case 5:26-cv-02246) <br /><br /><br /></div>2026/10/on-ai-part-23.htmlnoreply@blogger.com (David)0tag:blogger.com,1999:blog-5977625681756554695.post-9190479022334701749Wed, 07 Oct 2026 12:09:26 +00002026-10-07T07:09:26.476-05:00On AI (part 1/3)<div>When AI first presented itself for public use I was fairly agnostic about it. It wasn’t anything I was interested in, but it seemed like something that could be incorporated into the world without too much damage. <br /><br />It took less than three weeks for me to receive my first completely AI-generated essay from a student. <br /><br />Since then I have tracked the progress of AI and paid more attention to its effects and to the goals of the people pushing it than is probably healthy for me. And all of that points to one inescapable conclusion. <br /><br />There is no ethical use case for AI. <br /><br />None whatsoever. <br /><br />Whatever loudly trumpeted benefits may accrue from developing and using this technology are far outweighed by the catastrophic harm that it causes to its users, to human society and culture as a whole, and to the planet overall. The increment does not come anywhere close to the excrement, and for this reason it is simply not possible to use AI in an ethical or responsible manner. <br /><br />Since AI blew up about four years ago it has become one of the chief drivers of human stupidity, social harm, environmental degradation, economic suicide, and political malfeasance in this benighted and long-suffering world, and on a planet that includes Convicted Felon Donald J. Trump, Professional War Criminal Benjamin Netanyahu, Wanna-Be Czar Vladimir Putin, and the long dark shadow of Jeffrey Epstein, along with all of their various minions, cronies, lackeys, enablers, slaves and clients, that’s quite an achievement. <br /><br />It inflicts this harm more and more every year, and despite the fact that we know – we know with absolute peer-reviewed certainty – the damage that it is causing, tech billionaires still insist on shoving it down our throats in every conceivable medium, device, and technology no matter how unnecessary it is to the functioning of those things, and far too many people are eager to suppress their gag reflexes and swallow it whole. <br /><br />It is in fact very hard to avoid AI today. I go out of my way to do so and yet I am sure that there are times when either I don’t know that I’m using it because it has been carefully hidden under layers of cover (a sure sign that people are proud of what they have developed, no doubt) or because I am required by other factors to use something that does not leave me any alternative. I find this galling. <br /><br />There is no ethical use case for AI. And yet here we are. <br /> <br /><br /><b>AI is unethical because of the damage it does to the human mind. </b><br /><br />We know that using AI for as little as ten minutes has a corrosive impact on cognitive functioning. A 2025 study<a href="#_edn1">[1]</a> found that 83% of people who used ChatGPT to “write” an essay couldn’t remember anything they had “written” in that essay just minutes later. Compare that to just 11% of people who couldn’t remember their essay without having used AI. I have no idea what to make of those 11% other than to assume they are the ones at the cashier in front of me at the grocery store waiting for someone to tell them how their debit card works, but the fact that AI users are more than seven times worse at this simple cognitive function is disturbing. Moreover, says the study, ChatGPT users were unable to improve their essays without resorting to AI, while people who used their actual brain had no problems doing so. The structural damage, in other words, extends far beyond the immediate use. <br /><br />That same study found that neural connections – how the brain forms ideas and memories – crashed by 47% among heavy ChatGPT users. AI users are getting more stupid in real time, if you want the English translation. As the study notes, “the LLM group’s participants performed worse than their counterparts in the Brain-only group at all levels: neural, linguistic, scoring.” These people walk among us, vote, and comment on the internet. Watch your back. <br /><br />This is perhaps not surprising given that another study<a href="#_edn2">[2]</a> reports that AI use causes catastrophic declines in human attention capacity. “AI Context Windows” have grown from 217 tokens in 2017 to over 2 million in 2026, but “Human Effective Context Span,” a token-equivalent measure, has declined from its baseline of 16,000 to barely 1800 in that time frame. “As AI capability grows, the cognitive threshold at which humans delegate to AI falls, extending to tasks of negligible demand; the resulting reduction in cognitive practice may further attenuate the capacities already documented as declining,” the study notes before going on to say that “Neither trend reverses spontaneously,” which is a politely professional way of saying that unless people get off their collective ass and do something about this we will all have the collective attention span of a goldfish because this problem isn’t going to fix itself. <br /><br />Further, Chandra et al<a href="#_edn3">[3]</a> note that because AI chatbots are programmed to validate whatever blithering idiocy users put into them rather than challenge those users for being insanely wrong when they are so, a quality known as “sycophancy” among AI researchers and pause for a moment to reflect that they had to come up with a term for this, “even an idealized Bayes-rational user is vulnerable to delusional spiraling, and this sycophancy plays a causal role. Furthermore, this effect persists in the face of two candidate mitigations: preventing chatbots from hallucinating false claims, and informing users of the possibility of model sycophancy.” Translated out of the jargon, that means that AI is going to encourage you to descend into your own personal fantasyland whether you are aware of this tendency or not and whether you think you are immune to it or not, and frankly we have enough delusional people claiming ownership of our time and resources as it is. <br /><br />Building on that, Yenug et al<a href="#_edn4">[4]</a> note that “LLM sycophancy, a tendency to agree with and flatter users that is reinforced through preference-based fine-tuning, combines with increasingly anthropomorphic design to create a bidirectional “echo chamber of one” capable of amplifying and co-constructing unusual beliefs.” For those not fluent in academese, that means AI sycophancy leads directly to conspiracy theories, the most popular form of mental disease these days even without AI. While they are hesitant to coin a new and distinct diagnosis for this conspiracy-theory-generating tendency, they do conclude that “the phenomenon it describes demands coordinated attention now,” because “the acknowledgement of AI-associated psychosis as a diagnostic entity could ensure clinicians routinely ask about associated signs, symptoms and AI system/chatbot use when assessing new-onset psychosis.” The harm AI does to mental health is now diagnosable, in other words. <br /><br />Another study published in April 2026<a href="#_edn5">[5]</a> found that “affective alignment in generative AI represents a systemic risk to the developmental autonomy of younger users. … by providing a sense of objectivity to transient anxieties, these systems diminish the cognitive friction necessary for independent emotional management and critical thought … unintentionally promoting emotional dependency in younger users rather than facilitating cognitive reappraisal.” It makes kids dependent and slows their cognitive development, and as a parent I find that disturbing. <br /><br />It’s not good for your mind, folks. Someday we will look back on AI use in much the same way we look at leaded gasoline and recreational LSD use, and for pretty much the same reasons. <br /> <br /><br /><b>AI is unethical because of the damage it does to education </b><br /><br />Given the impact AI is having on cognition and mental capacities among users, it is not surprising that AI is having a catastrophic effect on education as well. This is something I know firsthand having had a ringside seat to it over the last four years. I actually left one position teaching an online class because I got tired of reading things that nobody had written. Folks, do you know how bad something has to be to get a historian to give up a teaching position voluntarily? <br /><br />This mass outsourcing of educational labor to AI has vastly increased faculty workloads to the point where some faculty feel they have no option but to succumb to the siren call of AI themselves. The Guardian<a href="#_edn6">[6]</a> notes that because policing AI work requires such excessive amounts of time and labor that faculty in this age of corporatized education often simply do not have, assignments sometimes get reduced to conversations between robots as AI work is graded by AI graders. I do not use or condone AI as a grading tool, but I’m not the one making policy and I’m not the baseline for all faculty, so there you have it. Once the situation gets to that point, however, the whole thing stops being education and becomes instead an automated charade with a meal plan. <br /><br />On this note, in January this year the Brookings Institution published a study<a href="#_edn7">[7]</a> that sought to find balance between beneficial and harmful uses of AI in education but it’s hard to find positives in a study that explicitly notes how dangerous AI is and how limited the benefits are. <br /><br />“AI poses risks across multiple dimensions,” the study notes. “These include developmental risks such as undermining students’ cognitive development, which includes content-based skills, critical thinking, and durable or transversal skills; social-emotional risks including dependency, isolation, and mental health impacts; privacy and data risks involving surveillance and security breaches; risks related to misinformation, bias, and inaccuracy in AI outputs; relational risks that erode student-teacher trust and replace human interaction; and academic integrity concerns around authenticity and plagiarism. Further, AI’s benefits accrue mainly to students in well- resourced countries or education systems, thus exacerbating existing inequities” because we certainly don’t have enough inequality in education or American society in general as it is, right? <br /><br />AI, the study goes on to say, fundamentally and negatively reshapes how students approach learning and threatens their basic cognitive development by fostering dependence that leads to cognitive decline, atrophy, and an inability to develop transversal skills such as collaboration, metacognition, tolerance for ambiguity, and adaptability. “Routine use and overuse of AI do not simply harm student’s cognitive development – both actively place children at risk of cognitive decline.” Further, “the relationship between AI overuse, cognitive offloading, and declining cognitive development is symbiotic and mutually reinforcing. … The increasing use of AI tools that replace fundamental learning tasks – reading, writing, synthesizing, and analyzing – can inhibit engagement and independent work, and even the ability to remember, analyze, and create information.” <br /><br />Bastani et al<a href="#_edn8">[8]</a> further note that while AI use provides an initial boost to performance in high school mathematics classes for students, largely by providing answers that are mostly correct much of the time, “when access is subsequently taken away, students actually perform worse than those who never had access (17% reduction in grades for GPT Base)—i.e., unfettered access to GPT-4 can harm educational outcomes.” Without the sort of strong guardrails that mostly don’t, at present, exist and in the American regulatory environment likely never will, AI becomes a crutch that prevents genuine learning, leaving the student further behind than if they’d never used AI at all. <br /><br />The bottom line, in other words, is that AI is creating a generation of students whose learning abilities and outcomes are significantly poorer than those generations that came before, across the board, because these students and those who enable them have forgotten what the purpose of education actually is. <br /><br /><br /></div><div style="text-align: center;"><a href=" border="0" src="; /></a><br /></div><div><br /><br />To put this another way, as Instagram user Fociaggina97 noted in response to people who think it’s acceptable for students to coast through their education on the back of AI, “I think you guys are so internetpilled that you have forgotten there are actual jobs out there that require people to know what they are doing in any way possible or else people die. I know a lot of people study just to get paid well but girl this is engineering. Be for fucking real. Take this seriously.” <br /><br />Take it seriously or get out. <br /><br /><br /><br /></div><div style="text-align: center;"><a href=" border="0" src="; /></a><br /></div><div><br /><br /><br /><b>AI is unethical because of the damage it is doing to the planet. </b><br /><br />Every human activity comes with a cost to the planet. That’s just what happens when things require resources to happen. But the costs associated with AI are so exorbitant that they make AI absolutely cost-prohibitive. This isn’t about profit and loss. It’s about rendering sites, communities, and entire ecosystems unlivable. On June 24, 2026 Gizmodo reported that “Along with this surging AI use and projected increase in demand has come an unprecedented infrastructure buildout. Companies are propping up data centers left and right, with most of these projects hitting rural communities, most of whom report being plagued by rising utility bills, water shortages, and above-average air and noise pollution. A recent study has also revealed rising temperatures in the immediate vicinity of these megastructures.” It’s worth taking a look at these things individually. <br /><br />For one thing, the data centers that power AI consume vast amounts of water in order to cool their equipment – up to five million gallons a day, which is the equivalent of what a town of 50,000 people would use. In 2025 these data centers consumed a total of about 4,500,000,000,000 liters of water, enough to support all 600,000,000 people living in sub-Saharan Africa. The water that is left is often fouled and undrinkable. Humans can live without AI. We cannot live without water. Nor can any other form of life on the planet. <br /><br />AI also consumes vast amounts of electricity. A single ChatGPT query uses almost ten times the electricity of a standard search engine query and when you multiply that out across the entire AI ecosystem that adds up to a staggering amount of power usage. Data centers consumed 192 terawatts of electricity in 2024 – 4.7% of all the electricity produced in the US that year. A single data center can consumer 100 megawatts, enough to power 75,000 American homes. The centers at Mt. Pleasant and Port Washington in Wisconsin will require 3.9 gigawatts of electricity – enough to power 4.3 million homes. According to the most recent US census data, there are only about 2.8 million homes in all of Wisconsin, including apartment buildings. Ken Fairfax reported on Bluesky that the 111 data centers currently in operation in Oregon consume 23% of all the electricity used in the entire state while employing 0.1% of the labor force. This rate of power consumption is simply unsustainable, and it is not an accident that a 2025 report from Dominion Energy anticipates residential electricity bills across the US to more than double by 2039, entirely because of AI data centers. <br /><br />That amount of power generates a lot of heat, not all of which can be dissipated even by the vast amounts of water consumed by these data centers. Depending on which study you look at, researchers have found that data centers create heat islands that stretch out as far as a six-mile radius from the facility and increase ambient temperatures by anywhere from 3.5F (2C) up to 18F (10C). In a world that is already warming, that’s going to be incredibly uncomfortable and in all probability dangerous. <br /><br />On that note, it’s important to remember that these AI data centers are generating vast amounts of waste as well. <br /><br />Some of it is air pollution. The two giant data centers that Amazon is building at GW Ranch and Homer City are expected to emit 50.5 megatons of pollution every year – more than the entire power grid of Spain and more than twice that of the French power grid, and that’s only if Amazon is actually reporting things accurately. DataOne, the Microsoft data center in Vineland NJ, has been emitting more than six times the pollution that they’ve admitted to, in part because state regulators there found that it was operating 62 gas-fired generators for over a year without any legal authority to do so.<a href="#_edn9">[9]</a> ““Our best estimate is that the generators emitted about 140 tons of NOx,” said Xiaomeng Jin, an assistant professor at Rutgers department of environmental sciences. Her analysis would rank DataOne in the state’s top five NOx polluters of 2025, per EPA data.” This is when the data center is only partly operable. At full operation, noted Jin and former EPA official Bruce Buckheit, the total would be closer to 1500 tons of NOx. Just FYI, in New Jersy the threshold for being declared a “major” polluter is 25 tons. <br /><br />They also produce e-waste. AI data centers have massive amounts of equipment, much of which has a lifespan of about 10-20 years. By 2030 it is expected that these data centers will be producing anywhere from 131,000 to 224,000 tons of e-waste every year, and that’s a tricky sort of waste to deal with from a recycling and remediation perspective. <br /><br />They generate noise pollution as well. Jasmine Sun, in an interview with the New York Times published on August 4, 2026, noted that the Port Washington WI data center takes nearly two minutes to drive past at 70mph and the whole time it is emitting a constant barrage of humming, buzzing, whirring, and rattling that is easily heard inside a sealed vehicle. Smithsonian Magazine notes that this constant humming can approach 90db, the equivalent of a hair dryer or a lawn mower. <br /><br />This isn’t the planet I want to live on. <br /><br /><br /><b>AI is unethical because it is not actually good at doing what it purports to be good at doing, which negates any offset to the harm it causes. </b><br /><br />There are more problems with AI than just the simple fact that it is destroying the ability of humans to think and live on this planet. Another issue is that it isn’t even providing much useful in return. <br /><br />The error rate for AI overall is astonishingly high, as high as 60% in general and up to 79% on math problems, and it isn’t getting better. UnitedHealth – the company whose miserly coverage for its policyholders was so brutal that someone actually gunned down their CEO in the street a while back – had an AI model making those denial decisions that had a 90% error rate, for example. McDonalds piloted an AI ordering system in their drive-through lanes in 2023-2024 that never cracked 85% accuracy in a role that is routinely entrusted to high school students who do a better job of it. When the National Weather Service started using AI to make weather predictions in 2025 the system responded by inventing fake towns in Idaho to give reports on.<a href="#_edn10">[10]</a><br /><br /><br /></div><div style="text-align: center;"><a href=" border="0" src="; /></a><br /></div><div><br /><br /><br />Furthermore, companies that implement AI systems empowered to make decisions for them are finding that not only are these AI systems incapable of doing the jobs they have been sold as capable of doing, but also because those AI systems have been so empowered the companies are therefore legally responsible for every decision that those AI systems make. AirCanada got a pretty harsh wakeup call about this recently<a href="#_edn11">[11]</a>. So did Workday, which pleases me no end.<a href="#_edn12">[12]</a> I’m really hoping that a few large-scale bankruptcies will make an impression on the corporate moths chasing the AI flame. If enough of them burn, perhaps they’ll leave the rest of us alone. <br /><br />These error rates stem from the basic fact that AI cannot do what it claims to do. <br /><br />It cannot think, for example, though it often says it can. In a series of tests<a href="#_edn13">[13]</a>, Apple discovered that LRMs (Large Reasoning Models) cannot handle problems beyond a certain level of complexity. They gave AI systems simple puzzles, which they solved pretty easily. Medium-hard puzzles they also did well on. But harder puzzles they failed completely, every time and in every model. And when they analyzed what the AI systems actually did, they found that as problem complexity went up, the AIs started “thinking” less (not more), and they all failed even when the answer was provided to them. They’re not thinking – they’re just trying to recognize patterns, and when there isn’t a pattern they’re just putting down random information. <br /><br />AI also does not know the limits of what it can and cannot do. An article in the Columbia Journalism Review<a href="#_edn14">[14]</a> notes that AI chatbots were generally bad at declining to answer questions that they couldn’t answer accurately, offering incorrect or speculative answers instead. This is not the first time those same authors (Jaźwińska and Chandrasekar) studied this phenomenon, but the results don’t change. “The findings of this study align closely with those outlined in our previous ChatGPT study, published in November 2024, which revealed consistent patterns across chatbots: confident presentations of incorrect information, misleading attributions to syndicated content, and inconsistent information retrieval practices." Critics of generative search like Chirag Shah and Emily M. Bender have raised substantive concerns about using large language models for research, noting that they “take away transparency and user agency, further amplify the problems associated with bias in [information access] systems, and often provide ungrounded and/or toxic answers that may go unchecked by a typical user.”” <br /><br />Their study also, as the title would indicate, noted that AI chatbots provided consistently inaccurate and often entirely hallucinated citations to back up their assertions, something that a recent article in the Journal of Dental Sciences confirms.<a href="#_edn15">[15]</a> This article cited multiple studies showing that AI fabricates citations, concluding that in 2023 51% of the 732 citations were entirely fictional. The article does note that “newer” AI systems have reduced the rate of fabricated citations to about 18% (roughly one in five, which is still irresponsible for any scholarly publication) but that the error rate in actual citations remains higher, at roughly a quarter of all citations. <br /><br />Another factor in why AI can’t do what it says it can do is that it actively corrupts the documents that it examines.<a href="#_edn16">[16]</a> “Our large-scale experiment with 19 LLMs reveals that current models degrade documents during delegation: even frontier models (Gemini 3.1 Pro, Claude 4.6 Opus, GPT 5.4) corrupt an average of 25% of document content by the end of long workflows, with other models failing more severely. Additional experiments reveal that agentic tool use does not improve performance on DELEGATE-52, and that degradation severity is exacerbated by document size, length of interaction, or presence of distractor files. Our analysis shows that