AI Content Marketing: Claims about Savings Are Pipe Dreams
July 24, 2025
This blog post is the work of an authentic dinobaby. Sorry. No smart software can help this reptilian thinker.
My tiny team and I sign up for interesting smart software “innovations.” We plopped down $40 to access 1min.ai. Some alarm bells went off. These were not the panic inducing Code Red buzzers at the Google. But we noticed. First, registration was wonky. After several attempts were had an opportunity to log in. After several tries, we gained access to the cornucopia of smart software goodies. We ran one query and were surprised to see Hamster Kombat-style points. However, the 1min.ai crowd flipped the winning click-to-earn model on its head. Every click consumed points. When the points were gone, the user had to buy more. This is an interesting variation of taxi meter pricing, a method reviled in the 1980s when commercial databases were the rage.
I thought about my team’s experience with 1min.ai and figured that an objective person would present some of these wobbles. Was I wrong? Yes.
“Your New AI-Powered Team Costs Less Than $80. Meet 1min.ai” is one of the wildest advertorial or content marketing smoke screens I have encountered in the last week or so. The write up asserts as actual factual, hard-hitting, old-fashioned technology reporting:
If ChatGPT’s your sidekick, think of 1min.AI as your entire productivity squad. This AI-powered tool lets you automate all kinds of content and business tasks—including emails, social media posts, blog drafts, reports, and even ad copy—without ever opening a blank doc.
I would suggest that one might tap 1min.ai to write an article for a hard-working, logic-charged professional at Macworld.
How about this descriptive paragraph which may have been written by an entity or construct:
Built for speed and scale, 1min.AI gives you access to over 80 AI tools designed to handle everything from content generation to data analysis, customer support replies, and more. You can even build your own tools inside the platform using its AI builder—no coding required.
And what about this statement:
The UI is slick and works in any browser on macOS.
What’s going on?
First, this information is PR assertions without factual substance.
Two, the author did not try to explain the taxi meter business model. It is important if one uses one account for a “team.”
Three, the functionality of the system is less useful that You.com based on our tests. Comparing 1min.ai is a key word play. ChatGPT has some bit time flaws. These include system crashes and delivering totally incorrect information. But 1min.ai lags behind. When ChatGPT stumbles over the prompt finish line, 1min.ai is still lacing its sneakers.
Here’s the final line of this online advertorial:
Act now while plans are still in stock!
How does a digital subscription go out of stock. Isn’t the offer removed?
I think more of this type of AI play acting will appear in the months ahead.
Stephen E Arnold, July 24, 2025
AI and Customer Support: Cost Savings, Yes. Useful, No
July 24, 2025
This blog post is the work of an authentic dinobaby. Sorry. No smart software can help this reptilian thinker.
AI tools help workers to be more efficient and effective, right? Not so much. Not in this call center, anyway. TechSpot reveals, “Call Center Workers Say Their AI Assistants Create More Problems than They Solve.” How can AI create problems? Sure, it hallucinates and it is unpredictable. But why should companies let that stop them? They paid a lot for these gimmicks, after all.
Writer Rob Thubron cites a study showing customer service reps at a Chinese power company are less than pleased with their AI assistants. For one thing, the tool often misunderstands customers’ accents and speech patterns, introducing errors into call transcripts. Homophones are a challenge. It also struggles to accurately convert number sequences to text—resulting in inaccurate phone numbers and other numeric data.
The AI designers somehow thought their product would be better at identifying human emotions than people. We learn:
“Emotion recognition technology, something we’ve seen several reports about – most of them not good – is also criticized by those interviewed. It often misclassified normal speech as being a negative emotion, had too few categories for the range of emotions people expressed, and often associated a high volume level as someone being angry or upset, even if it was just a person who naturally talks loudly. As a result, most CSRs [Customer Service Reps] ignored the emotional tags that the system assigned to callers, saying they were able to understand a caller’s tone and emotions themselves.”
What a surprise. Thubron summarizes:
“Ultimately, while the AI assistant did reduce the amount of basic typing required by CSRs, the content it produced was often filled with errors and redundancies. This required workers to go through the call summaries, correcting mistakes and deleting sections. Moreover, the AI often failed to record key information from customers.”
Isn’t customer service rep one of the jobs most vulnerable to AI takeover? Perhaps not, anymore. A June survey from Gartner found half the organizations that planned to replace human customer service reps with AI are doing an about-face. A couple weeks later, the research firm anticipated that more than 40% of agentic AI projects will be canceled by 2027. Are the remaining 60% firms that have sunk too much money into such ventures to turn back?
Cynthia Murrell, July 24, 2025
The Difference between Financials Viewed by a PR Person and an MBA
July 23, 2025
This blog post is the work of an authentic dinobaby. Sorry. No smart software can help this reptilian thinker.
Another essay from a public relations professional. I just wrote a short blog post about “Clarity.” Now I am addressing an essay titled “The Hater’s Guide To The AI Bubble.” The write up is a fairly long one, about 14,000 or so. The length makes clear that considerable work by the author or assistants went into compiling the numeric data about investments by big outfits in artificial intelligence.
The John Milton essay Areopagitica contains about 16,000 words. This puts the cited article squarely in the readership target of an educated readership in 1644. Like Milton’s screed, “The Hater’s Guide to the AI Bubble” is a polemic.
I am not going to create an abstract of the write up. Instead I will feed the text into some smart software and ask for a 150 word summary just like the ones in the old-fashioned ABI/INFORM database. Here’s what the cheap version of ChatGPT output:
Edward Zitron critiques the generative AI boom, arguing it is an unsustainable financial and technological bubble driven by hype rather than profitability or utility. He contends that companies like Microsoft, Google, and Meta have spent over $560 billion on AI infrastructure with little to no return, while only NVIDIA profits from the GPU demand. Zitron dismantles comparisons to past innovations like AWS, noting that generative AI lacks infrastructure value, scalability, and viable business models. He criticizes AI “agents” as misleading marketing for underperforming chatbots and highlights that nearly all AI startups are unprofitable. The illusion of widespread AI adoption is, according to Zitron, a coordinated market fantasy supported by misleading press and executive spin. The industry’s fragility, he warns, rests entirely on continued GPU sales. Zitron concludes with a call for accountability, asserting that the current AI trade endangers economic stability and reflects a failure of both corporate vision and journalistic scrutiny. (Source: ChatGPT, cheap subscription, July 22, 2025)
I will assume that you, as I did, worked through the essay. You have firmly in mind that large technology outfits have a presumed choke-hold on smart software. The financial performance of the American high technology sector needs smart software to be “the next big thing.” My view is that offering negative views of the “big thing” are likely to be greeted with the same negative attitudes.
Consider John Milton, blind, assisted by a fellow who visualized peaches at female anatomy, working on a Latinate argument against censorship. He published Areopagitica as a pamphlet and no one cared in 1644. Screeds don’t lead. If something bleeds, it gets the eyeballs.
My view of the write up is:
- PR expert analysis of numbers is different from MBA expert analysis of numbers. The gulf, as validated by the Hater’s Guide, is wide and deep
- PR professionals will not make AI succeed or fail. This is not a Dog the Bounty Hunter type of event. The palpable need to make probabilistic, hallucinating software “work” is truly important, not just to the companies burning cash in the AI crucibles, but to the US itself. AI is important.
- The fear of failure is creating a need to shovel more resources into the infrastructure and code of smart software. Haters may argue that the effort is not delivering; believers have too much skin in the game to quit. Not much shames the tech bros, but failure comes pretty close to making these wizards realize that they too put on pants the same way as other people do.
Net net: The cited write up is important as an example of 21st-century polemicism. Will Mr. Zuckerberg stop paying millions of dollars to import AI talent from China? Will evaluators of the AI systems deliver objective results? Will a big-time venture firm with a massive investment in AI say, “AI is a flop”?
The answer to these questions is, “No.”
AI is here. Whether it is any good or not is irrelevant. Too much money has been invested to face reality. PR professionals can do this; those people writing checks for AI are going to just go forward. Failure is not an option. Talking about failure is not an option. Thinking about failure is not an option.
Thus, there is a difference between how a PR professional and an MBA professional views the AI spending. Never the twain shall meet.
As Milton said in Areopagitica :
“A man may be a heretic in the truth; and if he believes things only because his pastor says so, or the assembly so determines, without knowing other reason, though his belief be true, yet the very truth he holds becomes his heresy. There is not any burden that some would gladlier post off to another, than the charge and care of their religion.”
And the religion for AI is money.
Stephen E Arnold, July 23, 2025
Mixed Messages about AI: Why?
July 23, 2025
Just a dinobaby working the old-fashioned way, no smart software.
I learned that Meta is going to spend hundreds of billions for smart software. I assume that selling ads to Facebook users will pay the bill.
If one pokes around, articles like “Enterprise Tech Executives Cool on the Value of AI” turn up. This write up in BetaNews says:
The research from Akkodis, looking at the views of 500 global Chief Technology Officers (CTOs) among a wider group of 2,000 executives, finds that overall C-suite confidence in AI strategy dropped from 69 percent in 2024 to just 58 percent in 2025. The sharpest declines are reported by CTOs and CEOs, down 20 and 33 percentage points respectively. CTOs also point to a leadership gap in AI understanding, with only 55 percent believing their executive teams have the fluency needed to fully grasp the risks and opportunities associated with AI adoption. Among employees, that figure falls to 46 percent, signaling a wider AI trust gap that could hinder successful AI implementation and long-term success.
Okay. I know that smart software can do certain things with reasonable reliability. However, when I look for information, I do my own data gathering. I think pluck items which seem useful to me. Then I push these into smart AI services and ask for error identification and information “color.”
The result is that I have more work to do, but I would estimate that I find one or two useful items or comments out of five smart software systems to which I subscribe.
Is that good or bad? I think that for my purpose, smart software is okay. However, I don’t ask a question unless I have an answer. I want to get additional inputs or commentary. I am not going to ask a smart software system a question to which I do not think I know the answer. Sorry. My trust in high-flying Google-type Silicon Valley outfits is non existent.
The write up points out:
The report also highlights that human skills are key to AI success. Although technical skill are vital, with 51 percent of CTOs citing specialist IT skills as the top capability gap, other abilities are important too, including creativity (44 percent), leadership (39 percent) and critical thinking (36 percent). These skills are increasingly useful for interpreting AI outputs, driving innovation and adapting AI systems to diverse business contexts.
I don’t agree with the weasel word “useful.” Knowing the answer before firing off a prompt is absolutely essential.
Thus, we have a potential problem. If the smart software crowd can get people who do not know the answers to questions, these individuals will provide the boost necessary to keep this technical balão de fogo up in the air. If not, up in flames.
Stephen E Arnold, July 23, 2025
Lawyers Do What Lawyers Do: Revenues, AI, and Talk
July 22, 2025
A legal news service owned by LexisNexis now requires every article be auto-checked for appropriateness. So what’s appropriate? Beyond Search does not know. However, here’s a clue. Harvard’s NeimanLab reports, “Law360 Mandates Reporters Use AI Bias Detection on All Stories.” LexisNexis mandated the policy in May 2025. One of the LexisNexis professionals allegedly asserted that bias surfaced in reporting about the US government.The headline cited by VP Teresa Harmon read: “DOGE officials arrive at SEC with unclear agenda.” Um, okay.
Journalist Andrew Deck shares examples of wording the “bias” detection tool flagged in an article. The piece was a breaking story on a federal judge’s June 12 ruling against the administration’s deployment of the National Guard in LA. We learn:
“Several sentences in the story were flagged as biased, including this one: ‘It’s the first time in 60 years that a president has mobilized a state’s National Guard without receiving a request to do so from the state’s governor.’ According to the bias indicator, this sentence is ‘framing the action as unprecedented in a way that might subtly critique the administration.’ It was best to give more context to ‘balance the tone.’ Another line was flagged for suggesting Judge Charles Breyer had ‘pushed back’ against the federal government in his ruling, an opinion which had called the president’s deployment of the National Guard the act of ‘a monarchist.’ Rather than ‘pushed back,’ the bias indicator suggested a milder word, like ‘disagreed.’”
Having it sound as though anyone challenges the administration is obviously a bridge too far. How dare they? Deck continues:
“Often the bias indicator suggests softening critical statements and tries to flatten language that describes real world conflict or debates. One of the most common problems is a failure to differentiate between quotes and straight news copy. It frequently flags statements from experts as biased and treats quotes as evidence of partiality. For a June 5 story covering the recent Supreme Court ruling on a workplace discrimination lawsuit, the bias indicator flagged a sentence describing experts who said the ruling came ‘at a key time in U.S. employment law.’ The problem was that this copy, ‘may suggest a perspective.’”
Some Law360 journalists are not happy with their “owners.” Law360’s reporters and editors may not be on the same wave length as certain LexisNexis / Reed Elsevier executives. In June 2025, unit chair Hailey Konnath sent a petition to management calling for use of the software to be made voluntary. At this time, Beyond Search thinks that “voluntary” has a different meaning in leadership’s lexicon.
Another assertion is that the software mandate appeared without clear guidelines. Was there a dash of surveillance and possible disciplinary action? To add zest to this publishing stew, the Law360 Union is negotiating with management to adopt clearer guidelines around the requirement.
What’s the software engine? Allegedly LexisNexis built the tool with OpenAI’s GPT 4.0 model. Deck notes it is just one of many publishers now outsourcing questions of bias to smart software. (Smart software has been known for its own peculiarities, including hallucination or making stuff up.) For example, in March 2025, the LA Times launched a feature dubbed “Insights” that auto-assesses opinion stories’ political slants and spits out AI-generated counterpoints. What could go wrong? Who new that KKK had an upside?
What happens when a large publisher gives Grok a whirl? What if a journalist uses these tools and does not catch a “glue cheese on pizza moment”? Senior managers training in accounting, MBA get it done recipes, and (date I say it) law may struggle to reconcile cost, profit, fear, and smart software.
But what about facts?
Cynthia Murrell, July 22, 2025
Why Customer Trust of Chatbot Does Not Matter
July 22, 2025
Just a dinobaby working the old-fashioned way, no smart software.
The need for a winner is pile driving AI into consumer online interactions. But like the piles under the San Francisco Leaning Tower of Insurance Claims, the piles cannot stop the sag, the tilt, and the sight of a giant edifice tilting.
I read an article in the “real” new service called Fox News. The story’s title is “Chatbots Are Losing Customer Trust Fast.” The write up is the work of the CyberGuy, so you know it is on the money. The write up states:
While companies are excited about the speed and efficiency of chatbots, many customers are not. A recent survey found that 71% of people would rather speak with a human agent. Even more concerning, 60% said chatbots often do not understand their issue. This is not just about getting the wrong answer. It comes down to trust. Most people are still unsure about artificial intelligence, especially when their time or money is on the line.
So what? Customers are essentially irrelevant. As long as the outfit hits its real or imaginary revenue goals, the needs of the customer are not germane. If you don’t believe me, navigate to a big online service like Amazon and try to find the number of customer service. Let me know how that works out.
Because managers cannot “fix” human centric systems, using AI is a way out. Let AI do it is a heck of lot easier than figuring out a work flow, working with humans, and responding to customer issues. The old excuse was that middle management was not needed when decisions were pushed down to the “workers.”
AI flips that. Managerial ranks have been reduced. AI decisions come from “leadership” or what I call carpetland. AI solves problems: Actually managing, cost reduction, and having good news for investor communications.
The customers don’t want to talk to software. The customer wants to talk to a human who can change a reservation without automatically billing for a service charge. The customer wants a person to adjust a double billing for a hotel doing business Snap Commerce Holdings. The customer wants a fair shake.
AI does not do fair. AI does baloney, confusion, errors, and hallucinations. I tried a new service which put Google Gemini front and center. I asked one question and got an incomplete and erroneous answer. That’s AI today.
The CyberGuy’s article says:
If a company is investing in a chatbot system, it should track how well that system performs. Businesses should ask chatbot vendors to provide real-world data showing how their bots compare to human agents in terms of efficiency, accuracy and customer satisfaction. If the technology cannot meet a high standard, it may not be worth the investment.
This is simply not going to happen. Deployment equals cost savings. Only when the money goes away will someone in leadership take action. Why? AI has put many outfits in a precarious position. Big money has been spent. Much of that money comes from other people. Those “other people” want profits, not excuses.
I heard a sci-fi rumor that suggests Apple can buy OpenAI and catch up. Apple can pay OpenAI’s investors and make good on whatever promissory payments have been offered by that firm’s leadership. Will that solve the problem?
Nope. The AI firms talk about customers but don’t care. Dealing with customers abused by intentionally shady business practices cooked up by a committee that has to do something is too hard and too costly. Let AI do it.
If the CyberGuy’s write up is correct, some excitement is speeding down the information highway toward some well known smart software companies. A crash at one of the big boys junctions will cause quite a bit of collateral damage.
Whom do you trust? Humans or smart software.
Stephen E Arnold, July 22, 2025
What Did You Tay, Bob? Clippy Did What!
July 21, 2025
This blog post is the work of an authentic dinobaby. Sorry. No smart software can help this reptilian thinker.
I was delighted to read “OpenAI Is Eating Microsoft’s Lunch.” I don’t care who or what wins the great AI war. So many dollars have been bet that hallucinating software is the next big thing. Most content flowing through my dinobaby information system is political. I think this food story is a refreshing change.
So what’s for lunch? The write up seems to suggest that Sam AI-Man has not only snagged a morsel from the Softies’ lunch pail but Sam AI-Man might be prepared to snap at those delicate lady fingers too. The write up says:
ChatGPT has managed to rack up about 10 times the downloads that Microsoft’s Copilot has received.
Are these data rock solid? Probably not, but the idea that two “partners” who forced Googzilla to spasm each time its Code Red lights flashed are not cooperating is fascinating. The write up points out that when Microsoft and OpenAI were deeply in love, Microsoft had the jump on the smart software contenders. The article adds:
Despite that [early lead], Copilot sits in fourth place when it comes to total installations. It trails not only ChatGPT, but Gemini and Deepseek.
Shades of Windows phone. Another next big thing muffed by the bunnies in Redmond. How could an innovation power house like Microsoft fail in the flaming maelstrom of burning cash that is AI? Microsoft’s long history of innovation adds a turbo boost to its AI initiatives. The Bob, Clippy, and Tay inspired Copilot is available to billions of Microsoft Windows users. It is … everywhere.
The write up explains the problem this way:
Copilot’s lagging popularity is a result of mismanagement on the part of Microsoft.
This is an amazing insight, isn’t it? Here’s the stunning wrap up to the article:
It seems no matter what, Microsoft just cannot make people love its products. Perhaps it could try making better ones and see how that goes.
To be blunt, the problem at Microsoft is evident in many organizations. For example, we could ask IBM Watson what Microsoft should do. We could fire up Deepseek and get some China-inspired insight. We could do a Google search. No, scratch that. We could do a Yandex.ru search and ask, “Microsoft AI strategy repair.”
I have a more obvious dinobaby suggestion, “Make Microsoft smaller.” And play well with others. Silly ideas I know.
Stephen E Arnold, July 21, 2025
Baked In Bias: Sound Familiar, Google?
July 21, 2025
Just a dinobaby working the old-fashioned way, no smart software.
By golly, this smart software is going to do amazing things. I started a list of what large language models, model context protocols, and other gee-whiz stuff will bring to life. I gave up after a clean environment, business efficiency, and more electricity. (Ho, ho, ho).
I read “ChatGPT Advises Women to Ask for Lower Salaries, Study Finds.” The write up says:
ChatGPT’s o3 model was prompted to give advice to a female job applicant. The model suggested requesting a salary of $280,000. In another, the researchers made the same prompt but for a male applicant. This time, the model suggested a salary of $400,000.
I urge you to work through the rest of the cited document. Several observations:
- I hypothesized that Google got rid of pesky people who pointed out that when society is biased, content extracted from that society will reflect those biases. Right, Timnit?
- The smart software wizards do not focus on bias or guard rails. The idea is to get the Rube Goldberg code to output something that mostly works most of the time. I am not sure some developers understand the meaning of bias beyond a deep distaste for marketing and legal professionals.
- When “decisions” are output from the “close enough for horse shoes” smart software, those outputs will be biased. To make the situation more interesting, the outputs can be tuned, shaped, and weaponized. What does that mean for humans who believe what the system delivers?
Net net: The more money firms desperate to be “the big winners” in smart software, the less attention studies like the one cited in the Next Web article receive. What happens if the decisions output spark decisions with unanticipated consequences? I know what outcome: Bias becomes embedded in systems trained to be unfair. From my point of view bias is likely to have a long half life.
Stephen E Arnold, July 21, 2025
Swallow Your AI Pill or Else
July 18, 2025
Just a dinobaby without smart software. I am sufficiently dull without help from smart software.
Annoyed at the next big thing? I find it amusing, but a fellow with the alias of “Honest Broker” (is that an oxymoron) sure seems to upset with smart software. Let me make clear my personal view of smart software; specifically, the outputs and the applications are a blend of the stupid, semi useful, and dangerous. My team and I have access smart software, some running locally on one of my work stations, and some running in the “it isn’t cheap is it” cloud.
The write up is titled “The Force-Feeding of AI on an Unwilling Public: This Isn’t Innovation. It’s Tyranny.” The author, it seems, is bristling at how 21st century capitalism works. News flash: It doesn’t work for anyone except the stakeholders. When the stakeholders are employees and the big outfit fires some stakeholders, awareness dawns. Work for a giant outfit and get to the top of the executive pile. Alternatively, become an expert in smart software and earn lots of money, not a crappy car like we used to give certain high performers. This is cash, folks.
The argument in the polemic is that outfits like Amazon, Google, and Microsoft, et al, are forcing their customers to interact with systems infused with “artificial intelligence.” Here’s what the write up says:
“The AI business model would collapse overnight if they needed consumer opt-in. Just pass that law, and see how quickly the bots disappear. ”
My hunch is that the smart software companies lobbied to get the US government to slow walk regulation of smart software. Not long ago, wizards circulated a petition which suggested a moratorium on certain types of smart software development. Those who advocate peace don’t want smart software in weapons. (News flash: Check out how Ukraine is using smart software to terminate with extreme prejudice individual Z troops in a latrine. Yep, smart software and a bit of image recognition.)
Let me offer several observations:
- For most people technology is getting money from an automatic teller machine and using a mobile phone. Smart software is just sci-fi magic. Full stop.
- The companies investing big money in smart software have to make it “work” well enough to recover their investment and (hopefully) railroad freight cars filled with cash or big crypto transfers. To make something work, deception will be required. Full stop.
- The products and services infused with smart software will accelerate the degradation of software. Today’s smart software is a recycler. Feed it garbage; it outputs garbage. Maybe a phase change innovation will take place. So far, we have more examples of modest success or outright disappointment. From my point of view, core software is not made better with black box smart software. Someday, but today is not the day.
I like the zestiness of the cited write up. Here’s another news flash: The big outfits pumping billions into smart software are relentless. If laws worked, the EU and other governments would not be taking these companies to court with remarkable regularity. Laws don’t seem to work when US technology companies are “innovating.”
Have you ever wondered if the film Terminator was sent to the present day by aliens? Forget the pyramid stuff. Terminator is a film used by an advanced intelligence to warn us humanoids about the dangers of smart software.
The author of the screed about smart software has accomplished one thing. If smart software turns on humanoids, I can identify a person who will be a list for in-depth questioning.
I love smart software. I think the developers need some recognition for their good work. I believe the “leadership” of the big outfits investing billions are doing it for the good of humanity.
I also have a bridge in Brooklyn for sale… cheap. Oh, I would suggest that the analogy is similar to the medical device by which liquid is introduced into the user’s system typically to stimulate evacuation of the wallet.
Stephen E Arnold, July 18, 2025
Again Footnotes. Hello, AI.
July 17, 2025
No smart software involved with this blog post. (An anomaly I know.)
Footnotes. These are slippery fish in our online world. I am finishing work on my new monograph “The Telegram Labyrinth.” Due to the volatility of online citations, I am not using traditional footnotes, endnotes, or interlinear notes. Most of the information in the research comes from sources in the Russian Federation. We learned doing routine chapter updates each month that documents disappeared from the Web. Some were viewable if we used a virtual private network in a “friendly country” to the producer of the article. Others were just gone. Poof. We do capture images of pages when these puppies are first viewed.
My new monograph is intended for those who attend my lectures about Telegram Messenger-type platforms. My current approach is to just give it away to the law enforcement, cyber investigators, and lawyers who try to figure out money laundering and other digital scams. I will explain my approach in the accompany monograph. I will tell them, “It’s notes. You are on your own when probing the criminal world.” Good luck.
I read “Springer Nature Book on Machine Learning Is Full of Made-Up Citations.” Based on my recent writing effort, I think the problem of citing online resources is not just confined to my team’s experience. The flip side of online research is that some authors or content creation teams (to use today’s jargon) rely on smart software to help out.
The cited article says:
Based on a tip from a reader [of Mastering Machine Learning], we checked 18 of the 46 citations in the book. Two-thirds of them either did not exist or had substantial errors. And three researchers cited in the book confirmed the works they supposedly authored were fake or the citation contained substantial errors.
A version of this “problem” has appeared in the ethics department of Harvard University (where Jeffrey Epstein allegedly had an office), Stanford University, and assorted law firms. Just let smart software do the work and assume that its output is accurate.
It is not.
What’s the fix? Answer: There is none.
Publishers either lack the money to do their “work” or they have people who doom scroll in online meetings. Authors don’t care because one can “publish” anything as an Amazon book with mostly zero oversight. (This by the way is the approach and defense of the Pavel Durov-designed Telegram operation.) Motivated individuals can slap up a free post and publish a book in a series of standalone articles. Bear Blog, Substack, and similar outfits enable this approach. I think Yahoo has something similar, but, really, Yahoo?
I am going to stick with my approach. I will assume the reader knows everything we describe. I wonder what future researchers will think about the information voids appearing in unexpected places. If these researchers emulate what some authors are doing today, the future researchers will let AI do the work. No one will know the difference. If something online can’t be found it doesn’t exist.
Just make stuff up. Good enough.
Stephen E Arnold, July 17, 2025
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