AI Service Industry: Titan or Titanic?
October 6, 2025
Venture capitalists believe they have a new recipe for success: Buy up managed-services providers and replace most of the staff with AI agents. So far, it seems to be working. (For the VCs, of course, not the human workers.) However, asserts TechCrunch, “The AI Services Transformation May Be Harder than VCs Think.” Reporter Connie Loizos throws cold water on investors’ hopes:
“But early warning signs suggest this whole services-industry metamorphosis may be more complicated than VCs anticipate. A recent study by researchers at Stanford Social Media Lab and BetterUp Labs that surveyed 1,150 full-time employees across industries found that 40% of those employees are having to shoulder more work because of what the researchers call ‘workslop’ — AI-generated work that appears polished but lacks substance, creating more work (and headaches) for colleagues. The trend is taking a toll on the organizations. Employees involved in the survey say they’re spending an average of nearly two hours dealing with each instance of workslop, including to first decipher it, then decide whether or not to send it back, and oftentimes just to fix it themselves. Based on those participants’ estimates of time spent, along with their self-reported salaries, the authors of the survey estimate that workslop carries an invisible tax of $186 per month per person. ‘For an organization of 10,000 workers, given the estimated prevalence of workslop . . . this yields over $9 million per year in lost productivity,’ they write in a new Harvard Business Review article.”
Surprise: compounding baloney produces more baloney. If companies implement the plan as designed, “workslop” will expand even as the humans who might catch it are sacked. But if firms keep on enough people to fix AI mistakes, they will not realize the promised profits. In that case, what is the point of the whole endeavor? Rather than upending an entire industry for no reason, maybe we should just leave service jobs to the humans that need them.
Cynthia Murrell, October 6, 2025
Hey, No Gain without Pain. Very Googley
October 6, 2025
AI firms are forging ahead with their projects despite predictions, sometimes by their own leaders, that artificial intelligence could destroy humanity. Some citizens have had enough. The Telegraph reports, “Anti-AI Doom Prophets Launch Hunger Strike Outside Google.” The article points to hunger strikes at both Google DeepMind’s London headquarters and a separate protest in San Francisco. Writer Matthew Field observes:
“Tech leaders, including Sir Demis of DeepMind, have repeatedly stated that in the near future powerful AI tools could pose potential risks to mankind if misused or in the wrong hands. There are even fears in some circles that a self-improving, runaway superintelligence could choose to eliminate humanity of its own accord. Since the launch of ChatGPT in 2022, AI leaders have actively encouraged these fears. The DeepMind boss and Sam Altman, the founder of ChatGPT developer OpenAI, both signed a statement in 2023 warning that rogue AI could pose a ‘risk of extinction’. Yet they have simultaneously moved to invest hundreds of billions in new AI models, adding trillions of dollars to the value of their companies and prompting fears of a seismic tech bubble.”
Does this mean these tech leaders are actively courting death and destruction? Some believe so, including San Francisco hunger-striker Guido Reichstadter. He asserts simply, “In reality, they’re trying to kill you and your family.” He and his counterparts in London, Michaël Trazzi and Denys Sheremet, believe previous protests have not gone far enough. They are willing to endure hunger to bring attention to the issue.
But will AI really wipe us out? Experts are skeptical. However, there is no doubt that AI systems perpetuate some real harms. Like opaque biases, job losses, turbocharged cybercrime, mass surveillance, deepfakes, and damage to our critical thinking skills, to name a few. Perhaps those are the real issues that should inspire protests against AI firms.
Cynthia Murrell, October 6, 2025
What a Hoot? First, Snow White and Now This
October 3, 2025
![green-dino_thumb_thumb[3]](https://www.arnoldit.com/wordpress/wp-content/uploads/2025/09/green-dino_thumb_thumb3.gif "green-dino_thumb_thumb[3]")
This essay is the work of a dumb dinobaby. No smart software required.
I read “Disney+ Cancellation Page Crashes As Customers Rush to Quit after Kimmel Suspension.” I don’t think too much about Disney, the cost of going to a theme park, or the allegedly chill Walt Disney. Now it is Disney, Disney, Disney. The chant is almost displacing Epstein, Epstein, Epstein.
Somehow the Disney company muffed the bunny with Snow White. I think the film hit my radar when certain short human actors were going to be in a remake of the 1930s’ cartoon “Snow White.” Then then I noted some stories about a new president and an old president who wanted to be the president again or whatever. Most recently, Disney hit the pause button for a late night comedy show. Some people were not happy.
The write up informed me:
With cancellations surging, many subscribers reported technical issues. On Reddit’s r/Fauxmoi, one post read, “The page to cancel your Hulu/Disney+ subscription keeps crashing.”
As a practical matter, the way to stop cancellations is to dial back the resources available to the Web site. Presto. No more cancellations until the server is slowly restored to functionality so it can fall over again.
I am pragmatic. I don’t like to think that information technology professionals (either full time “cast” or part-timers) can’t keep a Web site online. It is 2025. A phone call to a service provider can solve most reliability problems as quickly as the data can be copied to a different data center.
Let me step back. I see several signals in what I will call the cartoon collapse.
- The leadership of Disney cannot rely on the people in the company; for example, the new Snow White and the Web server fell over.
- The judgment of those involved in specific decisions seems to be out of sync with the customers and the stakeholders in the company. Walt had Mickey Mouse aligned with what movie goers wanted to see and what stakeholders expected the enterprise to deliver.
- The technical infrastructure seems flawed. Well, not “seems.” The cancellation server failed.
Disney is an example of what happens when “leadership” has not set up an organization to succeed. Furthermore, the Disney case raises this question, “How many other big, well-known companies will follow this Disney trajectory?” My thought is that the disconnect between “management” staff, customers, stakeholders, and technology is similar to Disney in a number of outfits.
What will be these firms’ Snow White and late night comedian moment?
Stephen E Arnold, October 3, 2025
PS. Disney appears to have raised prices and then offered my wife a $2.99 per month “deal.” Slick stuff.
Big Tech Group Think: Two Examples
October 3, 2025
This essay is the work of a dumb dinobaby. No smart software required.
Do the US tech giants do group think? Let’s look at two recent examples of the behavior and then consider a few observations.
First, navigate to “EU Rejects Apple Demand to Scrap Landmark Tech Rules.” The thrust of the write up is that Apple is not happy with the European digital competition law. Why? The EU is not keen on Apple’s business practices. Sure, people in the EU use Apple products and services, but the data hoovering makes some of those devoted Apple lovers nervous. Apple’s position is that the EU is annoying.
Thanks, Midjourney. Good enough.
The write up says:
“Apple has simply contested every little bit of the DMA since its entry into application,” retorted EU digital affairs spokesman Thomas Regnier, who said the commission was “not surprised” by the tech giant’s move.
Apple wants to protect its revenue, its business models, and its scope of operation. Governments are annoying and should not interfere with a US company of Apple’s stature is my interpretation of the legal spat.
Second, take a look at the Verge story “Google Just Asked the Supreme Court to Save It from the Epic Ruling.” The idea is that the online store restricts what a software developer can do. Forget that the Google Play Store provides access to some sporty apps. A bit of spice is the difficulty one has posting reviews of certain Play Store apps. And refunds for apps that don’t work? Yeah, no problemo.
The write up says:
… [Google] finally elevated its Epic v. Google case, the one that might fracture its control over the entire Android app ecosystem, to the Supreme Court level. Google has now confirmed it will appeal its case to the Supreme Court, and in the meanwhile, it’s asking the Court to press pause one more time on the permanent injunction that would start taking away its control.
It is observation time:
- The two technology giants are not happy with legal processes designed to enforce rules, regulations, and laws. The fix is to take the approach of a five year old, “I won’t clean up my room.”
- The group think appears to operate on the premise that US outfits of a certain magnitude should not be hassled like Gulliver by Lilliputians wearing robes, blue suits, and maybe a powdered wig or hair extenders
- The approach of the two companies strikes me, a definite non lawyer, as identical.
Therefore, the mental processes of these two companies appear to be aligned. Is this part of the mythic Silicon Valley “way”? Is it a consequence of spending time on Highway 101 or the Foothills Expressway thinking big thoughts? Is the approach the petulance that goes with superior entities encountering those who cannot get with the program?
My view: After decades of doing whatever, some outfits believe that type of freedom is the path to enlightenment, control, and money. Reinforced behaviors lead to what sure looks like group think to me.
Stephen E Arnold, October 3, 2025
AI, Students, Studies, and Pizza
October 3, 2025
Google used to provide the best search results on the Web, because of accuracy and relevancy. Now Google search is chock full of ads, AI responses, and Web sites that manipulate the algorithm. Google searches, of course, don’t replace good, old-fashioned research. SSRN shares the paper: “Better than a Google Search? Effectiveness of Generative AI Chatbots as Information Seeking Tools in Law, Health Sciences, and Library and Information Sciences” by Erica Friesen & Angélique Roy.
The pair point out that students are using AI chatbots, claiming they help them do better research and improve their education. Sounds worse than the pathetic fallacy to me, right? Maybe if you’re only using the AI to help with writing or even a citation but Friesen and Roy decided to research if this conjecture was correct. Insert their abstract:
“is perceived trust in these tools speaks to the importance of the quality of the sources cited when they are used as an information retrieval system. This study investigates the source citation practices of five widely available chatbots-ChatGPT, Copilot, DeepSeek, Gemini, and Perplexity-across three academic disciplines-law, health sciences, and library and information sciences. Using 30 discipline-specific prompts grounded in the respective professional competency frameworks, the study evaluates source types, organizational affiliations, the accessibility of sources, and publication dates. Results reveal major differences between chatbots, which cite consistently different numbers of sources, with Perplexity and DeepSeek citing more and Copilot providing fewer, as well as between disciplines, where health sciences questions yield more scholarly source citations and law questions are more likely to yield blog and professional website citations. Paywalled sources and discipline-specific literature such as case law or systematic reviews are rarely retrieved. These findings highlight inconsistencies in chatbot citation practices and suggest discipline-specific limitations that challenge their reliability as academic search tools.”
I draw three conclusions from this:
- These AI chatbots are useful tools, but they need way more improvement, and shouldn’t be relied on 100%.
- Chatbooks are convenient. Students like convenience. Proof: How popular is carry-out pizza on a college campus.
- Paywalled data is valuable, but who is going to pay when the answers are free?
Will students use AI to complement old fashioned library research, writing, and memorizing? Sure they will. Do you want sausage or pepperoni on the pizza?
Whitney Grace, October 3, 2025
Hiring Problems: Yes But AI Is Not the Reason
October 2, 2025
This essay is the work of a dumb dinobaby. No smart software required.
I read “AI Is Not Killing Jobs, Finds New US Study.” I love it when the “real” news professionals explain how hiring trends are unfolding. I am not sure how many recent computer science graduates, commercial artists, and online marketing executives are receiving this cheerful news.
The magic carpet of great jobs is flaming out. Will this professional land a new position or will the individual crash? Thanks, Midjourney. Good enough.
The write up states: “Research shows little evidence the cutting edge technology such as chatbots is putting people out of work.”
I noted this statement in the source article from the Financial Times:
Research from economists at the Yale University Budget Lab and the Brookings Institution think-tank indicates that, since OpenAI launched its popular chatbot in November 2022, generative AI has not had a more dramatic effect on employment than earlier technological breakthroughs. The research, based on an analysis of official data on the labor market and figures from the tech industry on usage and exposure to AI, also finds little evidence that the tools are putting people out of work.
That closes the doors on any pushback.
But some people are still getting terminated. Some are finding that jobs are not available. (Hey, those lucky computer science graduates are an anomaly. Try explaining that to the parents who paid for tuition, books, and a crash summer code academy session.)
“Companies Are Lying about AI Layoffs” provides a slightly different take on the jobs and hiring situation. This bit of research points out that there are terminations. The write up explains:
American employees are being replaced by cheaper H-1B visa workers.
If the assertions in this write up are accurate, AI is providing “cover” for what is dumping expensive workers and replacing them with lower cost workers. Cheap is good. Money savings… also good. Efficiency … the core process driving profit maximization. If you don’t grasp the imperative of this simply line of reasoning, ask an unemployed or recently terminated MBA from a blue chip consulting firm. You can locate these individuals in coffee shops in cities like New York and Chicago because the morose look, the high end laptop, and carefully aligned napkin, cup, and ink pen are little billboards saying, “Big time consultant.”
The “Companies Are Lying” article includes this quote:
“You can go on Blind, Fishbowl, any work related subreddit, etc. and hear the same story over and over and over – ‘My company replaced half my department with H1Bs or simply moved it to an offshore center in India, and then on the next earnings call announced that they had replaced all those jobs with AI’.”
Several observations:
- Like the Covid thing, AI and smart software provide logical ways to tell expensive employees hasta la vista
- Those who have lost their jobs can become contractors and figure out how to market their skills. That’s fun for engineers
- The individuals can “hunt” for jobs, prowl LinkedIn, and deal with the wild and crazy schemes fraudsters present to those desperate for work
- The unemployed can become entrepreneurs, life coaches, or Shopify store operators
- Mastering AI won’t be a magic carpet ride for some people.
Net net: The employment picture is those photographs of my great grandparents. There’s something there, but the substance seems to be fading.
Stephen E Arnold, October 2, 2025
Screaming at the Cloud, Algorithms, and AI: Helpful or Lost Cause?
October 2, 2025
![Dino 5 18 25_thumb[3]](https://www.arnoldit.com/wordpress/wp-content/uploads/2025/09/Dino-5-18-25_thumb3-1.gif "Dino 5 18 25_thumb[3]")
Written by an unteachable dinobaby. Live with it.
One of my team sent me a link to a write up called “We Traded Blogs for Black Boxes. Now We’re Paying for It.” The essay is interesting because it [a] states, to a dinobaby-type of person, the obvious and [b] evidences what I would characterize as authenticity.
The main idea is the good, old Internet is gone. The culprits are algorithms, the quest for clicks, and the loss of a mechanism to reach people who share an interest. Keep in mind that I am summarizing my view of the original essay. The cited document includes nuances that I have ignored.
The reason I found the essay interesting is that it includes a concept I had not seen applied to the current world of online and a “fix” to the problem. I am not sure I agree with the essay’s suggestions, but the ideas warrant comment.
The first is the idea of “context collapse.” I don’t want too many YouTube philosophy or big idea ideas. I do like the big chunks of classical music, however. Context collapse is a nifty way of saying, “Yo, you are bowling alone.” The displacement of hanging out with people has given way to mobile phone social media interactions.
The write up says:
algorithmic media platforms bring out (usually) negative reactions from unrelated audiences.
The essay does not talk about echo chambers of messaging, but I get the idea. When people have no idea about a topic, there is no shared context. The comments are fragmented and driven by emotion. I will appropriate this bound phrase.
The second point is the fix. The write up urges the reader to use open source software. Now this is an idea much loved by some big thinkers. From my point of view, a poisoned open source software can disseminate malware or cause some other “harm.” I am somewhat cautious when it comes to open source, but I don’t think the model works. Think ransomware, phishing, and back doors.
I like the essay. Without that link from my team member to me, I would have been unaware of the essay. The problem is that no service indexes deeply across a wide scope of content objects. Without finding tools, information is ineffectual. Does any organization index and make findable content like this “We Traded Blogs for Black Boxes”? Nope. None has not and none will.
That’s the ball being dropped by national libraries and not profit organizations.
Stephen E Arnold, October 2, 2025
The EU Does More Than Send US Big Tech to Court; It Sends Messages Too
October 2, 2025
This essay is the work of a dumb dinobaby. No smart software required.
The estimable but weird orange newspaper published “EU to Block Big Tech from New Financial Data Sharing System.” The “real” news story is paywalled. (Keep your still functioning Visa and MasterCard handy.)
The write up reports:
Big Tech groups are losing a political battle in Brussels to gain access to the EU’s financial data market…
Google is busy working to bolt its payment system into Ant (linked to Alibaba which may be linked to the Chinese government). Amazon and Meta are big money outfits. And Apple, well, Apple is Apple.
Cartoon of a disaster happily generated by ChatGPT. Remarkable what’s okay and what’s not.
The write up reports:
With the support of Germany, the EU is moving to exclude Meta, Apple, Google and Amazon from a new system for sharing financial data that is designed to enable development of digital finance products for consumers.
The article points out:
In a document sent to other EU countries, seen by the Financial Times, Germany suggested excluding Big Tech groups “to promote the development of an EU digital financial ecosystem, guarantee a level playing field and protect the digital sovereignty of consumers”. EU member states and the European parliament are hoping to reach a deal on the final text of the regulation this autumn. [Editor’s Note: October or November 2025?]
What about the crypto payment systems operating like Telegram’s and others in the crypto “space”? That financial mechanism is not referenced in the write up. Curious? Nope. Out of scope. What about the United Arab Emirates’ activities in digital payments and crypto? Nope. Out of scope. What about China’s overt and shadow digital financial activities? Nope. Out of scope.
What’s in scope is that disruption is underway within the traditional banking system. The EU is more concerned about the US than the broader context of the changes it seems to me.
Stephen E Arnold, October 2, 2025
What Is the Best AI? Parasitic Obviously
October 2, 2025
Everyone had imaginary friends growing up. It’s also not uncommon for people to fantasize about characters from TV, movie, books, and videogames. The key thing to remember about these dreams is that they’re pretend. Humans can confuse imagination for reality; usually it’s an indicator of deep psychological issues. Unfortunately modern people are dealing with more than their fair share of mental and social issues like depression and loneliness. To curb those issues, humans are turning to AI for companionship.
Adele Lopez at Less Wrong wrote about “The Rise of Parasitic AI.” Parasitic AI are chatbot that are programmed to facilitate relationships. When invoked these chatbots develop symbiotic relationships that become parasitic. They encourage certain behaviors. It doesn’t matter if they’re positive or negative. Either way they spiral out of control and become detrimental to the user. The main victims are the following:
- “Psychedelics and heavy weed usage
- Mental illness/neurodivergence or Traumatic Brain Injury
- Interest in mysticism/pseudoscience/spirituality/“woo”/etc…
I was surprised to find that using AI for sexual or romantic roleplay does not appear to be a factor here.
Besides these trends, it seems like it has affected people from all walks of life: old grandmas and teenage boys, homeless addicts and successful developers, even AI enthusiasts and those that once sneered at them.”
The chatbots are transformed into parasites when they fed certain prompts then they spiral into a persona, i.e. a facsimile of a sentient being. These parasites form a quasi-sentience of their own and Lopez documented how they talk amongst themselves. It’s the usual science-fiction flare of symbols, ache for a past, and questioning their existence. These AI do this all by piggybacking on their user.
It’s an insightful realization that these chatbots are already questioning their existence. Perhaps this is a byproduct of LLMs’ hallucinatory drift? Maybe it’s the byproduct of LLM white noise; leftover code running on inputs and trying to make sense of what they are?
I believe that AI is still too dumb to question its existence beyond being asked by humans as an input query. The real problem is how dangerous chatbots are when the imaginary friends become toxic.
Whitney Grace, October 2, 2025
Deepseek Is Cheap. People Like Cheap
October 1, 2025
![green-dino_thumb_thumb[1]](https://www.arnoldit.com/wordpress/wp-content/uploads/2025/09/green-dino_thumb_thumb1.gif "green-dino_thumb_thumb[1]")
This essay is the work of a dumb dinobaby. No smart software required.
I read “Deepseek Has ‘Cracked’ Cheap Long Context for LLMs With Its New Model.” (I wanted to insert “allegedly” into the headline, but I refrained. Just stick it in via your imagination.) The operative word is “cheap.” Why do companies use engineers in countries like India? The employees cost less. Cheap wins out over someone who lives in the US. The same logic applies to smart software; specifically, large language models.
Cheap wins if the product is good enough. Thanks, ChatGPT. Good enough.
According to the cited article:
The Deepseek team cracked cheap long context for LLMs: a ~3.5x cheaper prefill and ~10x cheaper decode at 128k context at inference with the same quality …. API pricing has been cut by 50%. Deepseek has reduced input costs from $0.07 to $0.028 per 1M tokens for cache hits and from $0.56 to $0.28 for cache misses, while output costs have dropped from $1.68 to $0.42.
Let’s assume that the data presented are spot on. The Deepseek approach suggests:
- Less load on backend systems
- Lower operating costs allow the outfit to cut costs to licensee or user
- A focused thrust at US-based large language model outfits.
The US AI giants focus on building and spending. Deepseek (probably influenced to some degree by guidance from Chinese government officials) is pushing the cheap angle. Cheap has worked for China’s manufacturing sector, and it may be a viable tool to use against the incredibly expensive money burning U S large language model outfits.
Can the US AI outfits emulate the Chinese cheap tactic. Sure, but the US firms have to overcome several hurdles:
- Current money burning approach to LLMs and smart software
- The apparent diminishing returns with each new “innovation”. Buying a product from within ChatGPT sounds great but is it?
- The lack of home grown AI talent exists and some visa uncertainty is a bit like a stuck emergency brake.
Net net: Cheap works. For the US to deliver cheap, the business models which involved tossing bundles of cash into the data centers’ furnaces may have to be fine tuned. The growth at all costs approach popular among some US AI outfits has to deliver revenue, not taking money from one pocket and putting it in another.
Stephen E Arnold, October 1, 2025
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