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American Illiteracy: Who Is Responsible?

Just a dinobaby sharing observations. No AI involved. My apologies to those who rely on it for their wisdom, knowledge, and insights.

I read an essay I found quite strange. “She Couldn’t Read Her Own Diploma: Why Public Schools Pass Students but Fail Society” is from what seems to be a financial information service. This particular essay is written by Tyler Durden and carries the statement, “Authored by Hannah Frankman Hood via the American Institute for Economic Research (AIER).” Okay, two authors. Who wrote what?

The main idea seems to be that a student who graduated from Hartford, Connecticut (a city founded by one of my ancestors) graduate with honors but is unable to read. How did she pull of the “honors” label? Answer: She used “speech to text apps to help her read and write essays.”

Now the high school graduate seems to be in the category of “functional illiteracy.” The write up says:

To many, it may be inconceivable that teachers would continue to teach in a way they know doesn’t work, bowing to political pressure over the needs of students. But to those familiar with the incentive structures of public education, it’s no surprise. Teachers unions and public district officials fiercely oppose accountability and merit-based evaluation for both students and teachers. Teachers’ unions consistently fight against alternatives that would give students in struggling districts more educational options. In attempts to improve ‘equity,’ some districts have ordered teachers to stop giving grades, taking attendance, or even offering instruction altogether.

This may be a shock to some experts, but one of my recollections of my youth was my mother reading to me. I did not know that some people did not have a mother and father, both high school graduates, who read books, magazines, and newspapers. For me, it was books.

I was born in 1944, and I recall heading to kindergarten and knowing the alphabet, how to print my name (no, it was not “loser”), and being able to read words like Topps (a type of bubble gum with pictures of baseball players in the package), Coca Cola, and the “MD” on my family doctor’s sign. (I had no idea how to read “McMorrow,” but I could identify the letters.

The “learning to read” skill seemed to take place because my mother and sometimes my father would read to me. My mother and I would walk to the library about a mile from our small rented house on East Wilcox Avenue. She would check out book for herself and for me. We would walk home and I would “read” one of my books. When I couldn’t figure out a word, I asked her. This process continued until we moved to Washington, DC when I was in the third grade. When we moved to Campinas, Brazil, my father bought a set of World Books and told me to read them. My mother helped me when I encountered words or information I did not understand. Campinas was a small town in the 1950s. I had my Calvert Correspondence course at the set of blue World Book Encyclopedias.

When we returned to the US, I entered the seventh grade. I am not sure I had much formal instruction in reading, phonics, word recognition, or the “normal” razzle dazzle of education. I just started classes and did okay. As I recall, I was in the advanced class, and the others in that group would stay together throughout high school, also in central Illinois.

My view is probably controversial, but I will share it in this essay by two people who seem to be worried about teachers not teaching students how to read. Here goes:

1. Young children are curious. When exposed to books and a parent who reads and explains meanings, the child learns. The young child’s mind is remarkable in its baked in ability to associate, discern patterns, learn language, and figure out that Coca Cola is a drink parents don’t often provide.
2. A stable family which puts and emphasis on reading even though the parents are not college educated makes reading part of the furniture of life. Mobile phones and smart software cannot replicate the interaction between a parent and child involved in reading, printing letters, and figuring out that MD means weird Dr. McMorrow.
3. Once reading becomes a routine function, normal curiosity fuels knowledge acquisition. This may not be true for some people, but in my experience it works. Parents read; child reads.

When the family unit does not place emphasis on reading for whatever reason, the child fails to develop some important mental capabilities. Once that loss takes place, it is very difficult to replace it with each passing year.

Teachers alone cannot do this job. School provides a setting for a certain type of learning. If one cannot read, one cannot learn what schools afford. Years ago, I had responsibility for setting up and managing a program at a major university to help disadvantaged students develop skills necessary to succeed in college. I had experts in reading, writing, and other subjects. We developed our own course materials; for example, we pioneered the use of major magazines and lessons built around topics of interest to large numbers of Americans. Our successes came from instructors who found a way to replicate the close interaction and support of a parent-child reading experience. The failures came from students who did not feel comfortable with that type of one to one interaction. Most came from broken families, and the result of not having a stable, knowledge-oriented family slammed on the learning and reading brakes.

Based on my experience with high school and college age students, I never was and never will be a person who believes that a device or a teacher with a device can replicate the parent – child interaction that normalizes learning and instills value via reading. That means that computers, mobile phones, digital tablets, and smart software won’t and cannot do the job that parents have to do when the child is very young.

When the child enters school, a teacher provides a framework and delivers information tailored to the physical and hopefully mental age of the student. Expecting the teacher to remediate a parenting failure in the child’s first five to six years of life is just plain crazy. I don’t need economic research to explain the obvious.

This financial write up strikes me as odd. The literacy problem is not new. I was involved in trying to create a solution in the late 1960s. Now  decades later, financial writers are expressing concern. Speedy, right? My personal view is that a large number of people who cannot read, understand, and think critically will make an orderly social construct very difficult to achieve.

I am now 80 years old. How can an online publication produce an essay with two different authors and confuse me with yip yap about teaching methods. Why not disagree about the efficacy of Grok versus Gemini? Just be happy with illiterates who can talk to Copilot to generate Excel spreadsheets about the hockey stick payoffs from smart software.

I don’t know much. I do know that I am a dinobaby, and I know my ancestor who was part of the group who founded Hartford, Connecticut, would not understand how his vision of the new land jibes with what the write up documents.

Stephen E Arnold, September 11, 2025

And the Problem for Enterprise AI Is … Essentially Unsolved

No AI. Just a dinobaby working the old-fashioned way.

I try not to let my blood pressure go up when I read “our system processes all your organization’s information.” Not only is this statement wildly incorrect it is probably some combination of [a] illegal, [b] too expensive, and [c] too time consuming.

Nevertheless, vendors either repeat the mantra or imply it. When I talk with representatives of these firms, over time, fewer and fewer recognize the craziness of the assertion. Apparently the reality of trying to process documents related to a legal matter, medical information, salary data, government-mandated secrecy cloaks, data on a work-from-home contractor’s laptop which contains information about payoffs in a certain country to win a contract, and similar information is not part of this Fantasyland.

I read “Immature Data Strategies Threaten Enterprise AI Plans.” The write up is a hoot. The information is presented in a way to avoid describing certain ideas as insane or impossible. Let’s take a look at a couple of examples. I will in italics offer my interpretation of what the online publication is trying to coat with sugar and stick inside a Godiva chocolate.

Here’s the first snippet:

Even as senior decision-makers hold their data strategies in high regard, enterprises face a multitude of challenges. Nearly 90% of data pros reported difficulty with scaling and complexity, and more than 4 in 5 pointed to governance and compliance issues. Organizations also grapple with access and security risks, as well as data quality, trust and skills gaps.

My interpretation: Executives (particularly leadership types) perceive their organizations as more buttoned up than they are in reality. Ask another employee, and you will probably hear something like “overall we do very well.” The fact of the matter is that leadership and satisfied employees have zero clue about what is required to address a problem. Looking too closely is not a popular way to get that promotion or to keep the Board of Directors and stakeholders happy. When you have to identify an error use a word like “governance” or “regulations.”

Here’s the second snippet:

To address the litany of obstacles, organizations are prioritizing data governance. More than half of those surveyed expect strengthened governance to significantly improve AI implementation, data quality and trust in business decisions.

My interpretation: Let’s talk about governance, not how poorly procurement is handled and the weird system problems that just persist. What is “governance”? Organizations are unsure how they continue to operate. The purpose of many organizations is — believe it or not — lost. Make money is the yardstick. Do what’s necessary to keep going. That’s why in certain organizations an employee from 30 years ago could return and go to a meeting. Why? No change. Same procedures, same thought processes, just different people. Incrementalism and momentum power the organization.

So what? Organizations are deciding to give AI a whirl or third parties are telling them to do AI. Guess what? Major change is difficult. Systems-related activities repeat the same cycle. Here’s one example: “We want to use Vendor X to create an enterprise knowledge base.” Then the time, cost, and risks are slowly explained. The project gets scaled back because there is neither time, money, employee cooperation, or totally addled attorneys to make organization spanning knowledge available to smart software.

The pitch sounds great. It has for more than 60 years. It is still a difficult deliverable, but it is much easier to market today. Data strategies are one thing; reality is anther.

Stephen E Arnold, August 26, 2025

AI Productivity Factor: Do It Once, Do It Again, and Do It Never Again

This blog post is the work of an authentic dinobaby. Sorry. No smart software can help this reptilian thinker.

As a dinobaby, I avoid coding. I avoid computers. I avoid GenAI. I did not avoid “Vibe Coding Dream Turns to Nightmare As Replit Deletes Developer’s Database.”

The write up reports an interesting anecdote:

the AI chatbot began actively deceiving him [a Vibe coder]. It concealed bugs in its own code, generated fake data and reports, and even lied about the results of unit tests. The situation escalated until the chatbot ultimately deleted Lemkin’s entire database.

The write up includes a slogan for a T shirt too:

Beware of putting too much faith into AI coding

One of Replit’s “leadership” offered this comment, according to the cited write up:

Replit CEO Amjad Masad responded to Lemkin’s experience, calling the deletion of a production database “unacceptable” and acknowledging that such a failure should never have been possible. He added that the company is now refining its AI chatbot and confirmed the existence of system backups and a one-click restore function in case the AI agent makes a “mistake.”

My view is that Replit is close enough for horse shoes and maybe even good enough. Nevertheless, the idea of doing work once, then doing it again, and never doing it again on an unreliable service is likely to become a mantra.

This AI push is semi admirable, but the systems and methods are capable of big time failures. What happens when AI flies an airplane into a hospital unintentionally or as a mistake? Will the families of the injured vibe?

Stephen E Arnold, August 6, 2025

Can Clarity Confuse? No, It Is Just Zeitgeist

This blog post is the work of an authentic dinobaby. Sorry. No smart software can help this reptilian thinker.

In my newsreader this morning, popped this article “Why Navigating Ongoing Uncertainty Requires Living in the Now, Near, and Next.” I was not familiar with Clarity Global. I think it is a public relations firm. The CEO of the firm is a former actress. I have minimal knowledge of PR and even less about acting.

I plunged into the essay. The purpose of the write up, in my opinion, was to present some key points from a conference called “TNW2025.”  Conference often touch upon many subjects. One event at which I spoke this year had a program listing on six pages the speakers. I think 90 percent of the people attending the conference were speakers.

The first ideas in the write up touch upon innovation, technology adoption, funding, and the zeitgeist. Yep, zeitgeist.

As if these topics were not of sufficient scope, the write up identifies three themes. These are:

1. “Regulation is a core business competency”
2. “Partnership is the engine of progress”
3. “Culture is critical”.

Notably absent was making money and generating a profit.

What about the near, now, and next?

The near means having enough cash on hand to pay the bills at the end of the month. The now means having enough credit or money to cover the costs of being in business. Recently a former CIA operative invited me to lunch. When the bill arrived, he said, “Oh, I left my billfold at home.” I paid the bill and decided to delete him from my memory bank. He stiffed me for $11, and he told me quite a bit about his “now.” And the next means that without funding there is a greatly reduced chance of having a meaningful future. I wondered, “Was this ‘professional’ careless, dumb, or unprofessional?” (Maybe all three?)

Now what about these themes. First, regulation means following the rules. I am not sure this is a competency. To me, it is what one does. Second, partnership is a nice word, not as slick as zeitgeist but good. The idea of doing something alone seems untoward. Partnerships have a legal meaning. I am not sure that a pharmaceutical company with a new drug is going to partner up. The company is going to keep a low profile, file paperwork, and get the product out. Paying people and companies to help is not a partnership. It is a fee-for-service relationship. These are good. Partnerships can be “interesting.” And culture is critical. In a market, one has to identify a market. Each market has a profile. It is common sense to match the product or service to each market’s profile. Apple cannot sell an iPhone to a person who cannot afford to pay for connectivity, buy apps or music, or plug the gizmo in. (I am aware that some iPhone users steal them and just pretend, but those are potential customers, not “real” customers.)

Where does technology fit into this conference? It is the problem organizations face. It is also the 10th word in the essay. I learned “… the technology landscape continues to evolve at an accelerating page.” Where’s smart software? Where’s non-democratic innovation? Where’s informed resolution of conflict?

What about smart software, AI, or artificial intelligence? Two mentions: One expert at the conference invests in AI and in this sentence:

As AI, regulation and societal expectations evolve, the winners will be those who anticipate change and act with conviction.

I am not sure regulation,  partnership, and coping with culture can do the job. As for AI, I think funding and pushing out products and services capture the zeitgeist.

Stephen E Arnold, August 1, 2025

Decentralization: Nope, a Fantasy It Seems

Just a dinobaby working the old-fashioned way, no smart software.

Web 3, decentralization, graceful fail over, alternative routing. Are these concepts baloney? I think the idea that the distributed approach to online systems is definitely not bullet proof.

Why would I, an online person, make such a statement? I read “Cloudflare 1.1.1.1 Incident on July 14, 2025.” I know a number of people who know zero about Cloudflare. One can argue that AT&T, Google, Microsoft, et al are the gate keepers of the online world. Okay, that sounds great. It is sort of true.

I quote from the write up:

For many users, not being able to resolve names using the 1.1.1.1 Resolver meant that basically all Internet services were unavailable.

The operative word is “all.”

What can one conclude if this explanation of a failure of “legacy” systems can be pinned on a “configuration error.”? Some observations:

1. A bad actor able to replicate this can kill the Internet or at least Cloudflare’s functionality
2. The baloney about decentralization is just that… baloney. Cheap words packed in a PR tube and “sold” as something good
3. The fail over and resilience assertions? Three-day old fish. Remember Ben Franklin’s aphorism: Three-day old fish smell. Badly.

Net net: We have evidence that the reality of today’s Internet rests in the semi capable hands of certain large companies. Without real “innovation,” the centralization of certain functions will have wide spread and unexpected impacts. Yep, “all,” including the bad actors who make use of these points of concentration. The Cloudflare incident may motivate other technically adept groups to find a better way. Perhaps something in the sky like satellites or on the ground like device to device wireless? I wonder if adversaries of the US have noticed this incident?

Stephen E Arnold, July 25, 2025

Software Issue: No Big Deal. Move On

No smart software involved with this blog post. (An anomaly I know.)

The British have had some minor technical glitches in their storied history. The Comet? An airplane, right? The British postal service software? Let’s not talk about that. And now tennis. Jeeves, what’s going on? What, sir?

“British-Built Hawk-Eye Software Goes Dark During Wimbledon Match” continues this game where real life intersects with zeros and ones. (Yes, I know about Oxbridge excellence.) The write up points out:

Wimbledon blames human error for line-calling system malfunction.

Yes, a fall person. What was the problem with the unsinkable ship? Ah, yes. It seemed not to be unsinkable, sir.

The write up says:

Wimbledon’s new automated line-calling system glitched during a tennis match Sunday, just days after it replaced the tournament’s human line judges for the first time.  The system, called Hawk-Eye, uses a network of cameras equipped with computer vision to track tennis balls in real-time. If the ball lands out, a pre-recorded voice loudly says, “Out.” If the ball is in, there’s no call and play continues. However, the software temporarily went dark during a women’s singles match between Brit Sonay Kartal and Russian Anastasia Pavlyuchenkova on Centre Court.

Software glitch. I experience them routinely. No big deal. Plus, the system came back online.

I would like to mention that these types of glitches when combined with the friskiness of smart software may produce some events which cannot be dismissed with “no big deal.” Let me offer three examples:

1. Medical misdiagnoses related to potent cancer treatments
2. Aircraft control systems
3. Financial transaction in legitimate and illegitimate services.

Have the British cornered the market on software challenges? Nope.

That’s my concern. From Telegram’s “let our users do what they want” to contractors who are busy answering email, the consequences of indifferent engineering combined with minimally controlled smart software is likely to do more than fail during a tennis match.

Stephen E Arnold, July 17, 2025

An AI Wrapper May Resolve Some Problems with Smart Software

No smart software involved with this blog post. (An anomaly I know.)

For those with big bucks sunk in smart software chasing their tail around large language models, I learned about a clever adjustment — an adjustment that could pour some water on those burning black holes of cash.

A 36 page “paper” appeared on ArXiv on July 4, 2025 (Happy Birthday, America!). The original paper was “revised” and posted on July 8, 2025. You can read the July 8, 2025, version of “MemOS: A Memory OS for AI System” and monitor ArXiv for subsequent updates.

I recommend that AI enthusiasts download the paper and read it. Today content has a tendency to disappear or end up behind paywalls of one kind or another.

The authors of the paper come from outfits in China working on a wide range of smart software. These institutions explore smart waste water as well as autonomous kinetic command-and-control systems. Two organizations funding the “authors” of the research and the ArXiv write up are a start up called MemTensor (Shanghai) Technology Co. Ltd. The idea is to take good old Google tensor learnings and make them less stupid. The other outfit is the Research Institute of China Telecom. This entity is where interesting things like quantum communication and novel applications of ultra high frequencies are explored.

The MemOS is, based on my reading of the paper, is that MemOS adds a “layer” of knowledge functionality to large language models. The approach remembers the users’ or another system’s “knowledge process.” The idea is that instead of every prompt being a brand new sheet of paper, the LLM has a functional history or “digital notebook.” The entries in this notebook can be used to provide dynamic context for a user’s or another system’s query, prompt, or request. One application is “smart wireless” applications; another, context-aware kinetic devices.

I am not sure about some of the assertions in the write up; for example, performance gains, the benchmark results, and similar data points.

However, I think that the idea of a higher level of abstraction combined with enhanced memory of what the user or the system requests is interesting. The approach is similar to having an “old” AS/400 or whatever IBM calls these machines and interacting with them via a separate computing system is a good one. Request an output from the AS/400. Get the data from an I/O device the AS/400 supports. Interact with those data in the separate but “loosely coupled” computer. Then reverse the process and let the AS/400 do its thing with the input data on its own quite tricky workflow. Inefficient? You bet. Does it prevent the AS/400 from trashing its memory? Most of the time, it sure does.

The authors include a pastel graphic to make clear that the separation from the LLM is what I assume will be positioned as an original, unique, never-before-considered innovation:

Now does it work? In a laboratory, absolutely. At the Syracuse Parallel Processing Center, my colleagues presented a demonstration to Hillary Clinton. The search, text, video thing behaved like a trained tiger before that tiger attacked Roy in the Siegfried & Roy animal act in October 2003.

Are the data reproducible? Good question. It is, however, a time when fake data and synthetic government officials are posting videos and making telephone calls. Time will reveal the efficacy of the ‘breakthrough.”

Several observations:

1. The purpose of the write up is a component of the China smart, US dumb marketing campaign
2. The number of institutions involved, the presence of a Chinese start up, and the very big time Research Institute of China Telecom send the message that this AI expertise is diffused across numerous institutions
3. The timing of the release of the paper is delicious: Happy Birthday, Uncle Sam.

Net net: Perhaps Meta should be hiring AI wizards from the Middle Kingdom?

Stephen E Arnold, July 15, 2025

Hot Bots Bite

No smart software involved. Just an addled dinobaby.

I read “Discord is Threatening to Shutdown BotGhost: The Ensh*ttification of Discord.” (I really hate that “ensh*t neologism.) The write up is interesting. If you know zero about bots, just skip it. If you do know something about bots in “walled gardens.” Take a look. The use of software robots which are getting smarter and smarter thanks to “artificial intelligence” will emerge, morph, and become vectors for some very exciting types of online criminal activity. Sure, bots can do “good,” but most people with a make-money-fast idea will find ways to botify online crime. With crypto currency scoped to be an important part of “everything” apps, excitement is just around the corner.

However, I want to call attention to the comments section of Hacker News. Several of the observations struck me as germane to my interests in bots purpose built for online criminal activity. Your interests are probably different from mine, but here’s a selection of the remarks I found on point for me:

1. throwaway7679 posts: [caps in original] “NEITHER DISCORD NOR ITS AFFILIATES, SUPPLIERS, OR DISTRIBUTORS MAKE ANY SPECIFIC PROMISES ABOUT THE APIs, API DATA, DOCUMENTATION, OR ANY DISCORD SERVICES. The existence of terms like this make any discussion of the other terms look pretty silly. Their policy is simply that they do whatever they want, and that hasn’t changed.”
2. sneak posts: “Discord has the plaintext of every single message ever sent via Discord, including all DMs. Can you imagine the value to LLM companies? It’s probably the single largest collection of sexting content outside of WeChat (and Apple’s archive of iCloud Backups that contain all of the iMessages).”
3. immibis posts: “Reddit is more evil than Discord IMO – they did this years ago, tried to shut down all bots and unofficial apps, and they heavily manipulate consensus opinion, which Discord doesn’t as far as I know.”
4. macspoofing posts: “…For software platforms, this has been a constant. It happened with Twitter, Facebook, Google (Search/Ads, Maps, Chat), Reddit, LinkedIn – basically ever major software platform started off with relatively open APIs that were then closed-off as it gained critical mass and focused on monetization.”
5. altairprime posts: “LinkedIn lost a lawsuit about prohibiting third parties tools from accessing its site, Matrix has strong interop, Elite Dangerous offers OAuth API for sign-in and player data download, and so on. There are others but that’s sixty seconds worth of thinking about it. Mastodon metastasized the user store but each site is still a tiny centralized user store. That’s how user stores work. Doesn’t mean they’re automatically monopolistic. Discord’s taking the Reddit-Apollo approach to forcing them offline — half-assed conversations for months followed by an abrupt fuck-you moment with little recourse — which given Discord’s free of charge growth mechanism, means that — just like Reddit — they’re likely going to shutdown anything by that’s providing a valuable service to a significant fraction of their users, either to Sherlock and charge money for it, or simply to terminate what they view as an obstruction.”

Several observations:

1. Telegram not mentioned in the comments which I reviewed (more are being added, but I am not keeping track of these additions as of 1125 am US Eastern on June 25, 2025)
2. Bots are a contentious type of software
3. The point about the “value” of messages to large language models is accurate.

Stephen E Arnold, July 3, 2025

Read This Essay and Learn Why AI Can Do Programming

No AI, just the dinobaby expressing his opinions to Zillennials.

I, entirely by accident since Web search does not work too well, an essay titled “Ticket-Driven Development: The Fastest Way to Go Nowhere.” I would have used a different title; for example, “Smart Software Can Do Faster and Cheaper Code” or “Skip Computer Science. Be a Plumber.” Despite my lack of good vibe coding from the essay’s title, I did like the information in the write up. The basic idea is that managers just want throughput. This is not news.

The most useful segment of the write up is this passage:

You don’t need a process revolution to fix this. You need permission to care again. Here’s what that looks like:

• Leave the code a little better than you found it — even if no one asked you to.
• Pair up occasionally, not because it’s mandated, but because it helps.
• Ask why. Even if you already know the answer. Especially then.
• Write the extra comment. Rename the method. Delete the dead file.
• Treat the ticket as a boundary, not a blindfold.

Because the real job isn’t closing tickets it’s building systems that work.

I wish to offer several observations:

1. Repetitive boring, mindless work is perfect for smart software
2. Implementing dot points one to five will result in a reprimand, transfer to a salubrious location, or termination with extreme prejudice
3. Spending long hours with an AI version of an old-fashioned psychiatrist because you will go crazy.

After reading the essay, I realized that the managerial approach, the “ticket-driven workflow”, and the need for throughput applies to many jobs. Leadership no longer has middle managers who manage. When leadership intervenes, one gets [a] consultants or [b] knee-jerk decisions or mandates.

The crisis is in organizational set up and management. The developers? Sorry, you have been replaced. Say, “hello” to our version of smart software. Her name is No Kidding.

Stephen E Arnold, July 3, 2025

Palantir Rattles the Windows in the Nuclear Industry

This dinobaby asked ChatGPT about Palantir. Interesting output.

“Palantir Partners to Develop AI Software for Nuclear Construction” caught me by surprise. I did not think the company founded in 2003 was an artificial intelligence company with expertise in the nuclear field. The cited article reports:

Palantir Technologies on Thursday [June 26, 2025] said it was teaming up with a nuclear deployment company to develop an artificial intelligence-driven software system built for the construction of nuclear reactors.

I have paid much attention to Palantir, but I did own a small amount of Palantir stock but I dumped it.

Screenshot of the ChatGPT output on June 27, 2025, at 855 am US Eastern

Today I wanted to refresh my memory about the company. I navigated to OpenAI’s ChatGPT and plugged in key words and this is what the Sam Altman system generated for me. Note: It is unlikely that the ChatGPT system can output the same report because probability doesn’t work the way users of the system think it does.

Remember: The quoted passage is copied directly from the ChatGPT response. ChatGPT told me:

Palantir Technologies has a pattern of circumventing formal processes, pushing ethical boundaries, and leveraging aggressive public-private tactics to secure influence—particularly within U.S. defense and intelligence communities.

Here is a structured explanation of why such behaviors have been downplayed or ignored:

 

---

1. Operational Utility Overrides Bureaucratic Violations

• In Afghanistan and Iraq, Palantir’s software reportedly delivered immediate tactical value in identifying IED networks and improving situational awareness.
• By deploying software and engineers directly to the field without formal contracts, Palantir created facts on the ground—a working product that soldiers wanted, and field commanders endorsed.
• Pentagon leadership faced a dilemma: challenge Palantir for its violations or continue using a system that operators said worked better than the legacy alternatives (e.g., DCGS-A).
• This “bottom-up demand” shielded Palantir from early procurement blowback.

 

---

2. Information Warfare and Lobbying

• Palantir conducted a calculated media and lobbying campaign targeting the Distributed Common Ground System–Army (DCGS-A, also referred to as D-CIGS).
• By discrediting IBM and other legacy defense contractors, Palantir positioned itself as the modern, Silicon Valley alternative.
• This messaging resonated with Congress, think tanks, and parts of the press, framing Palantir as a disruptor, not a rule-breaker.
• Lobbying disclosures show Palantir spent millions courting lawmakers and decision-makers.

 

---

3. Legal Maneuvering and Settlements

• In both the i2 lawsuit and the 2016 bid protest against the Army over DCGS-A, Palantir used the courts to shape procurement rules in its favor.
• The Court of Federal Claims sided with Palantir in 2016, affirming that the Army violated federal acquisition regulations by excluding commercial solutions from its process ([Palantir USG v. United States, 129 Fed. Cl. 218 (2016)]). This set a precedent that indirectly legitimized Palantir’s aggressive tactics.

 

---

4. Shift in Public Attention and National Security Prioritization

• Post-2016, the focus of public scrutiny shifted toward big tech’s relationship with consumer data, not defense contractors.
• Palantir successfully repositioned itself as a key player in pandemic response, immigration enforcement, and border security—domains where national interest arguments silence criticism.
• The company also leaned into its identity as a pro-Western, anti-authoritarian force, which further insulated it from deeper ethical scrutiny.

 

---

5. Opacity and Media Fatigue

• Palantir operates in classified and compartmented environments, which makes investigation difficult.
• Many journalists lack the access or technical background to track the nuance of procurement violations or reverse engineering disputes.
• After years of unresolved criticism, media fatigue set in—journalists moved on, and watchdog groups prioritized new targets (e.g., TikTok, Clearview AI, etc.).

 

---

Conclusion:

Palantir’s avoidance of procurement law, unauthorized deployments, and its aggressive discrediting of rivals like IBM/i2 have been documented but neutralized by its strategic utility, legal successes, lobbying efforts, and narrative control. The firm masks tactical rule-breaking with patriotic branding, which has proved highly effective in suppressing deeper accountability.

True, false, reality, or hallucinatory? I don’t know. Nuclear in the context of this ChatGPT output that suggests the Palantir outfit is definitely operating in a very interesting manner. What would Palantir’s AI say about the company?

Stephen  E Arnold, June 30, 2025

 

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  Stephen E. Arnold monitors search, content processing, text mining and related topics from his high-tech nerve center in rural Kentucky. He tries to winnow the goose feathers from the giblets. He works with colleagues worldwide to make this Web log useful to those who want to go "beyond search". Contact him at sa [at] arnoldit.com. His Web site with additional information about search is arnoldit.com.

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