Academics Lead and Student Follow: Is AI Far Behind?
July 16, 2025
Just a dinobaby without smart software. I am sufficiently dull without help from smart software.
I read “Positive Review Only: Researchers Hide AI Prompts in Papers.” Note: You may have to pay to read this write up.] Who knew that those writing objective, academic-type papers would cheat? I know that one ethics professor is probably okay with the idea. Plus, that Stanford University president is another one who would say, “Sounds good to me.”
The write up says:
Nikkei looked at English-language preprints — manuscripts that have yet to undergo formal peer review — on the academic research platform arXiv. It discovered such prompts in 17 articles, whose lead authors are affiliated with 14 institutions including Japan’s Waseda University, South Korea’s KAIST, China’s Peking University and the National University of Singapore, as well as the University of Washington and Columbia University in the U.S. Most of the papers involve the field of computer science.
Now I would like suggest that commercial database documents are curated and presumably less likely to contain made up information. I cannot. Peer reviewed papers also contain some slick moves; for example, a loose network of academic friends can cite one another’s papers to boost them in search results. Others like the Harvard ethics professor just write stuff and let it sail through the review process fabrications and whatever other confections were added to the alternative fact salads.
What US schools featured in this study? The University of Washington and Columbia University. I want to point out that the University of Washington has contributed to the Google brain trust; for example, Dr. Jeff Dean.
Several observations:
- Why should students pay attention to the “rules” of academic conduct when university professors ignore them?
- Have universities given up trying to enforce guidelines for appropriate academic behavior? On the other hand, perhaps these ArXiv behaviors are now the norm when grants may be in balance?
- Will wider use of smart software change the academics’ approach to scholarly work?
Perhaps one of these estimable institutions will respond to these questions?
Stephen E Arnold, July 16, 2025
AI Produces Human Clipboards
July 16, 2025
![Dino 5 18 25_thumb[3]](https://www.arnoldit.com/wordpress/wp-content/uploads/2025/07/Dino-5-18-25_thumb3-1.gif "Dino 5 18 25_thumb[3]")
No smart software involved with this blog post. (An anomaly I know.)
The upside and downside of AI seep from my newsfeed each day. More headlines want me to pay to view a story from Benzinga. Benzinga, a news release outfit. I installed Smartnews on one of my worthless mobile devices. Out of three stories, one was incoherent. No thanks, AI.
I spotted a write up in the Code by Tom blog titled “The Hidden Cost of AI Reliance.” It contained a quote to note; to wit:
“I’ve become a human clipboard.”
The write up includes useful references about the impact of smart software on some humans’ thinking skills. I urge you to read the original post.
I want to highlight three facets of the “AI problem” that Code by Tom sparked for me.
First, the idea that the smart software is just “there” and it is usually correct strikes me as a significant drawback for students. I think the impact in grade school and high school will be significant. No amount of Microsoft and OpenAI money to train educators about AI will ameliorate unthinking dependence of devices which just provide answers. The act of finding answers and verifying them are essential for many types of knowledge work. I am not convinced that today’s smart software which took decades to become the next big thing can do much more than output what has been fed into the neural predictive matrix mathy systems.
Second, the idea that teachers can somehow integrate smart software into reading, writing, and arithmetic is interesting. What happens if students do not use the smart software the way Microsoft or OpenAI’s educational effort advises. What then? Once certain cultural systems and norms are eroded, one cannot purchase a replacement at the Dollar Store. I think with the current AI systems, the United States speeds more quickly to a digital dark age. It took a long time to toward something resembling a non dark age.
Finally, I am not sure if over reliance is the correct way to express my view of AI. If one drives to work a certain way each day, the highway furniture just disappears. Change a billboard or the color of a big sign, and people notice. The more ubiquitous smart software becomes, the less aware many people will be that it has altered thought processes, abilities related to determine fact from fiction, and the ability to come up with a new idea. People, like the goldfish in a bowl of water, won’t know anything except the water and the blurred images outside the aquarium’s sides.
Tom, the coder, seems to be concerned. I do most tasks the old-fashioned way. I pay attention to smart software, but my experiences are limited. What I find is that it is more difficult now to find high quality information than at any other time in my professional career. I did a project years ago for the University of Michigan. The work concerned technical changes to move books off-campus and use the library space to create a coffee shop type atmosphere. I wrote a report, and I know that books and traditional research tools were not where the action was. My local Barnes & Noble bookstore sells toys and manga cartoons. The local library promotes downloading videos.
Smart software is a contributor to a general loss of interest in learning the hard way. I think smart software is a consequence of eroding intellectual capability, not a cause. Schools were turning out graduates who could not read or do math. What’s the fix? Create software to allow standards to be pushed aside. The idea is that if a student is smart, that student does not have to go to college. One young person told me that she was going to study something practical like plumbing.
Let me flip the argument.
Smart software is a factor, but I think the US educational system and the devaluation of certain ideas like learning to read, write, and “do” math manifest what people in the US want. Ease, convenience, time to doom scroll. We have, therefore, smart software. Every child will be, by definition, smart.
Will these future innovators and leaders know how to think about information in a critical way? The answer for the vast majority of US educated students, the answer will be, “Not really.”
Stephen E Arnold, July 16, 2025
An AI Wrapper May Resolve Some Problems with Smart Software
July 15, 2025
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:
- The purpose of the write up is a component of the China smart, US dumb marketing campaign
- 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
- 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
Google Is Great. Its AI Is the Leader, Just As Philco Was
July 15, 2025
No smart software involved with this blog post. (An anomaly I know.)
The Google and its Code Red Yellow or whatever has to pull a revenue rabbit out of its ageing Stetson. (It is a big Stetson too.) Microsoft found a way to put Googzilla on its back paw in January 2023. Mr. Nadella announced a deal with OpenAI and ignited the Softies to put Copilot in everything, including the ASCII editor Notepad.
Google demonstrated a knee jerk reaction. Put Prabhakar in Paris to do a stand up about Google AI. Then Google reorganized its smart software activities… sort of. The wizards at Google has pushed out like a toothpaste tube crushed by a Stanford University computer science professor’s flip flops. Suffice it to say there are many Google AI products and services. I gave up trying to keep track of them months ago.
What’s happened? Old-school, Google searches are work now. Some sites have said that Google referral traffic is down a third or more.
What’s up?
“Google Faces Threat That Could Destroy Its Business” offers what I would characterize as a Wall Street MBA view of the present day Google. The write up says:
As the AI boom continues to transform the landscape of the tech world, a new type of user behavior has begun to gain popularity on the web. It’s called zero-click search, and it means a person searches for something and gets the answer they want without clicking a single link. There are several reasons for this, including the AI Overview section that Google has added to the top of many search result pages. This isn’t a bad thing, but what’s interesting is why Google is leaning into AI Overview in the first place: millions of people are opening ChatGPT instead of Google to search for the things they want to know.
The cited passage suggests that Google is embracing one-click search, essentially marginalizing the old-school list of links. Google has made this decision because of or in response to OpenAI. Lurking between the lines of the paragraph is the question, “What the heck is Google doing?”
On July 9, Reuters exclusively reported that OpenAI would soon launch its own web browser to challenge Google Chrome’s dominance.
This follows on OpenAI’s stating that it would like to buy the Chrome browser if the US government forces Google to sell is ubiquitous data collection interface with users. Start ups are building browsers. Perplexity is building browsers. The difference is that OpenAI and Perplexity will use AI as plumbing, not an add on. Chrome is built as a Web 1 and Web 2 service. OpenAI and Perplexity are likely to just go for Web 3 functionality.
What’s that look like? I am not sure, but it will not come from some code originally cooked up someplace like Denmark and refurbished many times to the ubiquitous product we have today.
My view is that Google is somewhat disorganized when it comes to smart software. As the company tries to revolutionize medicine, create smart maps, and build expensive self driving taxis — people are gravitating to ChatGPT which is now a brand like Kleenex or Xerox. Perplexity is a fan favorite at the moment as well. To add some spice to the search recipe, Anthropic and outfits like China Telecom are busy innovating.
What about Google? We are about to learn how a former blue chip consultant will give Google more smarts. Will that intelligence keep the money flowing and growing? Why be a Debbie Downer. Google is the greatest thing since sliced bread. Those legal actions are conspiracies fueled by jealous competitors. Those staff cutback? Just efficiencies. Those somewhat confusing AI products and services? Hey, you are just not sufficiently Googley to see the brilliance of Googzilla’s strategy.
Okay, I agree. Google is wonderful and the Wall Street MBA type analysis is wonky, probably written with help from Grok or Mistral. Google is and will be wonderful. You can search for examples too. Give Perplexity a try.
Stephen E Arnold, July 15, 2025
Killing Consulting: Knowledge Draculas Live Forever
July 14, 2025
No smart software involved with this blog post. (An anomaly I know.)
I read an opinion piece published in the Substack system. The article’s title is “The Consulting Crash Is Coming.” This title is in big letters. The write up delivers big news to people who probably did not work at large consulting companies; specifically, the blue chip outfits like McKinsey, Bain, BCG, Booz, Allen, and a handful of others.
The point of the write up is that large language models will put a stake in the consulting Draculas.
I want to offer several observations as a former full-time professional at one of the blue chip outfits and a contractor for a couple of other pay-for-knowledge services firms.
First, assume that Mr. Nocera is correct. Whatever consulting companies remain in business will have professionals with specific work processes developed by the blue chip consulting firms. Boards, directors, investors, non-governmental organizations, individual rich people, and institutions like government agencies and major academic institutions want access to the people and knowledge value of the blue chip consulting firms. A consulting company may become smaller, but the entity will adapt. Leaders of organizations in the sectors I identified will hire these firms. An AT Kearney-type of firm may be disappeared, but for the top tier, resiliency is part of the blue chip DNA.
Second, anyone familiar with Stuart Kauffman (Santa Fe Institute) is familiar with his notion of spontaneous order, adjacency, and innovations creating more innovations. As a result of this de facto inferno of novelty and change, smart people will want to hire other smart people in the hopes of learning something useful. One can ask a large language model or its new and improved versions. However, blue chip consulting firms and the people they attract usually come up with orthogonal ideas and questions. The knowledge exercise builds the client’s mental strength. That is what brings clients to the blue chip firm’s door.
Third, blue chip consulting firms can be useful proxies for [a] reorganizing a unit and removing a problematic officer, [b] figuring out what company to buy, how to chop it up, and sell of the parts for a profit, [c] thinking about clever ways to deploy new technology because the blue chip professionals have first hand expertise from many different companies and their work processes. Where did synthetic bacon bits originate? Answer: A blue chip consulting company. A food company just paid the firm to assemble a team to come up with a new product. Bingo. Big seller.
Fourth, hiring a blue chip consulting firm conveys prestige to some clients. Many senior executives suffer from imposter syndrome. Many are not sure what happened to generate so much cash and market impact. The blue chip firm delivers “colleagues” who function to reduce the senior executive’s anxiety. Those senior executives will pay. My boss challenged Jack Welch in a double or nothing bet worth millions in consulting fees regarding a specific report. Mr. Welch loved the challenge from a mere consulting firm. The bet was to deliver specific high value information. We did. Mr. Welch paid the bill for the report he didn’t like and the one that doubled the original fee. He said, “We will hire you guys again. You think the way I do.”
Net net: Bring on the LLMs, the AI, the smart back office workflows. The blue chip consulting firms may downsize; they may recalibrate; they will not go away. Like Draculas, they keep getting invited back, to suck fees, and probably live forever.
Stephen E Arnold, July 14, 2025
Deezer: Not Impressed with AI Tunes
July 14, 2025
Apparently, musical AI models have been flooding streaming services with their tracks. But ai music is the tune for the 21st century is it not? The main problem: these bots can divert payments that should have gone to human artists. Now, we learn from MSN, “Streaming Platform Deezer Starts Flagging AI-Generated Music.” The article, originally published at The Economic Times, states:
“Deezer said in January that it was receiving uploads of 10,000 AI tracks a day, doubling to over 20,000 in an April statement — or around 18% of all music added to the platform. The company ‘wants to make sure that royalties supposed to go to artists aren’t being taken away’ by tracks generated from a brief text prompt typed into a music generator like Suno or Udio, Lanternier said. AI tracks are not being removed from Deezer’s library, but instead are demonetised to avoid unfairly reducing human musicians’ royalties. Albums containing tracks suspected of being created in this way are now flagged with a notice reading ‘content generated by AI’, a move Deezer says is a global first for a streaming service.”
Probably a good thing. Will other, larger streaming services follow suit? Spotify, for one, is not yet ready to make that pledge. The streaming giant seems squeamish to wade into legal issues around the difference between AI- and human-created works. It also points to the lack of a “clear definition” for entirely AI-generated audio.
How does Deezer separate the human-made tunes from AI mimicry? We learn:
“Lanternier said Deezer’s home-grown detection tool was able to spot markers of AI provenance with 98% accuracy. ‘An audio signal is an extremely complex bundle of information. When AI algorithms generate a new song, there are little sounds that only they make which give them away… that we’re able to spot,’ he said. ‘It’s not audible to the human ear, but it’s visible in the audio signal.’"
Will bots find a way to eliminate such tell-tale artifacts? Will legislation ever catch up to reality? Will Big Streaming feel pressure to implement their own measures? This will be an interesting process to follow.
Cynthia Murrell, July 14, 2025
Win Big at the Stock Market: AI Can Predict What Humans Will Do
July 10, 2025
No smart software to write this essay. This dinobaby is somewhat old fashioned.
AI is hot. Click bait is hotter. And the hottest is AI figuring out what humans will do “next.” Think stock picking. Think pitching a company “known” to buy what you are selling. The applications of predictive smart software make intelligence professionals gaming the moves of an adversary quiver with joy.
“New Mind-Reading’ AI Predicts What Humans Will Do Next, And It’s Shockingly Accurate” explains:
Researchers have developed an AI called Centaur that accurately predicts human behavior across virtually any psychological experiment. It even outperforms the specialized computer models scientists have been using for decades. Trained on data from more than 60,000 people making over 10 million decisions, Centaur captures the underlying patterns of how we think, learn, and make choices.
Since I believe everything I read on the Internet, smart software definitely can pull off this trick.
How does this work?
Rather than building from scratch, researchers took Meta’s Llama 3.1 language model (the same type powering ChatGPT) and gave it specialized training on human behavior. They used a technique that allows them to modify only a tiny fraction of the AI’s programming while keeping most of it unchanged. The entire training process took only five days on a high-end computer processor.
Hmmm. The Zuck’s smart software. Isn’t Meta in the midst of playing catch up. The company is believed to be hiring OpenAI professionals and other wizards who can convert the “also in the race” to “winner” more quickly than one can say “billions of dollar spent on virtual reality.”
The write up does not just predict what a humanoid or a dinobaby will do. The write up reports:
n a surprising discovery, Centaur’s internal workings had become more aligned with human brain activity, even though it was never explicitly trained to match neural data. When researchers compared the AI’s internal states to brain scans of people performing the same tasks, they found stronger correlations than with the original, untrained model. Learning to predict human behavior apparently forced the AI to develop internal representations that mirror how our brains actually process information. The AI essentially reverse-engineered aspects of human cognition just by studying our choices. The team also demonstrated how Centaur could accelerate scientific discovery.
I am sold. Imagine. These researchers will be able to make profitable investments, know when to take an alternate path to a popular tourist attraction, and discover a drug that will cure male pattern baldness. Amazing.
My hunch is that predictive analytics hooked up to a semi-hallucinating large language model can produce outputs. Will these predict human behavior? Absolutely. Did the Centaur system predict that I would believe this? Absolutely. Was it hallucinating? Yep, poor Centaur.
Stephen E Arnold, July 10, 2025
Apple and Telegram: Victims of Their Strategic Hubris
July 9, 2025
No smart software to write this essay. This dinobaby is somewhat old fashioned.
What’s “strategic hubris”? I use this bound phrase to signal that an organization manifests decisions that combine big thinking with a destructive character flow. Strategy is the word I use to capture the most important ideas to get an organization to generate revenue and win in its business and political battles. Now hubris. A culture of superiority may be the weird instinct of a founder; it may be marketing jingo that people start believing; or it is jargon learned in school. When the two come together, some organizations can make expensive, often laughable, mistakes. Examples range from Windows and its mobile phone to the Ford Edsel.
I read “Apple Reaches Out to OpenAI, Anthropic to Build Out Siri technology.” In my opinion, this illustrates strategic hubris operating on two pivot points like a merry-go-round: Up and down; round and round.
The cited article states:
… over the past year or so it [Apple] has faced a variety of leadership and technological challenges developing Apple Intelligence, which is based on in-house foundation models. The more personalized Siri technology with more personalized AI-driven features is now due in 2026, according to a statement by Apple …
This “failure” is a result of strategic hubris. Apple’s leadership believed it could handle smart software. The company taught China how to be a manufacturing super power could learn and do AI. Apple’s leadership seems to have followed the marketing rule: Fire, Aim, Ready. Apple announced AI or Apple Intelligence and then failed to deliver. Then Apple reorganized and it failed again. Now Apple is looking at third party firms to provide the “intelligence” for Apple.
Personally I think smart software is good at some things and terrible at others. Nevertheless, a failure to provide or “do” smart software is the digital equivalent of having a teacher put a dunce cap on a kid’s head and making him sit in the back of the classroom. In the last 18 months, Apple has been playing fast and loose with court decisions, playing nice with China, and writing checks for assorted fines levied by courts. But the premier action has been the firm’s failure in the alleged “next big thing”.
Let me shift from Apple because there is a firm in the same boat as the king of Cupertino. Telegram has no smart software. Nikolai Durov is, according to Pavel (the task master) working on AI. However, like Apple, Telegram has been chatting up (allegedly) Elon Musk. The Grok AI system, some rumors have it, would / could / should be integrated into the Telegram platform. Telegram has the same strategic hubris I associated with Apple. (These are not the only two firms afflicted with this digital SARS variant.)
I want to identify several messages I extracted from the Apple and Telegram AI anecdotes:
- Both companies were doing other things when the smart software yachts left the docks in Half Moon Bay
- Both companies have the job of integrating another firm’s smart software into large, fast-moving companies with many moving parts, legal problems, and engineers who are definitely into “strategic hubris”
- Both companies have to deliver AI that does not alienate existing users and attract new customers at the same time.
Will these firms be able to deliver a good enough AI solution? Probably. However, both may be vulnerable to third parties who hop on a merry-go-round. There is a predictable and actually no-so-smart pony named Apple and one named Messenger. The threat is that Apple and Telegram have been transmogrified into little wooden ponies. The smart people just ride them until the time is right to jump off.
That’s one scenario for companies with strategic hubris who missed the AI yachts when they were under construction and who were not on the expensive machines when they cast off. Can the costs of strategic hubris be recovered? The stakeholders hope so.
Stephen E Arnold, July 9, 2025
Humans May Be Important. Who Knew?
July 9, 2025
Here is an AI reality check. Futurism reports, “Companies that Replaced Humans with AI Are Realizing their Mistake.” You don’t say. Writer Joe Wilkins tells us:
“As of April, even the best AI agent could only finish 24 percent of the jobs assigned to it. Still, that didn’t stop business executives from swarming to the software like flies to roadside carrion, gutting entire departments worth of human workers to make way for their AI replacements. But as AI agents have yet to even pay for themselves — spilling their employer’s embarrassing secrets all the while — more and more executives are waking up to the sloppy reality of AI hype. A recent survey by the business analysis and consulting firm Gartner, for instance, found that out of 163 business executives, a full half said their plans to ‘significantly reduce their customer service workforce’ would be abandoned by 2027. This is forcing corporate PR spinsters to rewrite speeches about AI ‘transcending automation,’ instead leaning on phrases like ‘hybrid approach’ and ‘transitional challenges’ to describe the fact that they still need humans to run a workplace.”
Few workers would be surprised to learn AI is a disappointment. The write-up points to a report from GoTo and Workplace Intelligence that found 62% of employees say AI is significantly overhyped. Meanwhile, 45 percent of IT managers surveyed paint AI rollouts as scattered and hasty. Security concerns and integration challenges were the main barriers, 56% of them reported.
Anyone who has watched firm after firm make a U-turn on AI-related layoffs will not be surprised by these findings. For example, after cutting staff by 22% last year, finance startup Klarna announced a recruitment drive in May. Wilkins quotes tech critic Ed Zitron, who wrote in September:
“These ‘agents’ are branded to sound like intelligent lifeforms that can make intelligent decisions, but are really just trumped-up automations that require enterprise customers to invest time programming them.”
Companies wanted a silver bullet. Now they appear to be firing blanks.
Cynthia Murrell, July 9, 2025
We Have a Cheater Culture: Quite an Achievement
July 8, 2025
The annual lamentations about AI-enabled cheating have already commenced. Professor Elizabeth Wardle of Miami University would like to reframe that debate. In an opinion piece published at Cincinnati.com, she declares, “Students Aren’t Cheating Because they Have AI, but Because Colleges Are Broken.” Reasons they are broken, she writes, include factors like reduced funding and larger class sizes. Fundamentally, though, the problem lies in universities’ failure to sufficiently evolve.
Some suggest thwarting AI with a return to blue-book essays. Wardle, though, believes that would be a step backward. She notes early U.S. colleges were established before today’s specialized workforce existed. The handwritten assignments that served to train the wealthy, liberal-arts students of yesteryear no longer fit the bill. Instead, students need to understand how things work in the present and how to pivot with change. Yes, including a fluency with AI tools. Graduates must be “broadly literate,” the professor writes. She advises:
“Providing this kind of education requires rethinking higher education altogether. Educators must face our current moment by teaching the students in front of us and designing learning environments that meet the times. Students are not cheating because of AI. When they are cheating, it is because of the many ways that education is no longer working as it should. But students using AI to cheat have perhaps hastened a reckoning that has been a long time coming for higher ed.”
Who is to blame? For one, state legislatures. Many incentivize universities to churn out students with high grades in majors that match certain job titles. State funding, Wardle notes, is often tied to graduates hitting high salaries out of the gate. Her frustration is palpable as she asserts:
“Yes, graduates should be able to get jobs, but the jobs of the future are going to belong to well-rounded critical thinkers who can innovate and solve hard problems. Every column I read by tech CEOs says this very thing, yet state funding policies continue to reward colleges for being technical job factories.”
Professor Wardle is not all talk. In her role as Director of the Howe Center for Writing Excellence, she works with colleagues to update higher-learning instruction. One of their priorities has been how to integrate AI into curricula. She writes:
“The days when school was about regurgitating to prove we memorized something are over. Information is readily available; we don’t need to be able to memorize it. However, we do need to be able to assess it, think critically about it, and apply it. The education of tomorrow is about application and innovation.”
Indeed. But these urgent changes cannot be met as long funding continues to dwindle. In fact, Wardle argues, we must once again funnel significant tax money into higher education. Believe it or not, that is something we used to do as a society. (She recommends Christopher Newfield’s book “The Great Mistake” to learn how and why free, publicly funded higher ed fell apart.) Yes, we suspect there will not be too much US innovation if universities are broken and stay that way. Where will that leave us?
Cynthia Murrell, July 8, 2025
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