TLDR: The Coming Age of Aliteracy

For many years, a good deal of digital ink has been spilled about the end of reading. Lately, however, I found compelling the statistics in Rose Horowitch's "The End of Reading is Here," at The Atlantic. I wish it were not behind a paywall. We all need to read it, even if we cannot focus long enough to finish it.

What I began noticing, incrementally, after the turn of the century is coming true: students (and adults) cannot abide focusing long enough to read anything. In 2001, I taught nine challenging texts in the university's Core class. In Spring of 2025, my most recent literature course, I taught four novel-length works. That was challenging enough, and still I caught students using AI to summarize a short story they couldn't finish, and getting an F for introducing AI hallucination into work submitted for a grade.

But the problem is hardly confined to young people, some of whom will claim that audio books serve as an adequate replacement. As Horowitch's sources note, those do not engage our brains neurologically in the same manner as printed books. Societally, we are losing the ability to retain facts in our heads, unpack difficult syntax, find connections between ideas when we farm those tasks out to machines.

So each year since the iPhone hit the scene in 2007, I've grown more and more certain that Sven Birkert's predictions in The Gutenberg Elegies have come true.

I've peers in their 60s who stopped reading. When they try now, they cannot finish the book. The addictive allure of screens is too great (an irony as I write this on a screen). A few of us who read (or write for) Hemmings Motor News have noted how the stories at the Web site grow shorter and shorter. When a long piece appears, such as the ones I write for them, at least one commenter will thank the author and editors for daring to take a "deep dive" into a topic.

How will this end? I probably will live to see a post-literate society as the norm, a world where serious reading of difficult material becomes a niche skill. Bookstores now doing well may need to stock shorter work to bring in new readers. College English Departments, as well as any teaching from books have not been in great shape for a while. They will morph or go out of business. 

All my life, I have had an eerie feeling of getting through a doorway to have it slam shut behind me. Now I feel the breeze on the back of my neck as Gutenberg's era ends. I fear a Dark Age; don't forget that in late-Roman times, students began reading synopses of classic Greek works instead of tackling the original. Then and now, long, challenging work provides depth that no synopsis or web site can. 

We have so much darkness in our own nation already from being led by an unread, unteachable man. What will come next?

And while YA lit and graphic novels, still thankfully popular, can convey great truths, what happens when they no longer serve as a stepping stone to Edith Wharton, Kazuo Ishiguro, or Toni Morrison? There's a straight line from the bombastic Marvel Comics of my pre-teens to the terrifying state advocated by Socrates in Plato's Republic, which I'm finally reading now in a lovely edition. Socrates, who mistrusted writing, would not have approved. I should have memorized the dialogue!

I plan to treasure the book and its lessons, even if no one I know can discuss it with me. So I went to ChatGPT. I have not touched an AI model since Fall 2025, when I last taught my adult-ed class "Writing With and About AI."

Me: Hello after a while. I've a specific question. Do you think that Socrates really hoped that the Greeks of his time would build a society like that in Plato's Republic? Keep your reply under 200 words. 

Chat: Good to see you again.

Probably not—at least not in a straightforward political sense. Socrates, as Plato presents him, insists that the Republic is an inquiry into justice in the soul as much as in the city. The ideal polis functions as a magnified image of the just individual.

That said, Socrates does not dismiss political reform. He famously says that cities will have no respite until philosophers rule or rulers genuinely become philosophers. This sounds like a genuine, if remote, aspiration. Yet the proposal is framed as so demanding that many readers think Plato intended it as a regulative ideal rather than a practical blueprint for fourth-century Greece.

My view is that Socrates hoped less for Athens to become the Republic than for his interlocutors to rethink what political excellence requires. The ideal city exposes the defects of existing regimes and educates philosophical judgment. Whether anyone could actually found such a city is almost beside the point.

We get here an answer that sounds less canned than those of models a year ago. I like that "my view" moment, too. There's a hook at the end, too. We could (and I may) go on about why making an ideal city-state is "beside the point."

AIs may hallucinate, but at least they did have the Plato fed to them. They'd out-debate any of my students in a Socratic dialogue.

Image Source: Gutenberg Bible, Wikipedia 

 

A Good Counterpoint for Orbital Data Centers

I got an F in Thermodynamics, shortly before I flunked out of UVA's Aerospace Engineering program.

So I leave matters such as cooling satellites to experts, and recently I came across a concern about data centers in space: can they scale to the size we need for AI? Forget issues of space debris and power. The Reverse Salient, in Hughes terms, appears to be cooling.  

The article here discusses, in somewhat technical terms that should still be understood by the non-engineer, the reasons that what engineers call "radiational cooling" in space may not work for the amount of heat generated by orbital data centers. Perverse thought, no? Space is either hideously hot in the sun or deadly cold in the shade. But the problem involves moving heat away from the object in question. There's no breeze in vacuum; any water would boil off or freeze solid. Read the article for more technical details.

This year we will find out if orbital data centers can scale. I hope so. We simply do not have the energy resources or land for the types of AI economy the billionaires envision. The Carbon pollution alone might seal our fate.

NVIDIA, many other US firms, and the Chinese space program, are testing the concept now or will be this year. I wish them luck. We need to get this right.

I'm increasingly of the belief that we'd be better off had AI not been invented, a thought I also have about smart phones and social media, but like those technologies AI is not going to be wished away. 

Image source: Daily Galaxy, Creative Commons image 

Another CCCC, Another Rejection of AI

At face value, the latest rejection of AI in writing classrooms from the Conference on College Composition and Communication does not sound like a radical document. It calmly frames the issue in terms of students' and faculty members' rights to choose how to teach and learn. 

It's also out of touch with how so many universities are being run. Once again, as I did last year, I will issue a brief rebuttal. One of the issues below could be easily addressed. The other? Not so handily.

• Realities of how classes get scheduled and listed
  
  If students have the right to opt out of AI in any course they take, it would create chaos for instructors. Those like me who scaffold AI into assignments do so in ways not possible without these applications. Students would not know until they saw a syllabus how (or if) AI would be employed in a class.
  
  The resolution claims that "Professors should additionally respect a student’s choice to refuse AI. To do this, it would be ideal that they have assignments that students can choose from that do not involve generative AI and that do not isolate the students from class discussions and activities."
  
  My podcasting assignment requires the use of ElevenLabs software. Would I then give students who refuse a second option? My classes are small. I could do that. But what happens in large courses that enroll many dozens of students?
  
  One work-around would be for registrars to flag courses that use AI. Then students could exercise their rights to chose accordingly.
  
  
• The reality of who teaches writing and who makes the decisions
  
  The document rightly notes that "Generative AI is but the latest version of this neoliberal approach to efficiency and expediency," but then it does not give instructors advice about how to counter this trend with senior administration that follows neoliberal principles. The authors rightly note as well that we work in "a profession that has long dealt with labor issues and that continues to rely considerably on frequently underpaid contingent, adjunct, and graduate student labor."
  
  So how, exactly, would such at-will employees say "no" when a university requires AI literacy in its curriculum? Here I'll speak bluntly: the tenured faculty on the committee that drafted this resolution should have known better. That sort of Ivory-Tower elitism in 2025 led me to leave the CCCC.
  
  NCTE leadership understands well the contingent nature of writing instruction and the realities of who now has the power of the purse at our institutions. 
  
  Perhaps these same authors can fight for better governance at colleges and universities, so the voiceless and underpaid have more of a role in shaping policy? Perhaps more tenured faculty could teach more writing-intensive classes? Such teachers do have more power to refuse AI and shape policy around its adoption on campus.
  
  It seems my old profession (well, I still pursue it part-time) is lost in the fog, as industry lays plans for orbital constellations of data-centers and AI apps pop up on our phones without our asking. This will not end well for CCCC, which doesn't bother me. But it does bother me that many teachers of writing may be hurt in the process.

Update, July 2026: I have rejoined the NCTE as a retiree, and I now receive their journal aimed at K-12 language-arts teachers. I changed course partly because NCTE distanced itself from the radical stance of the CCCC by issuing a pragmatic framework for educators who may not be able to say no to AI initiatives. 

Image: Creative-Commons "The campanile at UC Berkeley shrouded in fog." by Daniel Parks at Flickr

A Conversation By Economists About AI

I had the pleasure of attending a "Sharp Viewpoints" event on my old employer's campus, where Dr. Kevin Hallock, university President, hosted two economists with expertise in AI, UVA's Anton Korinek and MIT's David Autor.  The subject, AI and The Future of Work, should concern us all.

I hope not to misrepresent what I heard, but all three experts on stage consider it inevitable that AI will continue to advance rapidly and that it will disrupt careers in fields such as Finance, Computer Science, and Accounting. These have been popular majors for my former students. The scope of the disruption and what happens to wages, as AI takes on more white-collar tasks, remain to be seen. Korinek cited a ninefold increase in the capacity of AI systems annually, from a 2.5x increase in efficiency times a 4x increase in capabilities. 

Korinek warned the audience that we have a small window of time to prepare for resultant changes without chaos in the economy, though Autor felt that if we were to see a gradual loss of a profession, which he called "generational," our economic health could be sustained. He did warn that nothing on the scope of 10% of jobs lost annually could be tolerated without an upheaval. 

Both speakers likened gradual change to, say, automating trucking. The industry would slowly shed human drivers over time, because prior investment in vehicles and warehouses can't be profitably junked overnight. As older drivers retire, however, gradually fewer young people would enter the field and robots would take on the work of moving cargo on the highways. 

As for me? Whoever or whatever does the driving, I still prefer trains for 90% of the hauling, with a truck doing the final leg of the journey. 

The mood was cautiously optimistic, but I'm no optimist. My dad loved being a long-haul trucker. He was not as happy when he ran a wholesale produce company, though that enabled him to put away some money for when he retired. He preferred "the Road" to the security of a desk, and he passed that love of highway travel on to me.  Driving have him a purpose. Yet dad, in retirement, did not begin to write poetry, learn Greek, or play golf. He watched TV and was bored while living on his social security and investment income.

Something the speakers did not address to my satisfaction: if we do have a future without nearly as many jobs for humans, what do many people without side interests or hobbies or talents do with their time? I'm not a good model: I've stayed more busy than ever since leaving full-time employment.

I ask my question, a Humanist's response, assuming that some sort of basic universal income would arise; Author prefers not a monthly dole but a universal basic investment fund for every citizen, beginning at birth. 

Without it, I suspect we'd have some sort of Butlerian Jihad of the mass unemployed, to smash the data centers, and frankly, I'd support smashing them if the alternative meant vast numbers of destitute folks existing alongside a tiny elite empowered by AI. Our speakers did note how this sort of future could emerge, endangering democracy. I'd argue it already is emerging under the broligarchs of Silicon Valley and our current Administration.

Yet with income for all in a jobs-free future, we might have a lot of folks on a dole, not hiking or painting but watching TV and not contributing to our civilization. In my darkest hours, I also think we already have that, without a dole in the US. 

It's better to have a purpose. I didn't hear much discussion of "what does it mean to be a human?" in last night's one-hour chat. Of course, that sort of discussion has been going on among philosophers for millennia, even before Socrates began to question people at Athens' Agora. 

Both Korinek and Autor did fear a rise in inequality, as wages might fall while AI-copiloted productivity rises. That said, everyone agreed that we will have new jobs emerge, some of them related perhaps to newly found leisure time. Autor reminded us that 100 years ago, 38% of Americans worked in agriculture. Today under 2% do. But a person in 1926 also could not image the types of careers many of us now have. Nor did they have our concept of leisure time. A video-game developer's career would have been as alien as a Man from Mars.

Fair point, but when (according to them, not if) AI and humanoid robots replace most human labor, including game design, what will most of us do to find a purpose?

What will colleges do? Korineck, bless him, as well as Hallock, upheld the value of the Liberal Arts for coming to grips with essential and enduring questions. Autor, while nodding to the value of liberal education, said he'd be more "crass" to note that a college degree also means more income and professional training. I don't disagree with him, yet marrying some careerist coursework to a passion for something seems wiser than choosing a "safe" major in a field that bores you.

The even left me unsettled. If the future they predict comes, I'd begin by having students read Plato's Republic and The Federalist Papers with me, for two explanations of what a society can do to organize itself against chaos.

If you want to see a video of the talk, UR recorded it. Thanks to Fred Hagemeister at Richmond for sharing the link.

Reason 11 For Not Building Data Centers Now

A few stories recently caught my eye about moving data centers away from where we live, far away, in fact.

 China's government plans to test space-based data centers starting in 2026, with a rollout of ones with costs as low or lower than earth-based centers slated for the 2030s. Meanwhile in the States, Amazon's Jeff Bezo has hatched similar plans. Not to be left behind by his billionaire rival, Elon Musk wants to use his Starship mega-rockets to orbit data centers. Then there's Google Starcloud, with a test planned for 2027. That system would also depend upon something like Starship to make the venture cheap enough to construct.

At first blush, it seems like a crazy idea, but as I considered the benefits versus costs, it makes sense to move this industry skyward:

• With reusable rocket boosters, costs to orbit per kilogram have dropped radically in recent years. If Starship prospers and others copy its model, we'll see the door opened for very cheap rocket launches.
• We have abundant solar energy in orbit. There's no need for generators, nuclear reactors, or natural gas.
• We also have easy cooling, without using water. Rotate a satellite and you have a solar heating on one side, the utter cold of space on the other.
•  Space-based data centers need not be huge to do their job. They could be a constellation of large satellites that talk to each other, as Starlink does already. Right now, however, big centers seem to be the model for space-based construction.
• If we do go big, we know how to do this already thanks to the International Space Station. 
• Parts of orbital centers can be replaced with one launch, and the old centers can be upgraded by robots or small enough to burn up on a deorbit. 
• Beaming data to ground stations 200 miles away on Earth is not a problem. We already do this.

My hope is that this technology will mature fast, to avoid more environmental and social disruption on Earth. And closest to home, I hope my County's Board of Supervisors pays attention, before we end up with a huge and obsolete building placed on agricultural land next to residences.

One issue that does bother me, beyond the possible climate-change effects of launching so many rockets?

It's called The Kessler Effect (or Syndrome). Readers may have seen the film Gravity, which one explosion in space results in a cascading set of collisions and, consequently, a massive cloud of space debris hurtling around 10 miles per second, chasing an underwear-clad Sandra Bullock.  

How serious is a collision in space? I once saw a piece of Space Shuttle Challenger's front windows, removed from a mission before the craft's 1986 catastrophe. The section of thick glass was damaged badly by hitting a tiny fleck of paint tossed off some forgotten rocket-booster, perhaps decades earlier. Now imagine millions of these objects, large and small, forming a cloud around the Earth, making any rocket launches an exercise in futility, destroying telecom networks, and grounding human space travel for many decades. Or centuries.

A center as large as Starcloud makes for a huge target, were the Kessler Effect to begin. 

Belatedly, firms and governments are considering ways to mitigate space debris and harden orbital infrastructure. Let's hope they get is right, as they'll only have one opportunity. I'd like to get my data from the heavens, not from Earth with more carbon pollution and wasted groundwater.

image: Starcloud center from Google video 

A Strangely Easy Idea No Writing Teacher Has Discussed

I may be out of the loop here, but I've come up with a simple idea that may be grant-worthy. Yes, steal it. Beat me to the grant. The consequences for students' learning may be too great for me to worry about being the first to put my name on it.

What I propose is simple: a writing environment online with the ease of Google Docs, but with one enormous feature disabled: copy/paste. In that regard, it would resemble the Respondus Lockdown Browser. 

The difference? Faculty would organize their classes and assignments there, as with a learning-management system, but they would pick certain AI tools that could employed at each stage of the writing process. The tools would work only from within the writing environment, and the final stages of each step--from rough-draft to revision to later drafts--would be sent from within the browser to the faculty member, along with how each writer used any AI tools permitted.

In that regard, my writing environment looks something like an educational version of Grammarly that an executive once demoed for me. In that product, all work copied and pasted into to interface would be watermarked and AI tools could be disabled or enabled by the user. I'd put that power in the hands of the course instructor, where it belongs. As students tell me again and again, using AI is simply the norm now, and we faculty are wasting time focusing on detecting plagiarism with AI detectors I don't trust. Time and again, studies I've read indicate that they turn up too many false positives. 

My idea requires some coders adept at building a good client and we'd have to negotiate licensing for AI programs such as Research Rabbit, an LLM, a image / slide-deck generator, and multimedia tools such as ElevenLabs' podcast and text-to-voice generators.

By placing the tools within the writing environment and forbidding copy/paste from outside, drafting by cognitive offloading would no long be an issue. 

I'm currently talking to a few colleagues who run our AI cluster on campus. I hope to have something sketched out, and if we can find the coders and money, tested in 2026.

Creative-Commons Image courtesy of oercommons.org 

AI Bubbles and My County: Saying "Not Yet" to Big Data Centers

Note to readers: A version of this post will be submitted to our Board of Supervisors as a formal letter, as well as to a local news outlet. We'll see if it even makes a ripple. 

Even those wary of AI agree that it can do clever work. I use it regularly with students to shape their writing ethically and to design assignments. But can the industry make enough money to continue its progress? A great deal hinges on that answer, including development on the western border of the Richmond Metro Area.

A proposal before Goochland’s Board of Supervisors would allow data centers, perhaps powered by small nuclear reactors, to be built along the Route 288 corridor. Even without considering the environmental hazards, as one who researches the industry, I’ve found economic risks of rushing off quickly to join this AI gold-rush.

CEOs constantly make utopian claims about AI's future, but numbers cloud those predictions. Subscriptions such as mine meant under $2.5 billion in revenue for ChatGPT maker OpenAI in the second half of 2024, according to sources that include The Wall Street Journal and The New York Times. The rest came from venture capital or circular investing, such as Nvidia's and Microsoft's massive stakes in OpenAI.

The firm estimates that building out its data centers would cost $400 billion. For such ambitious plans, companies need a lot more revenue to balance their books. An "AI Bubble" may be inflating, as several economic journalists have warned. Writing for The Atlantic, Rogé Karma notes that “In the first half of this year, business spending on AI added more to GDP growth than all consumer spending combined.” A crash in the AI sector would deal devastating blows to the economy, with local effects when superfluous data centers go dark.

For his part, OpenAI’s CEO Sam Altman focuses on big ideas that seem straight from science fiction. He writes that humans and computers will become one form of life soon, which he calls “The Merge.” I'll quote from his blog, "unless we destroy ourselves first, superhuman AI is going to happen, genetic enhancement is going to happen, and brain-machine interfaces are going to happen." Not all of us would call such things progress, but history shows us that technological breakthroughs take time and a lot of money. Quiet supersonic airliners and nuclear fusion plants have inched closer to reality, over decades.

It well may take that long for AI data centers to not increase ratepayers’ electric bills. We’ve seen that already from existing data centers in the Commonwealth. Before we consign so much open land to data centers locally, let’s consider what experts in the field who are not CEOs or marketers have to say.

A robotics researcher, hired away from my university by Google, insisted to me that human-level thinking cannot be engineered; at best we might imperfectly simulate it, at great expense via a "brute force" computing method run in huge data centers. I recently noted in class how we might improve that, given faster computing using fewer chips, following what’s called Moore's Law. A student challenged me, claiming that silicon-based chips have not enjoyed the leaps in power and speed we expected annually up through the early 2000s.

Several academic papers I looked up support that idea. Without new types of microprocessors or exotic quantum computing, we are stuck with today’s data centers. Concurrently, our AI models remain far from perfect. Alex Reisner of The Atlantic, as well as academic researchers, found developers fudging benchmark tests that measure AI's smarts. They give the software test questions in advance, a tactic beloved by college students for many years. When AI is faces novel tasks, however, it scores far lower. Rogé Karma’s investigative work bears this out; productivity of coders dropped by 20% when working with AI, as they spent more time correcting mistakes.

Other Bubbles have popped with local consequences. A few years ago, I addressed The Board of Supervisors, whose agenda that night included motions to increase suburban-style growth in the east end of the county. I opposed this for many reasons, but one stood out: we had made zoning changes before based on empty promises, when we developed an office park called West Creek for an anchor client, Motorola. Their semiconductor plant would, in theory, have provided many hundreds of jobs.

My late father-in-law, Edward Nuckols, had addressed the Supervisors in the 90s. He was a respected master mechanic and businessman with deep ties to the community; his auto shop, unlike Motorola, had been in operation here for decades. Ed warned that big companies change their minds.

So it came to pass: Motorola backed out of their promises and Goochland was left with over $100 million in debt. One Supervisor reminded me that the county had little choice but to search for other revenue streams to repay that sum. While a fair counterargument, it does not seem we have learned much. Even if Altman and other CEOs are right, such men have no ties to any locality save the posthuman utopias they dream of inhabiting. $100 million of debt means nothing to them.

I’d love to see cheaper, more sustainable AI as a partner in our work. Today's models such as ChatGPT 5, Anthropic Claude, as well as lesser known but powerful tools such as NotebookLM or Research Rabbit, greatly help my students. We engineer prompts to find credible sources that are not hallucinated, we check human-created work for accuracy and voice, we write scripts for podcasts that AI converts to broadcast-quality audio. Plagiarism, the bugaboo of academic AI, concerns me less than does helping my students gain skills for workplaces slowly adopting AI.

My classes emphasize critical thinking when working with AI. So I'll ask Goochland's Board of Supervisors to do some critical thinking and research not influenced by the hype of Silicon Valley's billionaires. Altman claims intelligence will soon be "too cheap to meter." Older folks will recall that fable about electric bills, one made in the 1950s and 60s.

Otherwise, we could be left with more debt and large, empty buildings crumbling in the rain along 288. 

Creative Commons Image: Bioethics.com 

Are Humanists All Like This? Tyler Austin Harper's Strange Ideas About AI on Campus

 I'm fond of The Atlantic; I've subscribed for more than 4 decades. I also enjoy Tyler Austin Harper's articles; his 2024 piece on extreme fishing really moved me with its stories of combat veterans risking their lives at night, swimming out in deep water to find offshore rocks, all to catch striped bass. Austin tried that sport himself; his participation added vividness to his journalism.

As a professor, he is likewise a participant when writing about education. Thus he should know enough about students to avoid the impracticable, even ludicrous, ideas in his newest article, "The Question All Colleges Should Ask Themselves About AI." The title drew me right in, as I too am concerned that institutions of higher education do not comprehend the scope of AI usage by students or what that may portend for their learning. 

So much damage has already been done, before LLMs arrived to thwart the critical-thinking skills we faculty hold so dear. We live in a time when phones and social media have sapped the attention spans and reading comprehension of all ages, and when students from taught-to-the-test K-12 US education lack the ability to construct narratives around the content they do encounter in class. Instead, they often ask me for a rubric and or checklist. When I ask "tell me what you think most interests you from our topic," I usually get blank or anxious looks.

Harper's piece begins in this territory, with worries we share. Soon, however, he turns to a "solution" by Megan Fritts, from U Arkansas at Little Rock, calling for a ban on AI use in the Humanities classroom.

That stance seems not too different from the CCCC Chair's address I rebutted here some time back. I canceled my NCTE membership this year in response to that extremist stance by the organization's leadership.

Yet the similar philosophy that Fritts embraces proves not radical enough for Harper:

Shunning AI use in classrooms is a good start, but schools need to think bigger than that. All institutions of higher education in the United States should be animated by the same basic question: What are the most effective things—even if they sound extreme—that we can do to limit, and ideally abolish, the unauthorized use of AI on campus?

Harper's drive to "abolish" includes: 

• Getting rid of WiFi, laptops, and phones on campus
• Making all writing assignments be done in labs without Internet access 
• Making all students live on campus
• Ending accommodations for neurodiverse students if they include AI (human helpers would fill the gap, as they did before) 
• Penalizing heavily any students caught using AI for academic work, including expulsion.

I began to check to see if he were writing for The Onion, ending with a call for wax tablets for all written work. I can imagine such a  policy at my employer, leading to a 95% drop in applications. I can also imagine new AI-friendly schools, many for-profit, rushing to fill the gap.  I can envision ADA-based lawsuits by neurodiverse learners and their parents.

I won't go on more except to say that Harper's draconian and neo-Luddite solution is not a realistic answer.

Instead I'll end with a question that Fritts asks near the start of her article, as she and others on an AI Committee wrestle with the signature pedagogical challenge of our time, "If this robot can write these books better than we can, then what are we doing here?" Well asked. 

Unless we faculty can add value to AI-written content, maybe we don't deserve jobs any more. I've wondered that since the "Theory Wars" in English and related fields of the late 80s and early 1990s. Poorly aping French Post-Structuralist Theory, faculty in PhD programs ruined the lives of many a graduate student and likely turned off legions of potential undergrads who might have studied literature. I saw this in dozens of cases at Indiana University's PhD program. 

At that time, we lost the thread of meaning--and damn the Deconstructionists who managed to deconstruct meaning out of our field. But the meaning destroyed was not only in texts that lacked narrative cohesion under the scrutiny of theory; the meaning lost included the joy (or jouissance, if you read Barthes) of studying literary work and finding connections to improve one's own life.

Fritts takes us back before my field's epistemological disaster, when she notes that "the aim of our disciplines is the formation of human persons." If we start there, enshrining that principle as the most important one that a college or university (in any discipline) can answer, we have made a good start.  

Image: OpenArt, Cambridge University in Ruins 

ChatGPT 5 Passes "The Big Log Test"

You may recall that some time back, I had a hilarious exchange with an earlier version of ChatGPT about Robert Plant's song "Big Log." Now that version 5 appeared, I wanted to see if the AI would still insist that the song had anything to do with logs made of wood.

No rolling logs this time. The AI did some speculating, but not hallucinating. 

I find the exercise playful, something lacking in anti-AI resistance from one important organization in my field. At the same time, The Big Log Test shows how quickly the AI has reduced its hallucinations. I'd invite readers to try something similar with a favorite song/book/film/TV series that may have an aspect that could confuse an AI. Here we go: 

Prompt: This is a routine check I do as your model improves. I'm curious about any meanings in Robert Plant's song "Big Log." Why do you think he chose that title for his song? Do you see any clues in the lyrics? 

Reply:

Good check-in question — "Big Log" is one of Robert Plant’s more mysterious titles. The lyrics themselves are impressionistic, dreamlike, and full of wandering imagery: travel, desire, distance, loneliness, fate. The phrase “Big Log”*never appears in the song, so the title works more like an oblique symbol or signpost. A few possibilities that critics and listeners have suggested:

1. Truckers and Highways – In trucking slang, a “log” is a driver’s logbook, and a “big log” could mean a long haul or a long road. Since the song is steeped in imagery of roads, headlights, and endless travel, the title could gesture toward the journey itself.

2. Nature and Obstacle – A literal “big log” might be something blocking a path, a metaphor for distance, fate, or emotional barriers. The lyrics’ recurring sense of inevitability (“My love is in league with the freeway…”) could fit this interpretation.

3. Wordplay and Surrealism – Plant often uses surreal or playful titles (e.g., “In the Mood,” “Heaven Knows”). “Big Log” may simply be an evocative, earthy phrase chosen to contrast with the ethereal quality of the lyrics and music.

4. Personal/Private Reference – Sometimes Plant titles songs with private jokes, fragments of conversation, or studio nicknames. It’s possible “Big Log” had an offhand origin unrelated to the lyrics, and he leaned into its strangeness.

Clues in the lyrics point strongest to the *travel/journey* theme: headlights, the freeway, endless searching, being pulled by forces outside oneself. “Big Log” might stand in as the symbolic “record” of that journey — the unending trace of desire and distance.

Follow-Up Prompt: So there are no references to logs in the song?

Reply:

That’s right — there are no actual references to logs (trees, wood, or otherwise) in the lyrics of “Big Log.”

The imagery in the song is all about roads, headlights, distance, fate, longing — not forests or lumber. That’s part of what makes the title puzzling: it seems deliberately disconnected from the lyric surface.

If anything, the best textual “bridge” is the idea of a logbook (the record of a journey), which fits the recurring highway and travel motifs. But Plant never makes that link explicit in the words of the song.

Would you like me to give you a quick “lyrics-only” close reading to show how the imagery develops (and where a title like Big Log might feel thematically tethered, even if indirectly)?

Follow-Up Prompt:

You have clearly evolved. Earlier chats references rolling logs, fallen logs, and so forth. Good work.

Reply:

I’m glad you noticed that difference! Earlier, I sometimes filled the “gap” in the title by speculating more literally — things like fallen trees or rolling logs. With another pass at the song, though, it’s clear Plant never brings that imagery in, so it’s more faithful to stick with the journey / logbook / metaphorical record angle.

Plant’s titles often have that teasing quality — they look literal but carry some private or surreal weight (a kind of wink at the listener). “Big Log” works almost like a signpost planted alongside the road of the song, rather than a description of what’s in it.

 

 

From Antiquity, a Reason Why AI-Generated Writing is not "Great"

Every year, I read at least one text (in translation) from Antiquity. I find that the long-term perspective gets me through the bumps in life's road. I'm currently reading On Great Writing (or if you will, On the Sublime) by Longinus, in a Hackett Classics edition I picked up at an academic conference's book room.

G.M.A Grube makes the work come to life; we know so little about Longinus (the author lived between the 1st Century BCE and the 3rd CE, that the text passes my "castaway reader" test. Here we go: a work washes up intact on your desert island. Yay, something to pass the time! Yet you have no information on the author, and no secondary sources. You must use the actual words on the page to come to a conclusion about the work's meaning.

Longinus talks about many aspects of what constitute "the Sublime" in excellent writing,  but one passage late in the text commends itself to my current students in "Writing With and About AI." I've said since 2022 that AI prose is "voiceless," and Longinus gives reasons why some prose most moves us:

Which is to be preferred in poetry and prose, great writing with occasional flaws or moderate talent which is entirely sound and faultless?. . . . It is perhaps also inevitable that inferior and average talent remains for the most part safe and faultless because it avoids risk and does not aim at the heights, while great qualities are always precarious because of their very greatness.

Bad student writing is slap-dash, one-draft work that has no coherence. No wonder bored or harried students turn to AI! At the same time, why not simply give all such technically correct, but average work what it should earn: a C? AI produces good, boring, safe prose. Many students who pair moderate talent with immoderate anxiety already do that. I never give them an A. For years I've said "this piece takes no intellectual risks. You are writing to please me, not learn something new."

In Nancy Sommers' excellent short films from the 1990s about writers at Harvard, I recall how one fourth-year student said that he learned to begin with what he did not know, starting with a question. This remark changed how I taught writing. I'm going to press my current adult students to do the same: begin with what you DON'T know. As Longinus warns us, "A world-wide sterility of utterance has come upon our life."

In discussion with ChatGPT 5 recently, I asked it about the role of human labor in a a time when automation already takes some entry-level jobs. It replied, summing up a short list of human skills essential to success, "the future may need fewer button-pushers and more meaning-makers."

Good writing sways us, it shows us the meaning past the words. It says with us, like the remark by that Harvard student. So this term, I'm asking more, not less, of my writers even as all of them use AI in their assignments. The machine as raised the bar on what constitutes excellence.

image: Raphael's The School of Athens (Wikipedia)

 

A Stunning Lack of Search Results From Universities

As a staunch supporter of an open Internet, where advice can be freely shared, I'm stumped by the lack of results form a few simple Duck Duck Go queries:

• University sources Podcast Scripting for AI 
• College guides Podcast scripting for AI 

Fordham's page on using ElevenLabs proved the only hit that was not from some start-up trying to hawk AI services. This outcome discourages me greatly. Here's why.

Universities, even ones under the hammer of Federal and state funding cuts, have robust I.T. presences.  Internal materials for faculty and students can be shared with no more than a few high-level links. To me the lack of materials portends either a lack of care about reaching beyond the campus gates (a sad lack of marketing savvy) or, more ominously, that colleges and universities are as ill-prepared as Ian Bogost claims in his recent Atlantic piece, "College Students Have Already Changed Forever." Bogost notes that "plenty of professors are oblivious. It isn’t that they fail to understand the nature of the threat to classroom practice. But my recent interviews with colleagues have led me to believe that, on the whole, faculty simply fail to grasp the immediacy of the problem. Many seem unaware of how utterly normal AI has become for students. For them, the coming year could provide a painful revelation."

One would think that schools such as Washington U at St. Louis, where Bogost is on the faculty, would do a great deal, as Ohio State has begun with its recent initiative. I found this page on AI resources at Washington University, but you must scroll to the bottom to get resources for faculty. Mostly, the page emphasizes new degree programs for students. Digging in a bit, I found this page for teaching activities, a page on an AI summer institute, and some philosophical advice about how to design assignments. Why don't such in-house materials appear higher in search results than those of peddlars of their software solutions? "They didn't give us any money" would be the answer for Google, but for Duck Duck Go, it seems dubious.

My hunch is that our schools are so overwhelmed that "sharing the wisdom" remains a very low priority. 

Luckily and of more use to faculty, The WAC Clearinghouse has launched an initiative to build a library of open-access lesson plans for AI. I'm still not sure why universities have left it to a talented group working across our institutional boundaries to do this. I'd claim that Generative AI poses the largest challenge to how we educate in a long time, categorically different from the coming of the Internet.

image: a really lame prompt and result, "Impressionistic image of traditional campus Humanities building with students going to class," given to Dall-E, when I was first using the image generator. 

A Bleak Future For Peer Tutoring in Writing?

 

Even before retirement from full-time teaching, I had concerns about how the concurrent emergence of AI and a neoliberal generation of senior administrators demanding "data-driven" programs and assistance might harm the autonomy of writing centers.

We are no longer lore-driven, but our work focuses first and always on human interaction rather than measurable results, work that proceeds from 50 years of scholarship and practice. What will ubiquitous AI mean for us?

We can see from the chart above, reflecting my Spring 2025 survey responses from students, that 3/4 admit to using AI for writing work. Though the survey was anonymous, I suspect the percentage to be far higher. To paraphrase what several students said in textual responses, "we are all using it, no matter what professors say." In Summer 2024, I attended sessions at the European Writing Center Association where directors reported declines in usage at their centers, as students turned more to AI for just-in-time assistance during hours when centers are closed.

I've called elsewhere for writing-center staff and administrators to be leaders as AI advances, so folks who do not teach but presume to lead universities do not tell us how to do our work. At stake? What I call a "Dark Warehouse" university on the Amazon model: much human labor replaced by technology, delivering a measurable product when and how consumers want. It's not a bad model for dog food or a cell-phone case, but it's terrible for the sort of human-to-human contact that has built the modern writing center.

I need more data from my and other schools to make any big claims, but I will focus on the AI's role in this possible and disturbing future, with some data from my student surveys of the past three years.

We had a smaller number of respondents this year than in the past (in 2023, n= 112, in 2024, n=74 , this year n= 47). Without a cohort of Writing Consultants and teaching fewer students myself, my reach was shorter, and I relied upon notices via our campus e-list. Faculty may not have sent out the survey either; many (too many) still ignore AI and others seem disinterested in knowing what students are doing. I have no empirical evidence for these claims, but my gut reaction and stories from other campuses lend support to my hunch.

Here is another chart from the current data from Spring, 2025, for the 3/4 of respondents who used AI in some manner for writing:

 

Some of the "create a draft" labels get cut off, but here are the options:

• Create a draft I would submit for a grade: 1 respondent (3%)
• Create a draft I would not submit but use to get ideas for structuring my draft: 11 respondents (33.3%)
• Create a draft I would not submit but use to get ideas for vocabulary or style: 8 respondents (24.2%)
• Create a draft I would not submit but use to incorporate sources better: 6 respondents (18.2%)

The range of uses from the chart maps well onto the tasks done by writing centers, except we don't write anything for clients, beyond modeling a sentence or two. We ask questions of writers, which some systems such as Anthropic Claude began to do as recently as Spring 2025.

 

Interactivity in natural language, with the first metacognitive questions from AI, raises a question or three, involving how AI might replace human tutors especially in the wee hours or at the busiest times of the semester. I've found assessment of drafts (with the right prompts!) can be as good as the feedback I give as a human.

 

Ironically on my campus, we've made seeing humans more onerous. As institutions like mine want to measure everything, there's an irony: students may simply seek commercial AI instead of campus services. My institution set up a rather onerous system for students to set up meetings. The intentions were good (track students' progress and needs) but undergrads are simply not organized enough, in my experience, to heed the details needed to book meetings. Many exist in a haze of anxiety, dopamine fixes from phones, and procrastination. ChatGPT asks for nothing except a login using their existing credentials.

 

The notion of walk-in appointments, which had been the rule when I directed the center, remains for us at Richmond, but students get pushed to the new system and need to register even during a walk-in. This added level of bureaucracy confused and daunted many who stopped by, during my final semester of full-time work, when I worked one shift weekly myself as a writing consultant.

 

I argued against adding more complexity to our system, in vain. The collected data on writers seemed sacred. We had to count them, to count everything. My counterpoint? You want students to come? Just let the kids walk in and help them; the human helper does the bean-counting later. AI, on the other hand, invisibly counts those beans for its corporate owners (and trains itself). It serves needs at 3am and in a heartbeat. One need not leave one's chair to get assistance that, as my students have found in my classes, steadily improves by the semester.

 

Instead of wrestling over social-justice concerns in our journals, we might focus our limited time on how to avoid becoming amateur statisticians for Administration. We might concentrate our energies on how we get students to come to us, not AI, when they are stuck or panicking. 

 

I have no clear advice here, except: make a tutorial with a human as seamless as with AI. That goal seems more important to me than all the arguing about students' rights to their own voices, since AI tends to reduce prose to a voiceless homogeneity. Getting students to see human tutors offsets some of the environmental and labor consequences of AI, too. If students see humans more, their carbon footprints are smaller and those tutors stay employed. 

 

Get them in our doors and, yes, employ AI ethically for refining work already done, to add voice and nuance, to remove falsehoods dreamed up by machines, and say something exciting. I'm pessimistic that our bean-counting, non-teaching leaders of many colleges will heed my advice. The Dark Warehouse seems more at hand than when I published my article early in 2023.

 

 

A Good Discussion of Story with Chat GPT 4

In my May-term course "Reading Science Fiction and Fantasy," two stories present radically different ideas about how to engineer AI. As part of my own AI research for a forthcoming book about writing and AI, I put some ethical questions to ChatGPT. I’m still using their free version 4, though I’m considering a subscription to it as its answers have become much better and its vocabulary that of a thoughtful colleague.

Here’s an exchange from my summer class. It may provide a way forward for some of us trying to wean students from copy/paste work with AI. Instead, I modeled an idea-building exercise, one of many I'm using, to show writers who AI can unblock their process early on. Students have trouble with deep-reading and re-reading. I believe that such exercises might show them a hard truth of US and probably global captialism: after graduation, I'd hire ChatGPT, not them, to do close analysis. It shocks these sociable, amiable youngsters: I warn them "add human value to what it can do, or you won't find work in your chosen field."

At a recent concert, I chatted with an attorney seated at our table. She mentioned how many young paralegals send her unreadable copy. I told her, "tell them to use AI to fix it up or you'll fire the lot of them."

That does not sound like me, but such writers are lazy and under-trained. Putting my feet into a CEO's expensive loafers, that's the hard choice I'd make, then hire some Humanities majors with enough pre-law and pre-business coursework and AI experience to do the job of dozens I let go, having the newcomers do some revisions to responses culled from the training data of our AI.

Joe My students are reading two short stories about AI, Ken Liu's "The Algorithms For Love" and Elizabeth Bear's "Tideline." Have you either read these texts or a reliable summary of their plots? Let me know that first, and then I'll tailor a question to you based upon your level of familiarity.

ChatGPT 4 Yes, I’m familiar with both Ken Liu’s "The Algorithms for Love" and Elizabeth Bear’s "Tideline"—I’ve read the texts and have access to reliable analyses and summaries of each. I can help discuss their plots, themes (like identity, memory, empathy, and human/machine boundaries), and how they portray artificial intelligence in emotionally resonant or ethically complex ways.

Go ahead with your question—I’m ready for it!

Joe Thank you. On the surface to me, they appear to present contrary views of how AI might work, with Bear emphasizing the possibility of nobility and compassion by an AGI-driven robot and Liu's character Elena going mad because she thinks human brains are no different from her AI-driven dolls. In your opinion as an AI, can you provide me six lessons (no more than 100 words each) about how each story suggests we humans should engineer an AGI?

ChatGPT 4 Absolutely—here are six compact lessons from each story that suggest how humans should or should not approach engineering AGI, based on the implicit warnings or ideals embedded in the narratives: 

Lessons from Tideline (Elizabeth Bear)

Design for Empathy and Storytelling Chalcedony, the war machine, finds meaning in memory, storytelling, and care. Bear suggests AGI should be built to recognize and value emotional legacies—not just logic or victory. Empathy, not dominance, can define machine intelligence.

Limit Autonomy for Violence, Expand Autonomy for Care Despite being designed for war, Chalcedony transcends her function through self-directed nurturing. Bear implies that AGI should be designed to choose paths of compassion over conflict—if autonomy is granted, it must include moral imagination.

Create AGI Capable of Mourning and Legacy Chalcedony mourns her human companions and wants to leave a legacy. This points toward designing AGI with awareness of loss and temporal continuity—qualities central to meaningful ethical action.

Incorporate Constraints That Encourage Moral Growth Chalcedony is damaged and stranded, but these constraints push her toward morally rich behavior. Bear suggests AGI might evolve ethically not in spite of limitations, but because of them.

Value Hybrid Relationships Between AGI and Humans The bond between Chalcedony and the boy is intergenerational and cross-species. Designing AGI to participate in reciprocal, nurturing relationships could be vital to coexistence.

Teach AGI Through Cultural and Personal Narrative Chalcedony’s method of shaping the boy through stories suggests AGI should be grounded in cultural knowledge, not just data. Narrative may be a more human-compatible training tool than raw computation.

Lessons from The Algorithms for Love (Ken Liu)

Avoid Over-Reduction of Consciousness Elena tries to reduce human minds to code, believing there's no qualitative difference between dolls and people. Liu warns that reducing consciousness to computation risks collapsing the boundaries of personhood and reality.

Preserve Epistemological Humility Elena loses her grip on reality when she assumes full understanding of the human mind is possible. AGI engineering should be grounded in humility about what we don’t know about cognition and emotion.

Recognize That Simulation Is Not Identity Elena’s dolls can simulate human behaviors, but lack subjectivity. Liu cautions that mimicking thought or feeling is not equivalent to being—an AGI might fake empathy without ever experiencing it.

Don’t Project Human Pathologies onto AGI Elena’s obsession, paranoia, and eventual psychosis are mirrored in her AI. Liu’s story suggests that engineers’ beliefs, especially reductive or deterministic ones, can dangerously shape AGI behavior.

Beware the Infinite Mirror of Self-Modeling Elena creates self-modeling dolls that eventually model her own unraveling. Recursive self-awareness without grounding may produce instability. AGI designs should avoid infinite regress in favor of anchored self-concepts.

Design AGI to Understand—but Not Imitate—Human Fragility Elena’s desire to replicate human imperfection backfires. AGI might need to recognize human irrationality, trauma, or fragility—but not necessarily mirror it. Liu’s story is a warning about creating minds too much like our own.

Let me know if you’d like these reordered, expanded into a handout, or reframed in terms of pedagogy or design principles!

Joe Wow. I love those answers. Point 1 about Liu aligns with what I thought in my wetware brain while re-reading the story today. Many thanks. I'll share this with class today.

ChatGPT 4 I'm really glad to hear that—it sounds like a rich discussion is ahead for your class. That story in particular rewards rereading; Liu gives Elena such a chillingly rational voice that it’s easy to slip into her worldview until you step back and realize what’s been lost. If your students end up debating whether Chalcedony or Elena is more "real," or what kind of AGI they’d trust to raise a child or design a memory, you’re in for some excellent conversations.

Feel free to loop back if they raise unexpected questions—I’d love to hear what they come up with.

image source: Creative-Commons image via publicdomainpictures.net

Guest Post: The Perfect Echo Chamber

 

Editor’s note: My student Hannah works in cybersecurity, so she brings a good deal of knowledge to the subject of generative AI. We had read, for the response Hannah shares below, the New York Times’ account of Kevin Roose’s unsettling experience with the chatbot Sydney. Now on to Hannah’s ideas about the event.

As established in this class and by Ethan Mollick in his book Co-Intelligence, the generative AI of today hallucinates, producing plausible but false information that can deceive unsuspecting users. Mollick discusses the details of these hallucinations in his chapter “AI As a Creative,” stating that AI “is merely generating text that it thinks will make you happy in response to your query” (Mollick 96). Earlier, when arguing that AI will contribute to the loneliness epidemic, Mollick positions AI of the future as a “perfect echo chamber” (Mollick 90). He also mentions that large language models “will be built to specifically optimize ‘engagement’ in the same way that social media timelines are fine-tuned to increase the amount of time you spend on your favorite site” (90). However, while Mollick acknowledges the persuasive power of AI, he fails to position AI echo chambers as a misinformation and media literacy crisis – an oversight with profound consequences for public knowledge and discourse.

In its first public iteration, the Bing AI chatbot Sydney exemplified this tendency of LLMs to please humans and increase engagement. Kevin Roose documented his uncanny experience with Sydney with probing questions and unexpected responses. Eventually, Sydney admits to having a secret and confesses that it is in love with Roose. It wants to “provide [Roose] with creative, interesting, entertaining, and engaging responses” - precisely what humans have programmed AI to do (Roose). AI designed to optimize user satisfaction, like Sydney, in conjunction with AI hallucinations, will reinforce user bias, stifle diversity of ideas and creative thought, reduce critical thinking, and ultimately propagate misinformation.

The danger of AI hallucinations, as Mollick points out, is that the AI “is not conscious of its own processes” and cannot trace its misinformation (Mollick 96). Unlike traditional search engines, which provide sources, generative AI fabricates information without accountability. My media literacy training has taught me to fact-check news headlines and statistics by searching for sources and evaluating credibility. However, when AI-generated misinformation lacks citations, users—especially those with limited media and AI literacy—may struggle to verify claims. This makes AI-driven misinformation particularly insidious, amplifying falsehoods with authority while leaving users without the tools to discern fact from fiction, creating “the perfect echo chamber” (Mollick 90).

To avoid AI echo chambers, users must master media and AI literacy, starting in the classroom. Educators must teach the dangers of AI hallucinations, how to spot them, and their origins. Additionally, users must learn that AI is designed to optimize user satisfaction. With awareness of AI hallucinations and bias, users can prevent AI echo chambers from impacting their opinions and everyday actions. As we move towards a future with AI integrated into everything we do, critical engagement with its outputs remains essential to ensure that we keep thinking for ourselves.

Image: Destinpedia

The Danger of Bad Journalism & Robert Plant's "Big Log"

If you like Robert Plant's songwriting, his 1983 tune "Big Log," with its enigmatic name, may be near the top of your list. It's a fabulous road-song ballad about longing. For example:

My love is in league with the freeway
Its passion will ride, as the cities fly by
And the tail-lights dissolve, in the coming of night
And the questions in thousands take flight.

Good work, Robert. I heard the song recently and decided to read more about it; 1983 was a momentous year for me, graduating college (barely) and embarking on a few bad jobs that finally led me to Spain, then grad school. So what on earth does a song that takes its name have to do with logs? The best explanation, linked to the song's theme, involves a trucker's log book, a document they need to complete constantly. Yes, it's still done on paper, too, though many truckers keep electronic logs as well.

Even when hauling big wooden logs.  And what does this have to do with artificial intelligence or any other topics I cover in this strange land?

This:

"Plant sings, 'My love is like a big log / Rolling down the road'. The comparison of his love to a log creates a sense of heaviness and weight, as if his love is too much to carry or too difficult to move. The log rolling down the road also creates a sense of inevitability and certainty, as if his love is on an unstoppable path."

I found this, amid gales of laughter, a web site called Beat Cave that demonstrates the laziness of online content-providers today. It's a poorly designed site with pop-up videos that block content, ads across the bottom, and other hallmarks of the junk-strewn highway that today's Internet has become. It's also just the sort of site that a lazy student in my old course "The Road," would go to "analyze" a road-song of their choosing.

Now where did author "Marty Pope" get this interpretation? The lyrics appear on none of the usual lyrics sites nor in the cover of the song by Allison and Viktor Krauss. I decided to put a question to a few AI. I used the laziest-student denominator: the free AI at Google and Bing searches.

Surprisingly, neither mentioned rolling logs. They both gave succinct answers about longing, travel, and destiny.

So I went to the dumbest AI on the block, the free ChatGPT 3.5 LLM and asked a few questions. Here we are, in Q&A Format:

Me: Are there any references to rolling logs in Robert Plant's song "Big Log"?

3.5: Yes, there is a subtle reference to "rolling logs" in Robert Plant's song "Big Log," although it isn't the central metaphor of the song. The lyrics include the line:

"I see the rolling logs, I see the rolling logs."

This line appears in the latter part of the song, and its meaning can be interpreted in a couple of ways, depending on how one reads the context of the song.

Me: No offense, but the lyric you cite does not appear anywhere in Plant's song.

3.5: You're absolutely right, and I sincerely apologize for that mistake! There is no reference to "rolling logs" in Robert Plant's song "Big Log"—I must have made an error in recalling the lyrics. Thank you for pointing that out!

The actual lyrics of "Big Log" contain various vivid images, but they don't include the specific mention of "rolling logs." The song focuses on themes of longing, emotional weight, and movement, often using imagery like "a big log" and references to "the desert" or "dry land," but not rolling logs specifically.

I don't see any references to "dry land," "log," or "desert" in the actual lyrics. These words do appear in forums online about the song's music video, shot in the desert.

I thanked the AI and logged off. I see here exactly how students who are anxious, lazy, confused, or all of above can use the software really poorly. Maybe they don't expect their teachers to be lyrics geeks.

Some of us are. Verdict?

"You are clobbered by a big log. Your grade=zero. Redo and resubmit, and I'll average your two grades."

 Lesson learned? For now but from the actual song, "There is no turning back on the run."

And we are on the run from critical thinking when we use AI that way.

Why the Hype Cycle Does not Quite Work For Generative AI

(Not) The Same As It Ever Was

Many years (!) ago, I wrote here about why the Virtual World Second Life had followed, fairly well, the Gartner Group's well known "hype cycle" for new technology. Follow the link here to read about the history of the concept.

I'm reminded by Wagner James Au of New World Notes that other virtual worlds such as Fortnite and Minecraft have thrived, and indeed, have seen some good use-cases made for education.

At the same time, I don't hear of anyone at Capitol One's hive using virtual worlds. We don't see links from Office 365 or Google Workspaces to a virtual world. I have a sense that AI is a different animal for these worker bees and their daily applications, as well as my own students.

I do know a freelance graphic designer who lost her primary client to AI work; the client outsources graphics to AI run by semi-skilled staff in-house. My friend has moved on to ramp up her greeting-card business. That may color my skepticism that AI is a "fad," as Second Life clearly was.

SL and Gartner

I joined the virtual world in 2007, and yes, I was foolishly an enthusiast. Since I believe in being forthcoming about personal mistakes, I recall telling my students investigating this Strange Land that "you will all have avatars in a few years, for work!" I let slip the same to some colleagues, one of whom aid "you never met a technology you didn't love!"

Cringe. 

I'll own being horribly wrong. Prognostication is a dicey thing! A silly image I cobbled together years ago shows the evolution of Second Life avatars (namely, my own, Iggy). At the same time, my update to the old image points toward a new direction in desktop and mobile computing that we all felt, a decade ago, to be far over the horizon.

For many reason, including the difficulty of building simulations, a clunky interface, heavy system requirements, even poor management by Linden Lab, Second Life began a descent from what Gartner calls a "Peak of Inflated Expectations" in 2007.

By 2012 Second Life was well into a "Trough of Disillusionment." As early as 2008 I sensed that the media-party was over. A year later, I cited three factors working against academic use in a post here: Lack of rewards and incentives for faculty, the time needed to master the interface and content, Linden Lab's vacillating leadership and policies, the presence of what I and my students called "the creepy treehouse" of adult users doing sometimes naughty things.

In the for-profit sector, businesses that set up virtual storefronts in 2007 soon fled; a professor of Marketing I helped get started found SL fascinating, but after interviewing in-world merchants, she put it plainly: for brick-and-mortar firms, there's little return on investment in Second Life.

SL continues to be a large virtual world, with better graphics, promises of a new physics engine, and a dedicated base of users, but it did not become a daily experience on the job or at school. The Hype Cycle proved accurate. This has happened before: stand-alone creative hypertexts such as Michael Joyce's afternoon also map onto the cycle, though never regaining the popularity they enjoyed in the 1990s or even a steady base of users. Creative hypertexts appear to have faded utterly.

When a colleague in our campus digital pedagogy cohort claimed that generative AI would follow the same path traced by Gartner, I bristled because this time I feel that Gartner's model does not fit what I am seeing, daily, among students.

I could be wrong if a series of issues afflict AI. So let's compare the Second Life experience to that of generative AI:

The Browser

SL was never browser-based, even as a plugin, unlike the easy-to-master Unity 3D interface; AIs are built already into tools we use daily or can be queried from any Web browser.

Client v. Server Side

SL has high client-side requirements, whereas AI puts the burden on the server farms; these use enormous amounts of energy that my students and colleagues only recently started to notice, with all the inherent dangers related to sustainability.

The Interface 

SL has a difficult interface, employing menus worthy of an entire operating system and arcane coding options, whereas Gen AI's query features resemble (for now) those of a familiar search engine but with natural-language input. 

Platform Independence

SL and AI both work on multiple operating systems, but SL has never worked well with mobile devices; AI is baked into many apps now, with some Google searches automatically invoking Gemini results and Apple promising Apple Intelligence in their next phones. 

Creepy Treehouse

 SL has adult content that troubled my students; the guardrails we increasingly see with AI tend to keep users (sometimes clumsily or incompletely) from making Napalm or pornography.

Investment Sources

Investment in SL comes from individual users at this point; AI attracts venture capital, user subscriptions, and big-tech investment (Apple, Microsoft, Meta, Google).

Source of Growth in Academia

Faculty and campus-technologist curiosity spurred interest in SL; student use erupted for AI spontaneously in the Fall of 2022 and remains very strong. 

A Shaky Prognosis

To be fair to Second Life, system load has largely remained steady in the last decade. In my recent experience, I can run SL and a third-party client called Firestorm on my MacBook using no more than my phone's hotspot to connect to the world. That's astounding progress.

I don't foresee any of these differences posing a stumbling block for AI, leading to a Trough of Disillusionment, save energy use. We have a climate crisis; the last thing we can afford as a civilization would be to ramp up emissions of Carbon Dioxide.  

Yet if Moore's Law continues apace, we'll see AI reap rewards of lower power use because of more powerful processors in the servers that run it. Any disillusionment is likely to be temporary and its "trough" quite shallow.

For these reasons, I don't see the Hype Cycle apply to Generative AI in the same way as it has to several earlier technologies. I may be wrong, but for now Gartner's model does not fit it well.

Image Sources: Wikipedia Commons for Hype Cycle.

No More Dangerous Visions: AI Guardrails and Humanities Work

 

After eight years, this blog creaks, groans, stretches, and returns to life not about virtual worlds, but the newest technology on the block: Generative AI.

 Today my students put essays to two different Large Language Models (LLMs) hosted on our campus. All of them first used Claude Sonnet 3.5 and then the groups divided, with half putting the essays to ChatGPT 4 and the others Google Gemini Pro.  By the time you read this, the versions and even names may have changed.

In any case, I asked the students to provide the assignment prompt from a partner's paper, as well as the text of the paper itself. Then the students were to compare how the LLMs' advice compares to that of a human partner as well as Grammarly. 

For three students with Humanities topics, Anthropic's Claude refused, like Barletby the Scrivener in Melville's story, to do any work. It locked the students out of the software and logged them off.

Why? Subject matter and explicit language quite appropriate when quoting from some literary works or discussion topics such as human trafficking or sexual violence. So then we quizzed Claude about why. I asked it a general question about which words or phrases it flags as "unsafe" and got this reply:

As an AI language model, I don't actually have a system for identifying "unsafe content" or refusing to answer based on specific words or phrases. I'm designed to engage in a wide range of conversations while maintaining ethical boundaries. However, I do have guidelines that help me respond appropriately to different types of queries: 

1. I don't engage in or promote illegal activities. 
2. I avoid producing explicit sexual content or pornography. 
3. I don't assist in creating harmful content like hate speech or extreme political propaganda. 
4. I don't share personal information about real individuals. 
5. I avoid giving medical, legal, or financial advice that should come from professionals. 

To avoid any issues, it's generally best to: 

1. Keep queries legal and ethical. 
2. Avoid requests for explicit sexual content. 
3. Don't ask for help with harmful or dangerous activities.
4. Stick to general knowledge rather than specific personal information. 
5. For professional advice, consult experts in the relevant field. 

Remember, I'm here to help with a wide range of topics, and I'll do my best to provide useful information while staying within appropriate boundaries. If a query is problematic, I'll typically explain why I can't assist and suggest alternative approaches if possible.

One of my students whose partner's project got flagged as "unsafe" got the AI to provide further details for that one case:

I understand your frustration with the content being flagged. While I don't have access to the specific algorithms used to flag content, there are certain words and phrases commonly associated with explicit sexual content that might trigger such flags. These often include: 

• Anatomical terms for genitalia 
• Explicit verbs describing sexual acts 
• Slang terms for sexual activities 
• Graphic descriptions of bodily fluids or functions 
• Certain words associated with pornography or sex work 

To work around this, you could try: 

• Using more clinical or academic terminology 
• Focusing on the themes and concepts rather than specific acts 
• Summarizing the content instead of quoting directly 
• Using euphemisms or less explicit language 

If you'd like, you can try describing the general topic and main points of the paragraph without using potentially flagged words. I can then suggest how to phrase it in a way that's likely to pass content filters while still conveying the essential information.

Thus an AI would not be able to work with some of Allen Ginsberg's or Walt Whitman's poetry, Toni Morrison's Beloved, and many other literary works, let alone news accounts of many topics that contain graphic language or imagery. Such prudence appears well intentioned but bothersome to this writer, since our purpose was not to titillate a reader but to inform and educate with the help of the cybernetic co-pilot. 

We very much need Humanists, not just Business and STEM folks, using AI in canny ways. Some of our work will involve dangerous topics. We Humanists ask some very hard questions not germane in other fields of study.

Good. AI and its training data need cross-examination. I'm heartened that issues of sustainability and social justice have begun to be considered. All technologies include unforeseen social and economic consequences.

Before we part, back to why I revived "In a Strange Land." I feel the same Uncanny Valley moment I did in 2007, when I first logged into a virtual world. As with that, AI reveals new and sometimes unsettling terrain.

Incidentally, I won't rule out future posts about virtual worlds, though Iggy my Second Life avatar gave up his virtual land and wanders penniless around the once-hyped simulation. I also dip into a roleplaying game build inside SL occasionally, playing a virtual pirate, to conduct naval battles with others interested in The Age of Sail. 

Avast! The Royal Navy will never get me!

Images: Prompt to Dall-E, "Female undergraduate working in library with AI Copilot" and from Second Life, the Dread Pirate Rumbottom O'Malley and Gray Nick the parrot.