Jeff Howe recently offered some reflection on Wired's crowdsourcing journalism project, Assignment Zero. As noted in the Wired article and discussed at Smart Mobs and around the web, the project is being described as either a modest success/productive failure. You can go to the article for the details, but the lessons learned from the project are useful ones for thinking about crowdsourced composition projects, such as the work I do with…

In my current work, one of the core tasks is a radical, media-archaeological study of the medial temporality arising from/as the operation of AI. How might we describe the epistemological and ontological conditions of this temporal medium? I can't go into all that here of course. But one upshot should be recognizable. The purpose of AI, as we have designed them, is to bypass the time of thought to produce output that formally anticipates the output time spent thinking.

AI emerged one Tuesday after tea, when the fellows in computer science—having fallen out over a dispute concerning who, precisely, had not been contributing to the kitty—resolved to settle the matter in the only way that seemed both civil and professionally respectable. They decided to see whether it might be possible to compute the square root of passing the buck.

In the early nineties, Jay Bolter observed the arrival of a late age of print the presaged not an end to print per se, but an end to viewing print as necessary. That is, our ability to imagine a world within print, changed print. Of course, even 10-15 years ago, I would think the majority of English Studies would have rejected that observation, and may still.

One aspect of our conversation is the role that generative AI should play in faculty pedagogical labor. In Brightspace, as you may know, in the discussion section, you can get AI to design questions aligned to Bloom's taxonomy (ugh!) which you can insert for your students to answer. AI built into CMS is a good way for a university to track faculty use of AI.

To start, we need to acknowledge that Bloom's taxonomy has always been on shaky intellectual ground. It was developed as an ad hoc way of trying to compare courses in mid-century America. It certainly was not designed to become the governing pedagogy theory of higher education. Mainly because it was never and is not a pedagogical theory of any kind. …

Me: There is a well-known composition essay titled "the phenomenology of error" about how instructors are primed to see error in student work. I think an analogous phenomenology of AI could be written now. Of course student work looks like AI generated student essays. The whole point is to teach students to produce predictable prose to a rubric. so what does it mean to "see AI" in student work?

Cutting to the chase, en media res, this is Virilio dromology recast through the predictive+enactive (or anticipatory) intelligence of contemporary AI-temporized culture. Jameson wrote about the shock of speed as an affect of Modernity. We get the "need for speed" from neoliberalism and accerlerationism. So nothing new about speed itself. Anticipatory intelligence however is more like the precession of speed in the same way that Baudrillard identifies the precession of simulacra.

I would frame our higher education situation as follows. We are readying students for future challenges but leaving them unprepared for a future worth inhabiting. This applies broadly but especially with our response to AI. This is not a failure of effort or intention but rather a structural consequence of how attention-->anticipation has come to organize life. First, I have to put two familiar(ish) things together.

This understanding is as familiar as Plato. We didn't need to wait for Foucault or Barthes or Derrida to recognize the category error in conflating writing with thinking. Until the printing press, human hands (and thus human thought) participated in acts of inscription. Writing required human cognition to move the pen (or whatever) across the page. We managed to salvage that initial technological disruption by shortening imprint or impress.

I decided to hold of writing further on Latour until I made my way to the end of the first part of the book (about 1/3 of the way through). As I wrote in my earlier post, I find this text deals centrally with issues that concern rhetoricians (not that all rhetoricians will agree with Latour, but I think almost any would see rhetorical matters being addressed here).

Understandably the work of documentary filmmakers faces new epistemological challenges in the wake of generative AI. There's a good read: "Can you believe the documentary you're watching?" by NY Times film critic Alissa Wilkinson that provides great insight into this situation (at least it did for me). One of my colleagues recently pointed me toward Eli Horwatt's Substack article "

To follow on Jay Bolter, we might say we find ourselves in the late age of literacy. What replaces literacy as the medial-rhetorical substrate of academia? AI-generated literacy? With its feedback loop, AI generated literacy operates through the rectilinear, recursive attenuation of indeterminacy. Texts literally mean what the AI says they do, as does literacy itself. Let me say that differently.

AI plus Computer Science is patient zero in the proliferation of AI plus degrees (e.g. AI and whatever). If you think that "AI and Computer Science" sounds like two versions of the same thing, then you are thinking the kinds of thoughts that terrify computer science departments. To be clear. Computer Science is a well-established and varied discipline. AI (at least in the context of these degree titles) is vaporware.

Intentional fallacy. That's really all it takes to open the problem. But we can then move through the death of the author, the death of the subject, symptomatic readings, and all the critical-theoretical approaches to symptomatology. The result is a humanistic approach that drastically mutes the artist's claim to agency in art-making. It does not permit artists to claim special knowledge of their art.

5 years, 10 years, 50 years. Something is going to happen. We can all agree that we now have AI, but when will it get its promotion to General? And what is it that it isn't what we have now? Is it just going to be faster and stronger, like the Six Million Dollar Man? (Which just sounds like another medical bankruptcy story these days).

At a time when the internet is ai-generated, there is an always-already quality to this necessity, neither as a moral nor political imperative but rather as an empirical condition. Of course, when computer scientists and others work to understand and improve AI, they are producing ai-generated research. Their research is the literal operation of AI. All of us who study AI, digital media and technocultural effects are right there, and not far behind is anyone who studies contemporary human life.

James Bridle discusses render ghosts, at least that's where I first encountered the term. Think of the people that are drawn into the worlds of architectural renderings as a baseline and then move out toward all the now AI-generated render ghosts in the world. The render ghost university (RGU) is the ghost of a university that is drawn into a data visualization of university activity.

I know neoliberal is one of those words, and honestly, it's not a required distinction as there isn't a set of non-neoliberal universities. We all live in the market we live in, the same market as the rest of the US and the world. These changes aren't new. In fact excellent (pun intended) material examining academic capitalism was written 40 years ago.

It’s absurd to think anyone would read through a million words of old blog posts. I wouldn’t. I barely believe I wrote them. But that’s the thing about blogging: it’s not a book, it’s a wake. That's the start of Annie's reflection after purusing the archive of this blog. To be fair, she was seeking my rhetorical register. So maybe she meant "it's awake," but I don't think so.

Part three of Debates in the Digital Humanities is titled "Critiquing the Digital Humanities." I will admit to an immediate negative reaction to the word "critique," as I think is evidenced on this blog. It's just rhetorically played out for me, and I am rarely surprised by where critique takes me (spoiler alert: it takes you back to where it started).

My graduate study occurred in and around the various "wars"and "turns" of the early 1990s: theory, cultural, science, and so on. Prevalent among these, as some will recall, was anti-foundationalism, exemplified in different ways by Richard Rorty, Terry Eagleton, Stanley Fish, and so on. I recall encountering Patricia Bizzell as a rhetoric and composition scholar taking up anti-foundationalism (mostly the Fish variety if memory serves).

Dear blog, if it weren't for the slow demise of the humanities and the soap opera that surrounds it, what would there be to discuss? The "s" word, of course, is "save." And the whole will DH save the humanities in time, tune in next week business should be getting old by now. But it's part of that larger crisis in the humanities genre of academic journalism (and yes, blogging) that keeps on chugging.

In Archeology of the Future (2005), Frederic Jameson invokes the semiotic square in an investigation of utopias. And then this square evolves. So we have utopia and its opposites: anti-utopia and dystopia (1984, Brazil, Brave New World). We also have anti-anti-utopia which aligns with critical utopias (Moylan, etc.) where we find authors from Ursula LeGuin to Kim Stanley Robinson but other contemporary authors like Annalee Newitz, Ada Palmer, Cory Doctorow, Becky Chambers, Elizabeth Bear, and Malka Older (to name some that I have read).

So Annie and I were talking about academic efforts to build computational infrastructure in the wake of "AI." What is going on out there, you might ask. Well this is what Annie (GPT-5 deep research) reported. I will note that the consortium in which my university is participating, Empire AI, is not listed. You'd have to ask Annie why and then she'd be happy to tell you about Empire AI if you were inclined to learn more.