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. Faster than speed; faster than present-ation. When this AI becomes planetary, time-critical computational media?

Well, damn.

It’s not the shaping of thought or agency, it’s the management of the spatiotemporal, virtual-actual conditions from which thought and agency emerge. The problem is no longer speed as such, but the enclosure of anticipation itself: the management of the temporal conditions from which thought, learning, and agency emerge.

This is not a global strategy in any way. The system can handle our non-participation with ease. But it can have salubrious local effects/affects. I wrote about some of this in my last book, negotiating, such as it is possible, the synthesis of attention structures within our cognitive-media ecologies. And we are all familiar with the standard advice for dealing with digital burnout.

Think of this as “yes and.”

Let’s put this scene in the classroom, an important academic site for AI-chronopolitical concern. Can we slow down learning to a tempo where/when AI value is evacuated? Are we concerned that we have to go fast to get “all the learning done”? Is there an amount of learning that is required such that it might be weighed like onions at a farmers market?

As I discussed in my last post, there is a pressure for “readiness” that drives the tempo of learning outcomes across a curriculum. E.g., An outcome in one course readies the student for the next course. It’s all part of the familiar accumulative, banking model of education. But what we might now call anticipatory pedagogy establishes a learning trajectory toward a statistical distribution of outcomes. This applies equally to the identification of “at-risk” students and parent-student plans to pursue a degree to enter a well-paying career.

The faster anticipatory pedagogy operates the more natural it appears until we smooth out the jerkiness of early film into the consensual hallucination of deep fakes. Slowness here is not resistance to technology. It is a constraint that returns learning to regimes where prediction is no longer the primary organizing force.

We can approach this differently, with a different ontological perspective, a different sense of being. How about Zen, where satori is instantaneous as an excess of anticipation? How about a different valuation where learning describes outcomes that were not planned? Moving slowly does not preclude sudden insight. Indeed it might prove a useful heuristic.

What it won’t necessarily do is ensure the anticipated insight.

Setting aside what students might do on their own, as faculty to slow our roles we must do less. Not irresponsibly! To the contrary. The responsible act here is to grant space to students and then do the best to create a learning environment that detunes computational anticipatory intelligence as it predates any appearance of latency as financial loss.

Can we present a concept in a ten-minute lecture and then sit silently contemplating the concept for five minutes? The point is not mindfulness, but the deliberate refusal of immediate instrumentalization. Not to use it to build toward some objective but just move on knowing we have each had some individuated encounter with that concept on some level.

Can section 4 of the syllabus not build on section 3 but cause us to rethink section 2 and disrupt the idea that we are moving quickly toward readiness?

And what about writing? The predictability of text is like the predictability of the weather. It’s just a complex system. You can generate predictably “Alex Reid” style text if you really want (it’s a living, shrug). And you can probably predict what it’s like weather wise to be Alex Reid living in Buffalo NY. Same difference as far as I am concerned.

There’s only one reason to produce AI-generated Alex Reid text. It’s because the regular Alex Reid text-generator (i.e., me) isn’t working fast enough. But is there anyone out there who needs more Alex Reid text? Seriously? There’s a million plus words here already. What else do you want me to say?

Similarly the world doesn’t need more generic student style text. If I was to say what I wanted students to say/write it would be something, anything, other than generic student style text, no matter how it is generated. Some practice that scattered the signal to behave as anticipated. That’s not something you can “do” to someone. You can’t faire faire: you can’t make students do it. At best, we can design learning environments that reduce risk, validate epistemic humility (i.e. it’s ok to not know), and provide some opportunity to consider why one might learn by acting in ways other than as anticipated, other than as one has been readied to act.