Four Points about the Infrastructures of Professional Development

On Thursday, January 5, I participated on a round table at the 2023 MLA convention, organized by the MLA itself. The panel was called “Infrastructures of Professional Development.” Here’s the panel description:

This roundtable includes leaders who have developed technical, pedagogical, administrative, and organizational structures with potential to serve as sites for professional development. Brief comments will be followed by an open forum on how the MLA can learn from and collaborate with these leaders and others to grow and enhance professional development offerings in service to members across the career arc.

I was joined by Kathleen Fitzpatrick and Sonja Rae Fritzsche, both from Michigan State University. We each delivered short remarks and the proceeded to have a wide-ranging discussion. Here are my prepared comments, such as they were.

I appreciate the work that Jason Rhody and Janine Utell at the MLA have done to bring this group of panelists together. My opening comments are going to be brief, because I know the best part of these roundtables is the discussion that follows. There are four points I want to make today regarding “Infrastructures of Professional Development.” And I want to preface them by saying that I’m zooming out and offering broad generalizations here, rather than nuts-and-bolts details about professional development initiatives that I’ve been a part of or helped to build—though I’m happy to talk about those in the discussion. The reason I’m zooming out is because my own context—I’m at a relatively well-resourced small liberal arts college—may not be your context, and infrastructure, as well as what counts as professional development, is highly contextual.

I.

I want to call your attention to the word infrastructures in our panel title. It’s an odd word in this context. You hear infrastructure and you think roads, bridges, sewer lines, power substations. The underlying structures that make everything else possible. As Susan Leigh Star and Martha Lampland put it, infrastructure is “the thing other things ‘run on’” (Star and Lampland 17). And the funny thing about infrastructures—and I’m far from the first person to point this out—is that when they are working, you don’t think about them. They’re all but invisible. It’s when infrastructure breaks down that it becomes visible, or as Heidegger would put it (and forgive me for quoting Heidegger), they become “present-at-hand.” They are no longer transparent. They’re in your face. You don’t notice the road until there’s a pothole. You don’t pay attention to a bridge until it’s closed and you have to detour the long way around. You don’t think about the power until the lights don’t come on.

II.

Let’s think about two phase states of infrastructure when it comes to professional development. The first phase state: infrastructure when it works and is invisible; and the second phase state: infrastructure when it’s not working and very much visible. It presents a bit of a dilemma. Infrastructures for professional development, if they’re working well, you don’t even see them. You take them for granted. It makes professional development hard to talk about, to share ideas with others, to build on what’s working at other institutions or organizations. That sharing is one of the things I hope we get to do today.

The flip side occurs when the processes for professional development aren’t working—and I’m sure we all have war stories to trade. The infrastructure becomes visible, because it’s broken. But what’s needed to fix or repair or replace that infrastructure—we might call this speculative infrastructures—those possibilities remain out of sight. And in fact, discussion about speculative infrastructures is displaced by something else. I’m thinking of a dynamic that Sara Ahmed describes frequently in her work. When someone points out a problem, they become the problem, not the problem itself. Working in institutions, as many of us do, you’ve seen this. As Ahmed puts it in her “Feminist Killjoys” essay, when you are the one to point out a problem, it means “you have created a problem. You become the problem you create” (“Feminist Killjoys (And Other Willful Subjects)”). It’s almost as if the problem didn’t exist—or at least some people wanted to pretend it didn’t exist—until somebody pointed out the problem. So I think our challenge here, in addition to sharing infrastructures for professional development that are promising, is to diagnose infrastructures for professional development in a way in which our complaints don’t supersede the underlying problem. Ahmed’s latest book, Complaint!, is instructive here, especially since it’s centered on institutions. Ahmed observes that we often think about complaints as formal allegations—I lodged a complaint—but she shows how complaints are “an expression of grief, pain, or dissatisfaction, something that is a cause of a protest or outcry, a bodily ailment” (Complaint! 4). There is an affective and embodied dimension to complaints. So as we talk this afternoon, and if some complaints about institutions and organizations come up, let’s hear the complaints for what they really are, testimonies about our lived experiences.

III.

As a consequence of infrastructure often being invisible, the people who design, implement, and maintain those infrastructures remain invisible as well. This is true whether the infrastructure is a bridge or an online collective. If we think about, say, the work the MLA does to support professional development, most members of the MLA do not know who is actually doing that work to support professional development. Who are the faces? What are their names? We have Jason and Janine here, but most MLA members would be hard pressed to name the people, beyond Paula, who work to make the convention happen. And to be clear, the convention, whatever else it is, is an infrastructure for professional development. And if this were any other infrastructure, that invisibility would be something you’d want. If you don’t know the people making something work, if they can fade into the background while the thing functions seamlessly, that’s usually what you want. It means things are working. But, in my own subfields of digital humanities, media studies, and science and technology studies, there’s been a growing attention paid to the labor of people who make things, who make things run, and who fix the things when they’re broken. And this is something I think we in our respective institutions and organizations should consider when it comes to infrastructures for professional development. Not just, as I’m doing here, recognizing the work that everyone is putting in to provide opportunities for professional development, but actually putting forward the stories and aspirations of those of you, of us, who work on infrastructures that support professional development. In other words, step out from behind the curtain, and introduce ourselves to our constituents. Tell them our stories—your stories. What are our hopes and dreams, what do we get out of supporting you? Show how supporting professional development isn’t simply a transaction, but, it’s a relationship. Make it clear that whatever infrastructure you are providing is like Soylent Green, it’s made out of people.

IV.

This brings me to my fourth and final point. People. One of the lodestars for how I think about labor in the academy is Miriam Posner, at UCLA. Years ago Miriam wrote a blog post that I still think about all the time. The post is called “Commit to DH People, Not DH Projects.” Miriam is talking here specifically about the digital humanities, and critiquing the tendency to frame work in DH around projects. What if, she wonders, we put the emphasis on people, not projects? Let me quote her here: “What if,” Miriam writes, “we viewed digital methods as a contribution to the long arc of a scholar’s intellectual development, rather than tools we pick up in the service of an immediately tangible product? Perhaps we’d come up with better ways of investing in people’s long-term potential as scholars” (Posner). If we blur out the particulars of digital humanities scholarship here, and think more broadly about Miriam’s underlying point, it applies in so many ways to supporting professional development across the board, whether that development is focused on scholarly, pedagogical, creative, or even administrative pursuits. The infrastructures for professional development need to support people, not projects, not stages of their careers. People, not one-off workshops, not a conference here or there, not week-long institutes, not webinars. People, and people over a long period of time, people who evolve and grow over time. Professional development, in the end, is about people supporting people, people supporting each other.

Works Cited

Ahmed, Sara. Complaint! Duke University Press, 2021.

—. “Feminist Killjoys (And Other Willful Subjects).” The Scholar and Feminist Online, vol. 8, no. 3, Summer 2010, http://sfonline.barnard.edu/polyphonic/print_ahmed.htm.

Posner, Miriam. “Commit to DH People, Not DH Projects.” Miriam Posner’s Blog: Digital Humanities, Data, Labor, and Information, 18 Mar. 2014, https://miriamposner.com/blog/commit-to-dh-people-not-dh-projects/.

Star, Susan Leigh, and Martha Lampland, editors. Standard and Their Stories: How Quantifying, Classifying and Formalizing Practices Shape Everyday Life. Cornell University Press, 2009.

AI Dungeon and Creativity

In early January I joined a group of AI researchers from Microsoft and my fellow humanist Kathleen Fitzpatrick to talk at the Modern Language Association convention about the implications of artificial intelligence. Our panel was called Being Human, Seeming Human. Each participant came to this question of “seeming human” from a different angle. My own focus was on creativity. Here’s the text of my prepared remarks.

Today I want to talk to talk briefly about artificial intelligence and creativity. And not just creativity as it pertains to AI but human creativity as well. So, has anyone heard or played AI Dungeon yet?

AI Dungeon was released just a few weeks ago and it has gone absolutely viral. It’s an online text adventure you play in your browser or run as an app on your phone. Now, text adventure, that was a popular kind of game in the 1980s. A lot of people know Zork. In these games the player is offered textual descriptions of a house, a cave, a spaceship, dungeon, whatever, and the player types short sentences like go east, get lamp, or kill troll in order to solve puzzles, collect treasure, and win the game. There’s a parser that understands these simple commands and responds with canned interactions prewritten by the game developers. Text adventures are also known as interactive fiction and there’s a rabid fan base online that’s part geek nostalgia, part genuine fondness for these text-based games.

Interactive fiction often revolves around choice, where players have multiple ways to transverse the world and solve the puzzles. Following this generic convention, AI Dungeon opens up with major choice, literally which genre of text adventure you want. Fantasy, mystery, apocalyptic, and so on.

So here I picked fantasy and immediately I’m thrust into a procedurally generated story: a fantasy world entirely written by a natural language processing program.

Generating a static dungeon on the fly is one thing. But what’s amazing about AI Dungeon is that it’s not a scripted world so much as an improv stage. You can literally type anything, and AI Dungeon will roll with it, generating an on-the-fly response.

So here, we have a stock feature of fantasy text adventures, a dragon. And I eat it. The game doesn’t bat an eye. It runs with it and lets me eat the dragon, responding with a fairly sophisticated sentence that aside from its subject matter, sounds like something you’d read in a classic text adventure. “You quickly grab the dragon’s corpse and tear of a piece of its flesh.”

Let me be clear. No human wrote that sentence. No human preconceived a scenario where the player might eat the dragon. The AI generated this. Semantically and grammatically, the AI nails language. It’s not as good at ontology. It lets me fly the dragon corpse to Seattle. The AI is a sponge that accepts all interactions. As you can imagine, people go crazy with this. The amount of AI dungeon erotica out there is staggering—and disturbing.

Later I run into some people and I ask them about the MLA convention.

A man responds to my question about the MLA, “It’s a convention where all wizards use the same language. It’ll make things easier.”

Oh, that answer is both so right and so wrong.

So how does this all work? I obviously don’t have time to go into all the details. But it’s roughly this: AI Dungeon relies on GPT-2, an AI-powered natural language generator. The full GPT-2 set is trained on 1.5 billion parameters gleaned from over 40 gigabytes of text scrapped from the Internet. The training of GPT-2 took months on super-powered computers. It was developed by Open AI, a not-for-profit research company funded by a mix of private donors like Elon Musk and Microsoft, which donated $1 billion to Open AI in July.

One innovation of GPT-2 is that you can take the base language model and fine-tune it on more specific genres or discourse. For a while Open AI stalled on releasing the full GPT-2 set because of concerns it could be abused, say by extremist groups generating massive quantities of AI-written propaganda. In the more benign case of AI Dungeon, the AI is finetuned using text adventures scrapped from chooseyourstory.com.

There’s much more to be said about AI Dungeon, but I’ll leave you with just a few provocations.

1. Games are often defined by their rules. So is AI Dungeon a game if you can do anything?
2. Stories are often defined by their storytellers. Is AI Dungeon a story if no one is telling it?
3. And finally, a mantra I repeat often to my students when it comes to technology: everything comes from somewhere else. Everything comes from somewhere else. GPT-2 didn’t emerge whole-cloth out of nothing. It’s trained on the Internet, specifically, sources linked to from Reddit. There’s money involved, lots of it. Follow the money. Likewise, AI Dungeon itself comes from somewhere else. On one hand its creator is a Brigham Young University undergraduate student, Nick Walton. On the other hand, the vision behind AI Dungeon—computers telling stories—goes back decades, a history Noah Wardrip-Fruin explores in Expressive Processing. The genre fiction invoked by AI Dungeon has an even longer history.

All this adds up to the fact that AI Dungeon turns out to be a perfect object of study for so many disciplines in the humanities. Whether you think it’s a silly gimmick, an abomination of the creative spirit, the precursor to a new age of storytelling, whatever, I think humanists ignore AI storytelling at our own peril.