I recently rewatched Hannah Gadsby‘s two Netflix specials, Nanette and Douglas. I’ve linked here to the trailers for each of these specials but the trailers don’t hint at the brilliance of Gadsby’s work. If you haven’t seen them, these specials are worth your time. Full disclosure: I think Hannah Gadsby is a comic genius. Here’s why: she is such a master of her discipline that she is able to explain her discipline’s tools, methodologies, and ways of engaging with the world to her audience, subvert those tools, methodologies, and ways of engaging with the world but still achieve her disciplinary goals. Brilliant!
Nanette is ground-breaking. Some have called it “post-comedy.” Daniel Feinberg of The Hollywood Reporter calls it “a detailed summation of joke construction that could be a textbook on its own.” Gadsby talks about why laughter is good. Laughter releases tension and holding tension in the human body is not a good thing. And because laughing is infectious, you release more tension when you laugh with other people than you would if you laugh alone. A joke is just two things, needs two things to work: a setup and a punch-line. “It is essentially a question with a surprise answer,” she says. As a comic, her job is to “artificially inseminate” the question, the setup, with tension. And the surprise answer, the punchline, releases the tension by making the audience laugh. She is so good at it, she says, because that tension relief has been a survival tactic for her whole life. I won’t go on to spoil what she talks about for the rest of the special. It just needs to be experienced. It is profound.
As ground-breaking and profound as Nanette is, I think Douglas is an even better illustration of Gadsby’s mastery of her discipline. She talks about the criticisms she heard about Nanette. Those who didn’t like it said it wasn’t funny, that it was a lecture rather than a comedy show, that Gadsby herself isn’t funny. In Douglas, Gadsby leans into those criticisms to prove that she knows exactly what she’s doing. She starts the show with a synopsis of everything she’s going to do in the show and exactly how the audience is going to react. She even says she’s going to give a lecture in the middle of the show. She then does exactly what she said she was going to do and despite having been given the synopsis, the audience reacts just as she said they would. And her lecture is hilarious. This comedian understands comedy and how to make people laugh, even when she’s subverting the conventions of comedy.
In the Cluster Pedagogy Learning Community (CPLC), we talk a lot about how to engage our students in interdisciplinary work. Our colleague Abby Goode, in her article Slow Interdisciplinarity, writes that interdisciplinarity “entails a metacognitive awareness of one’s own discipline, and an ability to explain that discipline to others.” That is, in order to engage in interdisciplinary work, our students need to be able to explain their disciplines. We need to help our students understand our disciplines so well that they can articulate the tools, methodologies, and ways of engaging with the world utilized by the discipline, much like Gadsby does with comedy.
We have just created a new Game Design major at PSU and so I’ve been thinking about this question for this new (to us) discipline. I don’t have a full answer yet but here are some initial thoughts. Game design takes some of its tools and methodologies from computer science and some from art (as well as other disciplines but I’ll stick with these two to start). I haven’t even completely thought through these questions with respect to computer science and art.
One of the major tools that computer scientists use that is important to game designers is abstraction. This is the idea that we want to hide (or sometimes remove) details that we deem unnecessary so that we can focus and build on whatever system we currently have. For example, as I type this blog post, I don’t need to understand how the blog software works. Those details are hidden from me. If I am the author of the blog software, I don’t need to understand how the operating system (Windows for the machine I’m working on) works. Those details are hidden from me. If I am the author of the operating system, I don’t need to know how the electronics of the hardware works. Those details are hidden from me. These levels of abstraction are useful because they allow more and more complex logic to be developed.
Computer scientists are system thinkers. We think about the world in terms of systems, made up of parts that interact with each other to create the working system. We are good at breaking those systems down into their parts to understand how they work individually and then putting them back together to understand how they interact to create the working system. When the system doesn’t work as we want it to, we pull it apart to try to figure out where the problem is. (Sometimes we are so well-trained to do this that we try to apply the method to our interpersonal relationships and the problems we find there. I can tell you from experience that it doesn’t work very well but that’s a story for another time.)
When we put these two ideas together, abstraction and systems thinking, we are able to build models of the world. For example, in game design, we might build an in-game world that models the weather patterns of the real world. This model won’t match the real world exactly because including all of the details (even if we knew them all) would be too computational-intensive to work fast enough on our computers to give a good game experience. So we leave some details out. Which we leave out depends on what we think is most important in weather systems. No model is perfect. As an aside, I see this as similar to using metaphor. The objects we’re comparing in a metaphor have some things in common and other things that are different. But we hope that the commonalities help illuminate what we’re talking about. I think of software systems as implementations of metaphors for the real world. We run into trouble when we come to think of the software systems as completely accurate representations of the real world. But I digress.
So I will want game design students to understand that their games are models of the real world, that they are making statements about the details of the world they think are important and which are not important. So we will talk about abstraction and systems thinking.
Creative processes are also important tools for game design. Students need to understand how to generate ideas, work on implementing those ideas, get feedback on the ideas, and generate ideas about how to revise their work in response to the feedback. (This is called the iterative game design process.) We will talk about where ideas come from and how to capture them. We will talk about divergent and convergent thinking, brainstorming, critiquing, prototyping, and play-testing. We will talk about how these processes are non-linear and that many of the stages may need to be revisited over and over.
I have not yet completely articulated for myself the tools, methodologies, epistemologies, and ways of engaging with the world that comprise the game design discipline. My research suggests that maybe nobody else has done this yet either. But Hannah Gadsby gives me hope that it can be done and that the effort is worthwhile.
I am currently Professor of Digital Media at Plymouth State University in Plymouth, NH. I am also the current Coordinator of General Education at the University. I am interested in game studies, digital literacies, open pedagogies, and generally how technology impacts our culture.