In this Humlab Share, Virginia Grande and Daniella Gati will present two discussions addressing AI through queer lenses. This event serves as a pre-event to the “Queer futures of AI? Possibilities, constraints, and risks”-event happening on 1st February at Humlab, Umeå University.
Understanding professionalism in AI education: who is (not) perceived as professional Virginia Grande, Uppsala University
Students in computing are expected to develop a series of professional competencies, which are defined as a trifecta of knowledge, skills and dispositions for a specific task in a specific context. Professionalism is part of these competencies. However, the definition of professionalism is loose, and some interpretations of it lead to the exclusion of marginalized communities. Thus, there's a growing imperative to extend the notion of professionalism in computing, particularly within the rapidly developing domain of Artificial Intelligence (AI). In our upcoming project, we survey students and educators in AI-related courses to throw light on how they understand professionalism in AI. This includes the potential tensions they identify between this disposition and their own or others’ social identities.
Thus, this HumLab Share aims to spark a discussion on the intersection of professionalism and social identities. Who gets to be considered as displaying professional behaviors or attitudes, and who does not? How can we expand the understanding of professionalism that computing students develop during their degrees? In particular, what are avenues we can explore to understand how queerness is part of these needed conversations? In this work-in-progress talk, we intend to discuss these and other questions related to the computing community's understanding of professionalism, social identities, and related behaviors. ''
Where Judith Butler Meets Exploding Equation Systems: Queer Possibilities from Mathematics to Computing Daniella Gati, University of Salford
This presentation takes a broad view of computing in general and asks about the theoretical entanglements between computing and queerness. I argue that computing as understood today is embroiled in a fundamentally anti-queer epistemological stance owing to its reliance on discrete categories. While queer theory has demonstrated the instability and constructedness of categories, exposing the fallacies of the ideas of gender and sex, computing relies on objects, variables, and operations with explicitly defined values and fixed boundaries. The key term for this is the mathematical concept of discreteness, which applies to objects whose boundaries are clearly demarcated and permit no permeation. Computing demands discrete objects; this means that any product of coding reasserts the notion that there exist distinct, definite, and defined categories among which there is no transgression. Therefore, it is very difficult to imagine queer alternatives to computing in its current form. Yet, I emphasize that this present form of computing, which we can call its categorical form, is historically contingent: it is not the inevitable product of some natural givens, but rather the product of specific historical forces, among whom most notable is the post-World War II capitalism of the United States. But there is no inevitable given of nature, neither in physics nor in mathematics, that would deterministically yield our particular form of computing. Indeed, in the final part of the talk I draw from mathematician and philosopher Arkady Plotnitsky’s notion of “non-Euclidian mathematics” to argue that the mathematical laws that underlie computing can very well be regarded as offering queer possibilities. Ultimately, then, while we don’t yet know what a queer form of computing would look like, and though it is difficult at present to imagine, still, its possibility exists, and categorical computing is not as inevitable as capitalist narratives would have us believe.
