“A Van Gogh style painting of an Academic meeting” generated by DALLE on March 4.

The DCL Digital Literacy Conversation Series
Version 1: Generative AI with Dr. Hugh Gusterson

When: 4:00 pm – 5:30 pm; Thursday, March 30, 2023
Where: ANSO 134 and Hybrid Zoom link: https://ubc.zoom.us/j/66942560370?pwd=NGlMZ1dTaVRZNW1Cak9Ua0pyeDFKUT09

Remarks by: Dr. Hugh Gusterson, followed by open discussion

“Algorithms are not autonomous technical objects, but complex sociotechnical systems.”
(Seaver 2018, 378)

The Digital Culture Lab invites you to the inaugural event in the Digital Literacy Conversation Series to discuss how generative artificial intelligence (AI) may impact our research, teaching, creative practices, and communities in general.

“Generative AI is a branch of artificial intelligence that involves creating systems that can generate new and original data or content, such as images, music, text, or videos. These systems use machine learning algorithms to learn from a given dataset and generate new output that is similar to the original data.” This definition, for example, is generated by ChatGPT, a generative AI and language model developed by OpenAI, which is designed to generate human-like responses to natural language prompts. Among all generative AI tools, ChatGPT is perhaps the most well-known, but there are many other tools that are used commercially (e.g., text-to-video generators like Synthesia) or recreationally (at least now; e.g., text-to-image tools like DALL-E 2). Like its less generative, but more bureaucratically established algorithmic predecessors (Besteman and Gusterson 2019), generative AI has legal, economic, societal, cultural, and educational consequences (Barassi 2022). Unless we gain and build experience alongside the technology and learn how and why generative AI works in the way it does, we cannot truly work with it (Jørgensen, Gad, and Winthereik 2023).

We will open our first Digital Literacy Conversation with Dr. Gusterson’s remarks about algorithms and what anthropology can contribute to critiques of algorithmic decision making. This will be followed by a discussion of the challenges and opportunities generative AI may create for and in our fields. Topics that we may wish to consider include:

How do we understand algorithms, algorithmic decision making, and machine learning and artificial intelligence? How do we evaluate them in terms of their capacity to democratize means of production vs reproduce existing inequalities?
What are some of our personal experiences with AI, especially generative AI, in our fields?
What are some of actual or potential negative or positive effects generative AI may have on our research (e.g., literature review; finding ‘gaps’ in literature; generative AI co-authorship), teaching (e.g., ban, evade, or adapt? developing best practices for students?), and creative practices (e.g., evaluation of AI-generated art; authenticity and creator rights)?
How can we study generative AI anthropologically?

RSVP

Barassi, Veronica. 2022. “Algorithmic Violence in Everyday Life and the Role of Media Anthropology.” In The Routledge Companion to Media Anthropology. Edited by Elisabetta Costa, Patricia G. Lange, Nell Haynes, and Jolynna Sinanan, 481-491. London: Routledge.

Besteman, Catherine, and Gusterson, Hugh, eds. 2019. Life by Algorithms: How Roboprocesses Are Remaking Our World. Chicago, IL: University of Chicago Press.

Jørgensen, Bastian, Gad Christopher, and Winthereik Brit R. 2023. “Organising Artificial Intelligence and Representing Work.” In An Anthropology of Futures and Teachnologies. Edited by Debora Lanzeni, Karen Waltorp, Sarah Pink, and Rachel C. Smith, 93-104. New York, NY: Routledge.

Seaver, Nick. 2018, “What Should an Anthropology of Algorithm Do?” Cultural Anthropology. 33: 375-385. https://doi.org/10.14506/ca33.3.04

Beneath the Surface of Things: New and Selected Essays (2024)