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- Convenors:
-
Jakob Krause-Jensen
(Aarhus University)
Helle Bundgaard (University of Copenhagen)
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- Format:
- Roundtable
- Location:
- G5
- Sessions:
- Friday 28 June, -
Time zone: Europe/London
Short Abstract:
Generative AI impacts the teaching and practice of ethnographic work. Ethnography is rooted in individual experience and the introduction of AI raises questions about voice, credibility, and craft. Participants are invited to share their experiences with AI in both ethnographic research and pedagogy
Long Abstract:
In this roundtable, we want to explore what happens when ethnography meets generative AI. What happens to our voice, our credibility, and our craft when we can prompt a chatbot to write up our fieldnotes in the style of Paul Stoller — or feed it a few photographic details and ask it to construct an arrival story a la Geertz?
Generative Artificial Intelligence is likely to change the way we work, including how we practice ethnography and teach our students. Ethnography is embodied and irreducibly tied to personal experience. Ethnographic texts are not persuasive by their ‘factuality’ alone, the craft depends on the author’s ability to engage readers emotionally, aesthetically, and intellectually. As Geertz once put it, the reason we pay attention is “because some ethnographers are more effective than others in conveying in their prose the impression that they have had close-in contact with far-out lives...” (Geertz 1989: 6).
When we teach and mentor our students to write from their own material, we want them to cultivate their own voice and sensibility. And that takes a lot of practice. Ethnography is, arguably, slow in the making. The chatbots are ‘Google on speed’, as one commentator put it. In what ways are these technologies a threat, and in what ways might AI be helpful in our efforts to train students to become ethnographers? We invite people to reflect on their experiences with the use of AI in their own ethnographic work as well as in ethnographic teaching and mentoring practices.
Accepted contribution:
Session 1 Friday 28 June, 2024, -Mark Friis Hau (University of Copenhagen)
Contribution short abstract:
The article explores ChatGPT in anthropological teaching, focusing on 3 key areas: teacher preparation, student homework, and supervision. It advocates a techno-constructivist approach informed by affordance theory and critical pedagogy that emphasizes active and critical engagement with technology.
Contribution long abstract:
The integration of Large Language Models (LLMs) like ChatGPT into anthropological teaching presents a host of possible changes to educational practices and paradigms. This article identifies three primary avenues of LLM application: teacher preparation, student homework, and student supervision, each offering unique opportunities and challenges. Firstly, the ease of teacher preparation using ChatGPT underscores a tension between educational quality and institutional efficiency. Secondly, ChatGPT can act as a democratizing force in student homework, aiding students in contextualizing theoretical concepts with their lived experiences, yet raises concerns about academic integrity such as the potential for misuse in completing assignments. Thirdly, the potential of ChatGPT in personalized supervision positively echoes traditional apprenticeship models but brings forth questions about the extent to which AI can responsibly guide student learning. To navigate this new digital turn in anthropological education, this paper advocates for a techno-constructivist approach, integrating active learning principles with the transformative role of digital technology. This framework, informed by affordance theory and critical pedagogy, emphasizes critical engagement with technology, understanding its potential and limitations while being acutely aware of its role in shaping new social and political contexts for learning and teaching. Through this lens, the article calls for a balanced, ethically-informed integration of AI in academia, aligning technological advancements with the core values of anthropological education and exploring hybrid educational models.