Synthetic Interlocutors. Experiments with Generative AI to Prolong Ethnographic Encounters

Fuente: arXiv
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Auteurs principaux: Søltoft, Johan Irving, Kocksch, Laura, Munk, Anders Kristian
Format: Preprint
Publié: 2024
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author Søltoft, Johan Irving
Kocksch, Laura
Munk, Anders Kristian
author_facet Søltoft, Johan Irving
Kocksch, Laura
Munk, Anders Kristian
contents This paper introduces "Synthetic Interlocutors" for ethnographic research. Synthetic Interlocutors are chatbots ingested with ethnographic textual material (interviews and observations) by using Retrieval Augmented Generation (RAG). We integrated an open-source large language model with ethnographic data from three projects to explore two questions: Can RAG digest ethnographic material and act as ethnographic interlocutor? And, if so, can Synthetic Interlocutors prolong encounters with the field and extend our analysis? Through reflections on the process of building our Synthetic Interlocutors and an experimental collaborative workshop, we suggest that RAG can digest ethnographic materials, and it might lead to prolonged, yet uneasy ethnographic encounters that allowed us to partially recreate and re-visit fieldwork interactions while facilitating opportunities for novel analytic insights. Synthetic Interlocutors can produce collaborative, ambiguous and serendipitous moments.
format Preprint
id arxiv_https___arxiv_org_abs_2410_11395
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Synthetic Interlocutors. Experiments with Generative AI to Prolong Ethnographic Encounters
Søltoft, Johan Irving
Kocksch, Laura
Munk, Anders Kristian
Human-Computer Interaction
Artificial Intelligence
This paper introduces "Synthetic Interlocutors" for ethnographic research. Synthetic Interlocutors are chatbots ingested with ethnographic textual material (interviews and observations) by using Retrieval Augmented Generation (RAG). We integrated an open-source large language model with ethnographic data from three projects to explore two questions: Can RAG digest ethnographic material and act as ethnographic interlocutor? And, if so, can Synthetic Interlocutors prolong encounters with the field and extend our analysis? Through reflections on the process of building our Synthetic Interlocutors and an experimental collaborative workshop, we suggest that RAG can digest ethnographic materials, and it might lead to prolonged, yet uneasy ethnographic encounters that allowed us to partially recreate and re-visit fieldwork interactions while facilitating opportunities for novel analytic insights. Synthetic Interlocutors can produce collaborative, ambiguous and serendipitous moments.
title Synthetic Interlocutors. Experiments with Generative AI to Prolong Ethnographic Encounters
topic Human-Computer Interaction
Artificial Intelligence
url https://arxiv.org/abs/2410.11395