TY - GEN
T1 - Discipline-Driven AI
T2 - 42nd ACM International Conference on Design of Communication, SIGDOC 2024
AU - Hedquist, Amber
AU - Willers, Heidi
AU - Hannah, Mark A.
N1 - Publisher Copyright: © 2024 Owner/Author.
PY - 2024/10/28
Y1 - 2024/10/28
N2 - This project reports on the process used to train an AI model for qualitative coding and lessons learned for AI utilization in discipline-specific qualitative research. Interdisciplinary scholars are assessing the role of AI in qualitative coding processes, analyzing tools such as Cody [1], PaTAT [2] and ChatGPT3 [3]. Early findings suggest that emerging AI technology may contribute to qualitative coding by providing new insights [2] and increasing intercoder reliability [1], among other benefits. Though important, the sustained attention to the outcomes of AI-Assisted coding provides little insight into the processes, successes, and failures during the training process. By focusing on process, researchers can better formulate strategies for AI-Assisted coding. This project highlights researchers' experiences training an AI with a disciplinary-specific knowledge base to support qualitative coding.
AB - This project reports on the process used to train an AI model for qualitative coding and lessons learned for AI utilization in discipline-specific qualitative research. Interdisciplinary scholars are assessing the role of AI in qualitative coding processes, analyzing tools such as Cody [1], PaTAT [2] and ChatGPT3 [3]. Early findings suggest that emerging AI technology may contribute to qualitative coding by providing new insights [2] and increasing intercoder reliability [1], among other benefits. Though important, the sustained attention to the outcomes of AI-Assisted coding provides little insight into the processes, successes, and failures during the training process. By focusing on process, researchers can better formulate strategies for AI-Assisted coding. This project highlights researchers' experiences training an AI with a disciplinary-specific knowledge base to support qualitative coding.
KW - Artificial Intelligence (AI)
KW - Disciplinarity
KW - Qualitative Coding
KW - Technical and Professional Communication (TPC)
UR - https://www.scopus.com/pages/publications/85212178164
UR - https://www.scopus.com/pages/publications/85212178164#tab=citedBy
U2 - 10.1145/3641237.3691686
DO - 10.1145/3641237.3691686
M3 - Conference contribution
T3 - Proceedings of the 42nd ACM International Conference on Design of Communication, SIGDOC 2024
SP - 266
EP - 268
BT - Proceedings of the 42nd ACM International Conference on Design of Communication, SIGDOC 2024
PB - Association for Computing Machinery, Inc
Y2 - 20 October 2024 through 21 October 2024
ER -