From Incident to Insight: Understanding AI Model Lifecycle Management through Case Analysis

Authors

  • Yeqing Kong Georgia Institute of Technology

Keywords:

AI lifecycle, Generative AI, AI incidents, Responsible AI, Technical Communication Pedagogy, Case analysis

Abstract

Understanding the AI lifecycle—the series of tasks and decisions that shape an AI project from conception to deployment—is essential for ensuring responsible AI practices. This article presents a hands-on teaching case designed for technical and professional communication classrooms, where students examine lifecycle failures in actual AI incidents. This approach helps students gain a deeper understanding of AI model lifecycle management in real-world contexts.

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Author Biography

Yeqing Kong, Georgia Institute of Technology

Yeqing Kong is an Assistant Professor of Technical Communication in the School of Literature, Media, and Communication at Georgia Institute of Technology. Her research examines the communication of scientific, technological, health, and environmental risks in the global context. Her scholarly work has appeared in Technical Communication Quarterly, IEEE Transactions on Professional Communication, Journal of Business and Technical Communication, and Proceedings of the ACM International Conference on the Design of Communication.

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Published

2025-10-20

How to Cite

Kong, Y. (2025). From Incident to Insight: Understanding AI Model Lifecycle Management through Case Analysis. Programmatic Perspectives, 17(1). Retrieved from https://programmaticperspectives.cptsc.org/index.php/jpp/article/view/118

Issue

Vol. 17 No. 1 (2026)

Section

Curriculum Showcases

License

Copyright (c) 2025 Yeqing Kong

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.