透视图(图形)
新闻
计算机科学
领域(数学)
标杆管理
自动化
叙述的
帧(网络)
知识管理
制度逻辑
社会学
人工智能
业务
工程类
语言学
营销
媒体研究
数学
社会科学
机械工程
电信
哲学
纯数学
作者
Stefanie Sirén‐Heikel,Martin Kjellman,Carl‐Gustav Lindén
摘要
Abstract As artificial intelligence (AI) technologies become more ubiquitous for streamlining and optimizing work, they are entering fields representing organizational logics at odds with the efficiency logic of automation. One such field is journalism, an industry defined by a logic enacted through professional norms, practices, and values. This paper examines the experience of technologists developing and employing natural language generation (NLG) in news organizations, looking at how they situate themselves and their technology in relation to newswork. Drawing on institutional logics, a theoretical framework from organizational theory, we show how technologists shape their logic for building these emerging technologies based on a theory of rationalizing news organizations, a frame of optimizing newswork, and a narrative of news organizations misinterpreting the technology. Our interviews reveal technologists mitigating tensions with journalistic logic and newswork by labeling stories generated by their systems as nonjournalistic content, seeing their technology as a solution for improving journalism, enabling newswork to move away from routine tasks. We also find that as technologists interact with news organizations, they assimilate elements from journalistic logic beneficial for benchmarking their technology for more lucrative industries.
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