新闻
民主
社会学
热情
公民新闻
相关性(法律)
对话
技术新闻
协商民主
认识论
公共关系
计算机科学
政治学
媒体研究
政治
法学
心理学
社会心理学
哲学
沟通
作者
Bibo Lin,Seth C. Lewis
标识
DOI:10.1080/21670811.2022.2084131
摘要
A recent wave of enthusiasm surrounding artificial intelligence (AI) has seen many observers focus on its potential to transform journalism, as with other forms of knowledge work. This conceptual essay, however, attempts to steer the conversation away from a technocentric emphasis on applications and instead pivot to the fundamental but overlooked issue of normativity: in this case, what should AI actually do to help fulfill journalism’s broader democratic aims? Building our analysis on Rasmus Kleis Nielsen’s approach that emphasizes one essential thing that journalism just might do for democracy—namely, provide accurate, accessible, diverse, relevant, and timely news about public affairs—we argue that journalistic AI could be normatively imagined and evaluated with a similar focus on simplicity and dose of democratic realism. In connection with three primary stages of newswork—information gathering, selection and production, and distribution and consumption—we explain how journalistic AI not only can work but also should work in the service of accuracy, accessibility, diversity, relevance, and timeliness. Ultimately, by placing normativity at the center of this analysis, our goal is to explore how AI might be oriented to enhance how news performs in each of these domains and thus make a pragmatic difference for journalism and democracy.
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