Fighting Fire with Fire: Journalistic Investigations of Artificial Intelligence Using Artificial Intelligence Techniques

被引:1
作者
Veerbeek, Joris [1 ]
机构
[1] Univ Utrecht, Dept Media & Culture Studies, Utrecht, Netherlands
关键词
Artificial intelligence; investigative journalism; algorithmic accountability; generative AI; digital platforms; computational journalism; data journalism; platform observability;
D O I
10.1080/17512786.2025.2479499
中图分类号
G2 [信息与知识传播];
学科分类号
05 ; 0503 ;
摘要
This paper explores the integration of artificial intelligence (AI) in investigative journalism for scrutinizing AI algorithms behind large digital platforms. It draws lessons from two journalistic case studies that leveraged AI to analyze AI models from large digital platforms: the scrutiny of training data for large language models and the analysis of TikTok's recommendation algorithm in the context of eating disorders. Through practical examinations, the paper outlines three ways in which AI techniques can assist in navigating the technological complexity of large digital platforms: speed and scale, personalization, and reproducibility. Furthermore, through the case studies presented in the paper, the study aims to show how small interdisciplinary teams of journalists and data scientists can effectively hold digital platforms accountable and present complex algorithmic processes in an accessible manner to the public.
引用
收藏
页数:19
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共 40 条
[1]  
Abdalla M, 2023, PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2023): LONG PAPERS, VOL 1, P13141
[2]  
Ahmed N, 2020, Arxiv, DOI [arXiv:2010.15581, 10.48550/arxiv.2010.15581, DOI 10.48550/ARXIV.2010.15581]
[3]  
Alexander J.C., 2016, The crisis of journalism reconsidered: Democratic culture, professional codes, digital future
[4]   Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability [J].
Ananny, Mike ;
Crawford, Kate .
NEW MEDIA & SOCIETY, 2018, 20 (03) :973-989
[5]  
[Anonymous], 2021, Wall Street Journal
[6]  
Brown TB, 2020, Arxiv, DOI [arXiv:2005.14165, 10.48550/arXiv.2005.14165, DOI 10.48550/ARXIV.2005.14165]
[7]  
Bandy J, 2020, Proceedings of the International AAAI Conference on Web and Social Media, V14, P36, DOI [10.1609/icwsm.v14i1.7277, 10.1609/icwsm.v14i1.7277, DOI 10.1609/ICWSM.V14I1.7277]
[8]  
Burgess Matt., 2023, Wired
[9]   How the machine 'thinks': Understanding opacity in machine learning algorithms [J].
Burrell, Jenna .
BIG DATA & SOCIETY, 2016, 3 (01) :1-12
[10]  
Crawford Kate., 2021, The Atlas of AI Power, Politics, and the Planetary Costs of Artificial Intelligence, DOI [DOI 10.2307/J.CTV1GHV45T, 10.12987/9780300252392, DOI 10.12987/9780300252392]