Fine-Tuning Languages: Epistemological Foundations for Ethical AI in Journalism

Dierickx, Laurence; Lindén, Carl-Gustav

doi:10.1109/sds57534.2023.00013

2023 10th IEEE Swiss Conference on Data Science (SDS) 2023

DOI: 10.1109/sds57534.2023.00013

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Fine-Tuning Languages: Epistemological Foundations for Ethical AI in Journalism

Laurence Dierickx,

Carl-Gustav Lindén

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2024

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Cited by 2 publications

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A data-centric approach for ethical and trustworthy AI in journalism

Dierickx,

Opdahl,

Khan

et al. 2024

Ethics Inf Technol

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AI-driven journalism refers to various methods and tools for gathering, verifying, producing, and distributing news information. Their potential is to extend human capabilities and create new forms of augmented journalism. Although scholars agreed on the necessity to embed journalistic values in these systems to make AI systems accountable, less attention was paid to data quality, while the results’ accuracy and efficiency depend on high-quality data in any machine learning task. Assessing data quality in the context of AI-driven journalism requires a broader and interdisciplinary approach, relying on the challenges of data quality in machine learning and the ethical challenges of using machine learning in journalism. To better identify these, we propose a data quality assessment framework to support the collection and pre-processing stages in machine learning. It relies on three of the core principles of ethical journalism—accuracy, fairness, and transparency—and participates in the shift from model-centric to data-centric AI, by focusing on data quality to reduce reliance on large datasets with errors, making data labelling consistent, and better integrating journalistic knowledge.

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A data-centric approach for ethical and trustworthy AI in journalism

Dierickx,

Opdahl,

Khan

et al. 2024

Ethics Inf Technol

View full text Add to dashboard Cite

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The Role of Artificial Intelligence in Contemporary Journalism Practice in Two African Countries

Adjin-Tettey,

Muringa,

Danso

et al. 2024

Journalism and Media

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Contemporary discussions about the application of artificial intelligence in newsrooms are commonplace because of the unique opportunities it presents for news media. This study investigated the intricate relationship between journalism and AI with the broad research question: How are journalists adopting AI technologies and what challenges and opportunities do such technologies present to them? Eighteen journalists practising in Ghana and South Africa were interviewed through qualitative research techniques. Transcribed interview data were analysed thematically using the data analysis method proposed by Charmaz. The findings were that most newsrooms in the two countries have not formally incorporated AI tools into newsroom practices. However, journalists use AI tools at their discretion in a non-complex manner, such as transcription, research, generating story ideas, and fact-checking. Practical limitations to the formal integration of AI technology into newsroom operations include cost, language barrier, and aversion to change. Although participants recognised the advantages of employing AI for newsroom tasks, they were also concerned about the ethical quandaries of misinformation, improper attribution, and intellectual property. Participants also thought that fact-checking and mindfulness regarding ethical usage might increase ethical AI usage in newsrooms. This study adds an important perspective on AI’s role in African journalism, addressing the obstacles and ethics concerns.

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Fine-Tuning Languages: Epistemological Foundations for Ethical AI in Journalism

Cited by 2 publications

References 100 publications

A data-centric approach for ethical and trustworthy AI in journalism

A data-centric approach for ethical and trustworthy AI in journalism

The Role of Artificial Intelligence in Contemporary Journalism Practice in Two African Countries

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