Towards responsible AI journalism
Mapping journalists’ perceptions of AI ethics
Bibliographic Data
| ID | 21719082 |
|---|---|
| Authors | Doh Shin (0000-0002-5439-4493, Texas Tech University, corresponding author), Shuhua Zhou (0000-0003-2917-658X, City University of Hong Kong, corresponding author), Azmat Rasul (0000-0001-7843-3058, Zayed University) |
| Year | 2025 |
| Publication date | 2025-07-29 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journalism (JOURNAL) |
| Journal identifiers | ISSN: 1464-8849 • E-ISSN: 1741-3001 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/14648849251363045 |
| OpenAlex | W4412885672 |
| Language | EN |
| Citations received | 3 |
| References cited | 14 |
The rapid advancement of artificial intelligence (AI) introduces pressing social and ethical dilemmas, reshaping both the integration of AI into journalistic routines and the broader dynamics of news production and dissemination. This study investigates how journalists perceive and navigate the ethical dimensions of AI, with particular attention to how ethical principles are understood and operationalized in practice. Drawing on a dual sensemaking approach, we propose a conceptual framework for AI journalism ethics that traces how ethical values are constructed, interpreted, and enacted in newsroom contexts. Journalistic heuristics initially shape the normative interpretation of AI, while assessments of technical efficacy and practical utility subsequently inform how AI’s role is recontextualized within journalistic work. Building on these insights, we introduce a model of responsible AI journalism that seeks to integrate core journalistic values with ethical standards in AI development and application
Epistemology · Journalism · Media studies · Perception · Political science · Sociology · Ethics and Social Impacts of AI · Misinformation and Its Impacts · Philosophy · Psychology · Psychology of Moral and Emotional Judgment
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| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |