They Think AI Can Do More Than It Actually Can: Practices, Challenges, & Opportunities of AI-Supported Reporting In Local Journalism
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866917295953018880 |
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| author | Cifliku, Besjon Heuer, Hendrik |
| author_facet | Cifliku, Besjon Heuer, Hendrik |
| contents | Declining newspaper revenues prompt local newsrooms to adopt automation to maintain efficiency and keep the community informed. However, current research provides a limited understanding of how local journalists work with digital data and which newsroom processes would benefit most from AI-supported (data) reporting. To bridge this gap, we conducted 21 semi-structured interviews with local journalists in Germany. Our study investigates how local journalists use data and AI (RQ1); the challenges they encounter when interacting with data and AI (RQ2); and the self-perceived opportunities of AI-supported reporting systems through the lens of discursive design (RQ3). Our findings reveal that local journalists do not fully leverage AI's potential to support data-related work. Despite local journalists' limited awareness of AI's capabilities, they are willing to use it to process data and discover stories. Finally, we provide recommendations for improving AI-supported reporting in the context of local news, grounded in the journalists' socio-technical perspective and their imagined AI future capabilities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_22887 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | They Think AI Can Do More Than It Actually Can: Practices, Challenges, & Opportunities of AI-Supported Reporting In Local Journalism Cifliku, Besjon Heuer, Hendrik Human-Computer Interaction Computers and Society Declining newspaper revenues prompt local newsrooms to adopt automation to maintain efficiency and keep the community informed. However, current research provides a limited understanding of how local journalists work with digital data and which newsroom processes would benefit most from AI-supported (data) reporting. To bridge this gap, we conducted 21 semi-structured interviews with local journalists in Germany. Our study investigates how local journalists use data and AI (RQ1); the challenges they encounter when interacting with data and AI (RQ2); and the self-perceived opportunities of AI-supported reporting systems through the lens of discursive design (RQ3). Our findings reveal that local journalists do not fully leverage AI's potential to support data-related work. Despite local journalists' limited awareness of AI's capabilities, they are willing to use it to process data and discover stories. Finally, we provide recommendations for improving AI-supported reporting in the context of local news, grounded in the journalists' socio-technical perspective and their imagined AI future capabilities. |
| title | They Think AI Can Do More Than It Actually Can: Practices, Challenges, & Opportunities of AI-Supported Reporting In Local Journalism |
| topic | Human-Computer Interaction Computers and Society |
| url | https://arxiv.org/abs/2602.22887 |