The dominant discourse in journalism often frames its future as shaped by “technological rupture” and innovation imperatives. This paper challenges such narratives, arguing instead for an understanding of journalism’s transformation as a broader structural change. Through the concept of “pioneer journalism,” we analyze how journalists who experiment with new practices and imagine possible futures shape the field’s transformation. Based on a media-ethnographic study in Germany, we examine how pioneer journalists imagine the societal needs for public communication and what implications they derive from this for innovating journalism for a better future. Our findings reveal that their imaginations are strongly rooted in democratic values, emphasizing the need for independent information, foster a basic consensus and civic engagement, among other things. Paradoxically, however, their discourse on innovation often mirrors Silicon Valley’s categories, raising critical questions about whether such frameworks can adequately address the imagined needs for public communication. Finally, we discuss the question of whether the idea of such societal needs should not necessitate an alternative understanding of innovation.

This study explores the legitimacy of AI-generated images in photojournalism and their potential role in documentary practices. While much of the discourse surrounding AI-generated images focuses on their involvement in disinformation and misinformation, less attention has been given to their possible documentary and informational applications. This research investigates how news media professionals assess the use of AI-generated images for documenting events and the ethical and procedural challenges they pose. Through a qualitative study involving 15 semi-structured interviews with photo-editors, photojournalists and documentary photographers in Italy, the study examines their perspectives on AI-generated images in news media contexts. Findings suggest that AI-generated images could be perceived not as a radical disruption but rather as a continuation of pre-existing illustrative trends. While AI-generated images may find a place in journalism, they should not be considered an extension of traditional photography but rather a distinct visual medium requiring its own ethical framework and editorial verification processes.

This study examines how algorithmic mediation influences the visibility of Open Access journals, linking it to broader discussions on data capitalism, techno-colonialism, and platformization. We argue that academic knowledge circulation is shaped by a paradox of mediation: an illusion of direct access to research objects, alongside increasing dependence on Big Tech infrastructures. Despite their centrality, search engines like Google remain largely invisible as mediators of scientific visibility. By analyzing traffic metrics from an Open Access journal in Communication and Information, we explore the role of algorithmic logics in shaping discoverability. Using data from Google Analytics and the journal’s CMS, we investigate six key indicators, including traffic sources, organic search patterns, and PDF downloads. Our findings reveal how search algorithms privilege certain knowledge formations, reinforcing epistemic dependencies that challenge digital sovereignty. We discuss how algorithmic sorting does not directly promote or suppress academic work but instead governs its accessibility through logics of popularity, similarity, and profiling. This dynamic raises ethical concerns, particularly as the metrification of science increasingly aligns with platform-driven visibility metrics. While alternative circulation strategies—such as direct traffic and academic networking platforms—mitigate some challenges, they do not offset the structural dominance of Google/Alphabet in Open Access dissemination. Our research underscores the need for critical engagement with algorithmic infrastructures, advocating for regulatory frameworks and tactical interventions to promote epistemic autonomy in digital knowledge production. These findings contribute to broader debates on platform governance, knowledge equity, and the future of scholarly communication.

Environmental journalism is vital for public awareness of ecological crises, particularly in regions like the Amazon. This study investigated audience engagement with environmental reporting, focusing on trust and impact within a fragmented media landscape. Using media engagement theory and examining the datafication of journalism, it explored data-driven storytelling, personalized content, and community-centered narratives. Partnering with InfoAmazonia, five focus groups with journalists, researchers, activists, and citizens were conducted. Thematic analysis revealed a tension between in-depth reporting and audience preferences for concise content. Participants favored multimodal storytelling, integrating text, visuals, and audio to balance depth and accessibility. Empirical evidence and transparent sourcing were crucial for building trust, with data visualizations like interactive maps and infographics enhancing comprehension and credibility. Concerns about data manipulation highlighted the need for clear methodologies. Social media platforms, including Instagram, Twitter, and WhatsApp, were key news sources, emphasizing media convergence. Human-centered storytelling resonated strongly, with personal stories, community quotes, and a conversational tone preferred. Diverse content formats, including text, images, videos, podcasts, and emojis, were deemed essential for broader appeal, with audio accessibility highlighted. Participants emphasized representation and community engagement, seeking news that amplified local voices, particularly Indigenous leaders. Representation was viewed as ethical and crucial for building trust. Our findings suggest that balancing technological innovation with human-centered journalism is critical. Prioritizing accessibility, transparency, and community focus can foster deeper engagement, trust, and impact in environmental journalism, especially in information-critical regions like the Amazon.