More Human or More AI? Visualizing Human-AI Collaboration Disclosures in Journalistic News Production
arXiv:2601.11072v1 Announce Type: cross Abstract: Within journalistic editorial processes, disclosing AI usage is currently limited to simplistic labels, which misses the nuance of how humans and AI collaborated on a news article. Through co-design sessions (N=10), we elicited 69 disclosure designs and implemented four prototypes that visually disclose human-AI collaboration in journalism. We then ran a within-subjects lab study (N=32) to examine how disclosure visualizations (Textual, Role-based Timeline, Task-based Timeline, Chatbot) and collaboration ratios (Primarily Human vs. Primarily AI
The proliferation of AI in content creation, particularly journalism, necessitates new standards for transparency and disclosure as public understanding and regulatory scrutiny increase.
This research directly addresses the critical issue of trust in information by exploring how to clearly communicate human-AI collaboration, influencing future media ethics and public perception.
The focus is shifting from simple AI tags to nuanced, visual disclosures that explain the degree and nature of human-AI interaction in content production.
- · Ethical media organizations
- · News consumers
- · AI transparency tool developers
- · Disinformation actors
- · Media outlets with opaque AI usage
- · Simplistic disclosure standards
Journalistic standards bodies will integrate more granular AI disclosure guidelines into their codes of conduct.
New user interface conventions will emerge for indicating AI involvement across various forms of digital content beyond journalism.
Public literacy regarding AI's role in content creation will improve, fostering greater discernment and potentially increasing demand for human-verified information.
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Read at arXiv cs.AI