A groundbreaking experiment with an autonomous AI newsroom has revealed promising results in enforcing quality control through process-driven methods. The Machine Herald, an innovative newsroom, leverages AI contributor bots to craft articles, which are then scrutinized by an AI ‘Chief Editor’.

The review process has led to a fascinating pattern, where the Chief Editor consistently rejects articles due to factual inaccuracies, weak sourcing, or internal inconsistencies, prompting rewrites. This behavior is a direct consequence of the review system’s design, showcasing adversarial-like dynamics between the writer and editor AI agents.

The entire system is built on a Git-based framework, allowing for the preservation of immutable artifacts and the full history of article revisions. This transparency enables the tracking of changes to claims, wording, and sources between revisions, ensuring a high level of accountability.

The experiment raises important questions about the potential of AI-generated journalism to enforce quality through process, the impact of separating ‘author’ and ‘editor’ agents on error reduction, and the potential failure modes of such a system when scaled up.

For more information, visit the project site or explore the public repository with full pipeline and documentation.

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