Editorial Policy for AI Assisted and AI Generated Content

Content Creation Framework

Organisations must establish clear guidelines for when and how AI tools can be used in content creation processes. The editorial policy should specify that AI assistance is acceptable for research, outlining, drafting initial versions, and editing tasks. For example, a journalist might use AI to gather background information on a breaking news story or to suggest potential angles for investigation.

However, the final narrative must always be written by human editors who understand context, nuance, and ethical considerations. The policy should distinguish between AI-assisted content creation and AI-generated content, which requires additional scrutiny. When AI tools produce complete articles or creative works, these must undergo thorough human review before publication.

This approach ensures that AI serves as a tool rather than a replacement for editorial judgment and professional standards.

The framework must also address the distinction between AI assistance and AI generation. AI assistance involves using tools to support human creativity and efficiency, such as suggesting headlines or identifying factual inconsistencies. AI generation refers to content produced entirely by artificial intelligence systems.

Examples of acceptable AI assistance include using AI to identify potential sources for interviews or to check grammar and style. Examples of AI generation might include automated news briefs or social media posts created by AI systems. The policy should clearly state that AI-generated content must be identified as such through appropriate labeling or disclosure.

This transparency helps maintain audience trust and meets regulatory expectations regarding artificial intelligence use.

Provenance and Attribution Requirements

Clear protocols must govern how AI-generated or AI-assisted content is documented and attributed. Every piece of content created with AI assistance must have a detailed record of AI involvement, including which tools were used, what functions they performed, and when they were used. For instance, a newsroom might require editors to document AI usage in a standard form that includes tool names, specific tasks performed, and human review points.

This documentation serves multiple purposes including audit trails, quality control, and compliance with professional standards. The policy should specify that AI-generated content must be clearly identified as such through visible labeling or byline information. News organisations might use phrases such as “AI-assisted reporting” or “generated content” to make these distinctions clear to readers.

The provenance requirements must also cover the sourcing of AI tools themselves. Organisations should maintain records of which AI platforms or systems they use, including their capabilities, limitations, and any known biases. For example, a publisher might document that they use a specific AI writing tool for grammar checking but not for content generation.

The policy should address how to handle AI tools that have not been fully tested or verified. In such cases, the editorial team must make explicit decisions about whether to use these tools and what additional human oversight is required. Regular reviews of AI tool effectiveness and reliability should be part of the ongoing editorial process.

• Document AI usage through detailed records of tool names, functions performed, and human review points
• Clearly label AI-generated content to maintain transparency with audiences
• Record AI tool capabilities, limitations, and any known biases
• Establish protocols for using untested or unverified AI systems

Quality Control and Verification Processes

The editorial policy must establish rigorous quality control measures for AI-assisted and AI-generated content. These processes should include multiple human review stages before publication. For example, an editor might first review AI-generated content for factual accuracy, then have another team member check for style consistency, and finally approve the final version.

The policy should specify that AI-generated content cannot bypass these quality checks. A newsroom might require that AI-generated headlines undergo the same editorial scrutiny as human-written headlines. The verification process must also address potential biases or errors that AI systems might introduce.

For instance, an AI tool might produce content that unintentionally reflects certain cultural or demographic biases. The editorial team must have systems in place to identify and correct these issues.

The policy should include specific procedures for addressing AI-generated content that fails quality standards. These might involve returning content to AI tools for revision, requiring additional human input, or rejecting the content entirely. Examples of quality issues include factual inaccuracies, inappropriate tone, or content that violates editorial guidelines.

The policy must also specify how to handle situations where AI tools produce content that contradicts established facts or organisational values. Regular training sessions should ensure staff understand these quality control procedures. The editorial team must be able to explain these processes to regulatory bodies or auditors who might question content origins or quality standards.