AI Policy & Operational Guideline

• Artificial Intelligence Policy & Operational Guidelines
• Reporters At Large (reportersatlarge.com)
• Document Control: Version 1.0 | Editorial & Tech Compliance
• Review Cycle: Quarterly (Next Review: October 2026)

Executive Summary

As digital media shifts toward AI-assisted workflows, maintaining the trust of our global audience remains our single highest priority. Artificial Intelligence presents extraordinary opportunities for efficiency, data analysis, and multi-platform distribution. However, without clear editorial parameters, it poses risks to factual accuracy, source protection, and public trust.

This document establishes the official AI operational framework for Reporters At Large. Grounded in international media standards, this policy outlines how our newsroom harnesses AI to assist—never replace—rigorous human journalism.

1. Purpose, Scope & Core Objectives

Purpose: To establish clear rules for integrating Artificial Intelligence into our newsgathering, reporting, production, and distribution workflows without compromising newsroom ethics, credibility, or legal compliance.

Core Objectives

• Maintain absolute accuracy, editorial independence, and narrative integrity across all platforms.
• Protect confidential sources, proprietary newsroom data, and intellectual property.
• Ensure full transparency with our readers and viewers regarding how content is produced.
• Ensure full compliance with relevant local, regional, and international legal frameworks.

Who Is Covered?

This policy is binding for all full-time, part-time, contract, and freelance staff, including:

• Reporters, Correspondents, and Columnists
• Line Editors, Copy Editors, and Managing Editors
• Producers and Multimedia Specialists
• Photojournalists, Graphic Designers, and Cartoonists
• Researchers, Data Analysts, and Technical Staff
• Interns and Editorial Fellows

2. Permitted vs. Prohibited AI Use Cases

AI tools are designated strictly as assistive assets. They are subject to a clear division between allowed and banned applications:

Editorial AI Framework

PERMITTED USE (Assistive Workflows)
* Grammatical & style checks
* Research & brainstorming
* Format conversions & transcripts
* Multilingual translation
* Audience comment moderation

PROHIBITED USE (Zero-Tolerance)
* Unassisted article drafting
* Automated self-publishing
* Core investigative reporting
* Visual or audio deepfakes
* Synthetic source avatars

Approved Permitted Uses

1. Research & Ideation: Summarising lengthy public documents, whitepapers, and reports; generating preliminary angle ideas.
2. Text Processing & Editing: Copy-editing for grammar, spelling, and style consistency.
3. Format Conversion: Speeding up transcribing audio/video, converting text to video outlines, or generating closed captions.
4. Data Analysis: Parsing large public datasets to identify statistical outliers or hidden trends for human investigation.
5. Language Translation: Translating foreign-language wire copy or background documents (subject to verification by a native speaker or editor).
6. Fact-Checking Assistance: Cross-referencing claim timelines against archived public records.
7. Production Support: Assistance in comment moderation, SEO metadata generation, and local news signal monitoring.

Strictly Prohibited Uses (Zero-Tolerance)

1. Unassisted Article Generation: No news article, feature, opinion piece, analysis, or editorial may be written by an AI and published.
2. Automated Publishing: AI systems must never be connected directly to our Content Management System (CMS) for auto-publishing without human intervention.
3. Investigative Conclusiveness: AI tools must not be used to verify core facts, confirm anonymous sources, or conclude investigative reports.
4. Synthetic Avatars & Impersonation: Generating photorealistic AI avatars, synthetic voices, or simulated likenesses of real interviewees, sources, or journalists is strictly banned.
5. Generative Imagery for Real Events: Creating synthetic photos or video footage of real news events, places, or public figures (e.g., deepfakes) is prohibited.

3. Human Oversight & Editorial Accountability

AI cannot hold legal, ethical, or professional responsibility. Therefore, the principle of Human-in-the-Loop (HITL) governs every stage of our editorial process.

• The Editor’s Responsibility: Every piece of text, data point, translation, or graphic created with AI assistance must undergo verification by a human editor before publication.
• Accountability Chain: By submitting or approving a piece of content, the reporter and editor assume 100% personal and professional responsibility for its accuracy, fairness, and legal compliance.
• Fact Verification: Facts, quotes, and statistics suggested by generative AI tools must be independently verified using primary sources. Generative “hallucinations” (fabricated facts) passed into publication will be treated as journalistic negligence.

4. Audience Transparency & Labelling Standards

Trust relies on radical transparency. When AI noticeably shapes the visual or auditory presentation of our work, we inform our audience clearly.

Disclosure Requirements

• Standard Editing & Research: Routine tasks like copy-editing, transcribing interviews, or translation do not require a public label.
• Significant Assistance: Content that relies heavily on AI processing (such as automated data visualisations, synthetic voiceovers, or AI-translated articles) must include a clear disclosure.

Standard Disclosure Labels

Visual Content: “Graphic/Illustration created with AI assistance and reviewed by Reporters At Large editorial staff.”

Text/Data Content: “This report utilised AI tools to process underlying raw data. All findings and text were verified and edited by our editorial team.”

5. Fairness, Bias Mitigation & Localised Context

Generative AI models often carry systemic Western, linguistic, and cultural biases due to the datasets on which they are trained.

• Localised AI Initiatives: Reporters At Large is committed to training and utilising localised AI tools that reflect regional contexts, nuances, languages, and cultural idioms.
• Bias Audits: Our technology team will run quarterly audit logs on all in-house AI tools to check for representativeness, algorithmic bias, and structural errors.
• Community Input: We invite feedback from civic groups and our audience to identify bias or misrepresentation in AI-supported coverage.

6. Privacy, Source Protection & Data Security

Protecting sensitive information and whistleblowers is non-negotiable. Public AI models regularly use input prompts to train future iterations, creating severe privacy risks.

CRITICAL DATA PROTOCOL:
Staff are strictly prohibited from entering sensitive, off-the-record, confidential, or personally identifiable information (PII) into commercial, public LLMs (such as ChatGPT, Claude, or Gemini).

Safeguards

• Restricted Datasets: Only public documents or published press releases may be fed into commercial cloud-based AI tools.
• Secured In-House Instances: Investigative data analysis requiring AI processing must use locally hosted, enterprise-grade, encrypted AI environments that do not store or transmit data to external servers.
• Legal Alignment: All AI implementations must adhere to global data protection standards, including the EU General Data Protection Regulation (GDPR) and local privacy legislation.

7. Capacity Building, Training & Institutional Support

To ensure seamless implementation, Reporters At Large provides continuous education and technical infrastructure for all staff members.

• Mandatory Onboarding Training: A mandatory training track on ethical AI implementation, prompt engineering, bias detection, and verification techniques for all newsroom personnel.
• Ongoing Skill Building: On-demand micro-courses to keep staff updated on emerging generative tools, automated OSINT techniques, and deepfake verification methodologies.
• Tool Adaptation: When new software is introduced, staff will receive proper training before those systems enter active newsroom workflows.

8. Policy Governance & Maintenance

• Quarterly Review: This policy is a living document. It will be formally reviewed every three months by a joint committee composed of editorial leads, media lawyers, and technical specialists.
• Ad-Hoc Updates: Immediate policy revisions will occur in response to sudden technological shifts, legislative changes, or emerging industry standards.
• Expert Partnerships: Reporters At Large actively collaborates with digital media scholars, ethical AI researchers, and academic institutions to stay ahead of industry developments.