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Last Updated: 2026-10-06

AI Transparency

About This Page

This page explains where AuditSocials uses AI, how AI-generated text is labelled and checked, and who is responsible for it. It is our disclosure under Article 50 of the EU AI Act (Regulation (EU) 2024/1689). AI drafts and checks content on AuditSocials; it does not make decisions about people.

1. Policy Change Summaries

When a platform policy page changes, an AI model drafts the title, summary, severity, action steps and industry notes from the before/after text. The quotes the model relies on are machine-checked against the actual page text, and an editor reviews every change before it is published. These summaries are labelled AI · Summary · Editor-reviewed.

2. Regulator Signals

An AI model summarises public regulator notices and filings. A signal is published automatically only if it passes automated checks: the source is in our highest source tier, the platform involved appears verbatim in the source, and a separate AI check reviews the summary against the source. There is no human review before publication, so these are labelled AI · Summary · Auto-checked against source.

3. Compliance API, MCP & Free Checker

Content you submit is checked by deterministic rule matching first, then by an AI layer that looks for risks keywords cannot catch. Every finding states its origin: source rule or source ai. Findings from the AI layer contain AI-generated explanations and suggestions and are labelled AI · Generated in our free checker.

4. Dashboard Briefs

Logged-in users may see a short personalised brief generated by an AI model from the policy and enforcement data we have already published, filtered to the industries and platforms they selected. Briefs are labelled AI · Generated.

5. Models We Use

  • Primary: OpenAI GPT models via the OpenAI API.
  • Fallback: if OpenAI is unavailable, most AI features switch to an open-weight model (gpt-oss) served through NVIDIA's API.
  • We do not train our own AI models. We use general-purpose models from these providers.

Both providers are listed as sub-processors on our Security & Trust page.

6. How We Label AI-Generated Text

  • On web pages and in the dashboard: AI-generated text is shown with an "AI" label, and the element holding it carries the machine-readable attribute data-ai-generated="true".
  • In the Compliance API and MCP: each finding has source: "rule" | "ai", and responses include aiGenerated and aiDisclosure. Policy-change and regulator-signal tools include the same two fields.
  • In emails and PDF reports: AI-generated text is tagged "AI" (or "[AI]" in PDFs) with a disclosure line, and PDF reports also state it in their document properties.

7. Editorial Responsibility

Editorial responsibility for AI-assisted content published on AuditSocials lies with Reaktör Teknoloji Tic. Ltd. Şti., the company that operates AuditSocials, through the AuditSocials editorial team. Contact: support@auditsocials.com. The editor reviews each policy change against the platform's own policy page before it is published.

8. What We Don't Use AI For

  • No chatbot. You are not talking to an AI anywhere on this site.
  • No scoring, profiling or decisions about individual people.
  • No biometric identification, biometric categorisation or emotion recognition.

9. Limits and Reporting Errors

AI can be wrong. Policy changes and regulator signals link to their source where one is available — check it before you rely on the summary. Nothing on AuditSocials is legal advice, and a clean compliance check does not guarantee a platform will approve your content. Found an error in an AI-generated summary? Email support@auditsocials.com and we will correct it.