Legal Document

AI Content Disclosure Policy

How artificial intelligence is used across the BytePulse platform — systems deployed, disclosure, and limitations.

Effective May 15, 2026Last updated 12 May 2026

AI Content Disclosure Policy

Effective Date: May 15, 2026 · Last Updated: May 15, 2026

BytePulse is an AI-native platform. Transparency about how AI is used is central to our commitment to media literacy.

1. AI Systems Deployed

FunctionAI TechnologyHuman Oversight
Surface summariesLLM with source groundingEditorial QA on Breaking/High-priority
Context explainersLLM with structured promptingEditorial QA on all outputs
Deep Dive chatLLM with RAG (Retrieval-Augmented Generation)Automated guardrails + confidence fallback
Beyond Bias — PerspectivesLLM comparative framing analysisAutomated quality scoring
Beyond Bias — StakeholdersLLM impact extractionAutomated quality scoring
Beyond Bias — Blind SpotsCoverage frequency analysis engineAutomated; editorial thresholds
Beyond Bias — NarrativeTemporal framing shift detectionAutomated + editorial review triggers
Quiz generationLLM with answer verificationRandom sampling QA
Content categorizationML classificationCMS override capability
Feed personalizationML recommendationDiversity safeguards (no echo chambers)
Poll question generationLLM with tone/complexity rulesEditorial review for sensitive topics
Content moderationML classifier + LLM filterHuman review for flagged content

2. Disclosure and Labeling

All AI-generated content is clearly labeled:

  • AI-generated summaries show an "AI" badge on story cards
  • Beyond Bias lens outputs labeled "AI-powered analysis"
  • Deep Dive chat identifies responses as AI-generated
  • AI-generated quiz/poll questions display the "AI" tag

We do not present AI content as human-written journalism — the distinction is maintained at all times.

3. Limitations and Known Risks

  • Accuracy — AI may produce inaccurate or incomplete content despite controls
  • Hallucination — LLMs may generate plausible-sounding statements that are factually incorrect (RAG mitigates but does not eliminate)
  • Bias — AI models may reflect biases in training data; we actively test and mitigate
  • Timeliness — analyses reflect data at generation time and may not capture subsequent developments
  • Interpretation — Beyond Bias outputs are computational interpretations, not definitive editorial judgments

4. Source Grounding and Anti-Hallucination

  • Deep Dive responses are generated via RAG from verified source-article chunks in our vector database
  • Below confidence thresholds, AI falls back to: "I'm not confident enough to answer accurately — here's the original article."
  • AI is explicitly prohibited from generating information not present in source material
  • All outputs include citation references

5. Age-Appropriate Safeguards

For users under 16: simplified language complexity, enhanced sensitivity filters, and restricted access to AI chat topics related to violence, substance use, or self-harm.

6. Right to Human Review

Any user may request human review of an AI output via the in-app flag icon or by emailing admin@bytepulse.club. Corrections are prioritized and processed within 24 hours.

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