Protected Groups in AI Governance

🌍 Protected Groups in AI Governance

Research Report: A Text Analysis of Global Policy Documents

By Imogen Hull · Age-Inclusive AI · Beyond the Average

Summary

This report examines how major AI governance frameworks—from the EU AI Act to UNESCO’s Ethics of AI Recommendation—refer to protected groups such as age, gender, disability, race and ethnicity.

Using a transparent text-analysis method built in Python, the study compares the visibility of these categories with more abstract ethical principles like fairness, safety, accountability and transparency.

Key findings

• Protected groups are referenced far less frequently than system-level principles.
• “Fairness” is often framed procedurally (through risk and accountability) rather than socially (through equality and inclusion).
• Gender receives the most consistent attention; age and ethnicity are least visible.
• The balance of focus differs between rights-driven and innovation-driven frameworks.

Why it matters

AI policy is evolving fast, but fairness means little unless it protects real people.

This analysis shows where global frameworks align with equality law—and where they risk leaving age and intersectional bias out of scope.

Ideal for

Researchers, policymakers, ethics leads, and audit professionals working to embed fairness and inclusion into AI governance and risk management.

Details

• Format: PDF
• Length: ~20 pages
• Version 1.0 · Published October 2025
• © Imogen Hull | Age-Inclusive AI | Beyond the Average

📘 Topics covered:

AI Ethics • Responsible AI • Fairness • Inclusion • Policy Analysis • Age-Inclusive Design