Rethinking AI data: From scraping to sustainable and ethical data sharing
OECD-level thinking on ethical data sourcing for AI training could inform Australian data governance and AI procurement frameworks.
Key points
- OECD's VIADUCT project explores ethical AI training data sharing as an alternative to web scraping.
- Addresses legal and ethical tensions including copyright, GDPR compliance, and fairness in data sourcing.
- Extracted text is a stub only - substantive findings are not available from this item.
Summary
An OECD AI blog post introduces the VIADUCT project, which examines ethical and sustainable AI training data sharing as an alternative to broad web scraping. The project addresses challenges including data scarcity despite apparent abundance, copyright issues, GDPR compliance, trust, and fairness in AI data ecosystems. The extracted content is a brief teaser only; the full post would need to be read directly for substantive analysis.
Implications for Australian agencies
- Monitor Agencies involved in AI procurement or data governance may want to monitor VIADUCT outputs as international consensus on ethical training data practices develops.
Implications are AI-generated. Starting points, not advice.
"Rethinking AI data: From scraping to sustainable and ethical data sharing" Source: OECD AI Wonk Blog Published: 31 March 2026 URL: https://wp.oecd.ai/rethinking-ai-data-from-scraping-to-sustainable-and-ethical-data-sharing/ An OECD AI blog post introduces the VIADUCT project, which examines ethical and sustainable AI training data sharing as an alternative to broad web scraping. The project addresses challenges including data scarcity despite apparent abundance, copyright issues, GDPR compliance, trust, and fairness in AI data ecosystems. The extracted content is a brief teaser only; the full post would need to be read directly for substantive analysis. Implications for Australian agencies: - [Monitor] Agencies involved in AI procurement or data governance may want to monitor VIADUCT outputs as international consensus on ethical training data practices develops. Retrieved from SIMS, 18 May 2026.