This talk was presented at the AI The Docs 2025 online conference. We are thrilled to share the recording and the summary with you.
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Summary
What is the foundational element that shapes discoverability in digital systems, and why is it so crucial?
In her presentation, Tammy Lee (CEO and co-founder of Culture Creates) argues that in an AI-first world, discoverability is built or broken by metadata infrastructure. What machines surface, summarize, or erase is not neutral: it reflects who gets to shape public knowledge.
Discoverability depends on three elements:
- Signal strength: how much something stands out.
- Pathway clarity: how easy it is to reach it.
- Context: whether it appears at the right time.
Without strong metadata, discoverability collapses: signals fail, content becomes invisible, bias is reinforced, and entire perspectives can disappear. AI systems amplify this problem since they mostly learn from web content already shaped by commercial platforms, narrowing what is visible. Tammy Lee’s central claim: Content is not king. Metadata decides what is surfaced, seen, or lost.
Culture Creates’ approach: People-shaped open knowledge graphs
- Arts organizations in Canada use Footlight CMS to publish structured data about events, venues, and artists.
- This data flows into Arts Data, an open knowledge graph, creating a living feedback loop where people (not just machines) shape visibility.
- The infrastructure is designed for non-technical users, shifting agency back to communities.
Key insight: Discoverability is not technical but political: it reflects who controls metadata. In an AI-first world, we face a choice:
- Do we rely on commercial platform logic to define what is seen?
- Or do we invest in public metadata infrastructure, where communities shape their own visibility?
Takeaway: To ensure diversity and agency in public knowledge, we must build metadata infrastructures shaped by people, not platforms.
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