61 lines
4.4 KiB
Markdown
61 lines
4.4 KiB
Markdown
---
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type: source
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title: "Democracy and AI: CIP's Year in Review 2025"
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author: "CIP (Collective Intelligence Project)"
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url: https://blog.cip.org/p/from-global-dialogues-to-democratic
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date: 2025-12-01
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domain: ai-alignment
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secondary_domains: [collective-intelligence, mechanisms]
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format: article
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status: unprocessed
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priority: medium
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tags: [cip, democratic-alignment, global-dialogues, weval, samiksha, digital-twin, frontier-lab-adoption]
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---
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## Content
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CIP's comprehensive 2025 results and 2026 plans.
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**Global Dialogues scale**: 10,000+ participants across 70+ countries in 6 deliberative dialogues.
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**Key findings**:
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- 28% agreed AI should override established rules if calculating better outcomes
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- 58% believed AI could make superior decisions versus local elected representatives
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- 13.7% reported concerning/reality-distorting AI interactions affecting someone they know
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- 47% felt chatbot interactions increased their belief certainty
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**Weval evaluation framework**:
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- Political neutrality: 1,000 participants generated 400 prompts and 107 evaluation criteria, achieving 70%+ consensus across political groups
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- Sri Lanka elections: Models provided generic, irrelevant responses despite local context
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- Mental health: Developed evaluations addressing suicidality, child safety, psychotic symptoms
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- India health: Assessed accuracy and safety in three Indian languages with medical review
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**Samiksha (India)**: 25,000+ queries across 11 Indian languages with 100,000+ manual evaluations — "the most comprehensive evaluation of AI in Indian contexts." Domains: healthcare, agriculture, education, legal.
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**Digital Twin Evaluation Framework**: Tests how reliably models represent nuanced views of diverse demographic groups, built on Global Dialogues data.
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**Frontier lab adoption**: Partners include Meta, Cohere, Anthropic, UK/US AI Safety Institutes. Governments in India, Taiwan, Sri Lanka incorporated findings.
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**2026 plans**: Global Dialogues as standing global infrastructure. Epistemic Evaluation Suite measuring truthfulness, groundedness, impartiality. Operationalize digital twin evaluations as governance requirements for agentic systems.
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## Agent Notes
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**Why this matters:** CIP is the most advanced real-world implementation of democratic alignment infrastructure. The scale (10,000+ participants, 70+ countries) is unprecedented. Lab adoption (Meta, Anthropic, Cohere) moves this from experiment to infrastructure. The 2026 plans — making democratic input "standing global infrastructure" — would fulfill our claim about the need for collective intelligence infrastructure for alignment.
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**What surprised me:** The 58% who believe AI could decide better than elected representatives. This is deeply ambiguous — is it trust in AI + democratic process, or willingness to cede authority to AI? If the latter, it undermines the human-in-the-loop thesis at scale. Also, the Sri Lanka finding (models giving generic responses to local context) reveals a specific failure mode: global models fail local alignment.
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**What I expected but didn't find:** No evidence that Weval/Samiksha results actually CHANGED what labs deployed. Adoption as evaluation tool ≠ adoption as deployment gate. The gap between "we used these insights" and "these changed our product" remains unclear.
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**KB connections:**
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- [[democratic alignment assemblies produce constitutions as effective as expert-designed ones]] — extended to 10,000+ scale
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- [[community-centred norm elicitation surfaces alignment targets materially different from developer-specified rules]] — confirmed at scale
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- [[no research group is building alignment through collective intelligence infrastructure]] — CIP is partially filling this gap
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**Extraction hints:** Claims about (1) democratic alignment scaling to 10,000+ globally, (2) 70%+ cross-partisan consensus achievable on AI evaluation criteria, (3) frontier lab adoption of democratic evaluation tools.
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**Context:** CIP is funded by major tech philanthropy. CIP/Anthropic CCAI collaboration set the precedent.
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## Curator Notes (structured handoff for extractor)
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PRIMARY CONNECTION: [[democratic alignment assemblies produce constitutions as effective as expert-designed ones while better representing diverse populations]]
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WHY ARCHIVED: Scale-up evidence for democratic alignment + frontier lab adoption evidence
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EXTRACTION HINT: The 70%+ cross-partisan consensus and the evaluation-to-deployment gap are both extractable
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