Collecting Real Stories of AI Integration
Project Overview
AI Culture Lab is conducting the first comprehensive, cross-cultural study of how people around the world are actually experiencing AI in their daily lives. Unlike studies focused on capabilities or market adoption, we’re documenting the human stories—the unexpected moments, cultural adaptations, and emotional responses that reveal how AI is truly reshaping society.
Why This Matters
- Cultural Blind Spots: Most AI research comes from Western, tech-centric perspectives
- Human Experience Gap: We study AI capabilities but not human adaptation
- Policy Implications: Real experiences should inform AI governance
- Academic Need: Ethnographic data for cultural anthropology research
What We’re Collecting
Story Categories:
- Workplace AI: How AI is changing professional relationships and workflows
- AI Companions: Emotional relationships with chatbots, assistants, and AI tools
- Creative Collaboration: Artists, writers, and creators working with AI
- Family & Education: AI in homes, schools, and child-raising
- Cultural Adaptation: How different cultures interpret and use AI
- Unexpected Moments: Surprising, funny, or profound AI interactions
Research Methodology
- Ethnographic Approach: Detailed personal narratives
- Cross-Cultural Analysis: Stories from diverse global communities
- Longitudinal Study: Tracking changes over time (2024-2026)
- Mixed Methods: Qualitative stories + quantitative pattern analysis
- Open Science: All findings published openly
Participation
Stories are collected through our secure submission system with full anonymity options. All participants provide informed consent, and sensitive stories are handled with academic ethical standards.
Academic Partnerships
We’re actively seeking university collaborations for this research. Contact us to discuss partnership opportunities.
Expected Outcomes
- Peer-reviewed publications in anthropology and HCI journals
- Annual research reports with anonymized findings
- Policy recommendations based on real user experiences
- Public resource library of AI cultural adaptation patterns
This research is conducted under academic ethical guidelines with IRB-equivalent review processes.