Topic hub · Last reviewed
Narrative Intelligence
Narrative Intelligence is the ability to examine how a story forms, spreads, and shapes the way people understand a situation and make decisions.
In plain language
Narrative Intelligence goes beyond positive or negative sentiment. It examines who is speaking, which evidence is used, what keeps being repeated, whose voice is missing, and how meaning changes over time.
Data shows what happened. Narrative helps explain why people attach a particular meaning to it. Both are needed for more responsible communication decisions.
A practical framework
- Define the question and the groups you need to understand.
- Separate statements, evidence, sources, and assumptions.
- Look for patterns, differences, missing voices, and change over time.
- Test the findings against human context before acting.
Learning path
- Questions and Metrics · Data Literacy
- Unit of Analysis · Data Literacy
- Quality and Provenance · Data Literacy
- Tokens and Counts · Data Literacy
- TF-IDF · Data Literacy
- Affected Stakeholders · AI Ethics
- The Bias Lifecycle · AI Ethics
- Incentives and Communication · Leadership
Sources you can check
- Data on the Web Best Practices: W3C. Supports data provenance, metadata, quality, access, and reuse.
- Recommendation on the Ethics of Artificial Intelligence: UNESCO. Supports human rights, fairness, transparency, accountability, and oversight.
- People + AI Guidebook: Google PAIR. Supports human-centred AI product design, mental models, feedback, and control.