Human-generated data
Why AI needs human-generated data.
Quick answer
Human-generated data is content created directly by people: writing, conversations, decisions, annotations, code and judgments. AI developers need it because it carries human reasoning, expertise and preferences that models learn to imitate and are evaluated against. Researchers have also reported that training models repeatedly on model-generated output can degrade quality, which keeps human data in demand.
What counts
- Expert writing and documentation
- Conversations between people (support, sales, consultations)
- Decisions with outcomes (approvals, diagnoses, resolutions)
- Code written and reviewed by engineers
- Ratings, rankings and corrections (human feedback)
Where businesses hold it
Most operational systems are full of human-generated data: ticketing tools, CRMs, email, document management, code repositories and QA systems.
What makes it valuable
- Expertise of the people involved
- Link to outcomes
- Consistency and volume
- Clear rights and consents
Related
- What is human-feedback data? (/questions/what-is-human-feedback-data)
- What is RLHF data? (/questions/what-is-rlhf-data)
- Real-world data (/real-world-data)
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