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HUMAN to SYSTEM relationship models

Recurring patterns that emerge when new technologies meet human behaviour. This is a working library, updated as mechanisms are understood and developed.

Decision Compression
People are overwhelmed by abundance. More options do not lead to better decisions.
Constructed Insight
Understanding arrives through guided inquiry. The right questions create the conditions for insight to surface.
Autonomy Gradient
Autonomy is earned. The degree of agency delegated to system could only increase as trust increases.
Preference Accumulation
Preferences are situational. Taste is more stable. Systems should learn how people choose, not just what they choose.
Cognitive Scaffolding
People often need help thinking, not answers. Systems can help with strengthening thought rather than generating output.
Elimination Sequencing
When constraints are objective and self-known, preferences can be declared sequentially.
Escalation Intelligence
Not everything should be delegated. Knowing when a human should re-enter the loop is as important as knowing when they shouldn’t.
Intent Extraction
Users rarely articulate their actual need. They ask for solutions instead of expressing goals.
Judgment Amplification
The most valuable systems amplify expertise rather than replace it. Experts need support, not substitution.
Adaptive Complexity
Beginners and experts require different experiences. Interfaces should reveal sophistication progressively.
Attention Compression
Attention is the scarce resource. Reduce cognitive load without reducing awareness.
Shared Decision Systems
Important decisions require collaboration. The future is collaborative intelligence, not replacement.