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HBT-COG-0310 · Dimension COG · Cognition

Feedback Loop

Output of a process re-enters as input.

Systems·Concept·Grade C·draft· enriching…
In one paragraph

Feedback Loop is output of a process re-enters as input. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0310, within the Systems family. The core principle: output of a process re-enters as input. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.

Scientific Definition

Output of a process re-enters as input.

Plain-English Definition

Output of a process re-enters as input.

Feynman Explanation

Every system you ignore is training itself behind your back.

Core Principle

Output of a process re-enters as input.

Mechanisms

Psychological

Pending editorial review.

Behavioral Economic

Pending editorial review.

Neurological

Pending editorial review.

Evolutionary

Pending editorial review.

Sociological

Pending editorial review.

Computational

Pending editorial review.

Systems

Pending editorial review.

Inputs (Triggers)

Pending editorial review.

Outputs (Behaviors)

Pending editorial review.

Behavioral Signature

Every system you ignore is training itself behind your back.

Examples

Everyday
  • Performance reviews shape next-quarter behavior, which shapes next review.
Modern (Organizational)
  • Most strategic surprises are feedback loops the org didn't model.
Historical

Pending editorial review.

Lab Commentary

Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.

Why this element matters to incentive design

When this element shows up in a diagnostic, the instinct is to train people out of it. Training rarely moves it. The mechanism underneath it operates in the Cognition dimension — how do we think?. You can recognize it in the field by its signature: every system you ignore is training itself behind your back. Every element in the Cognition dimension changes the perceived payoff of an action before the action happens, which is exactly where incentive design has leverage.

How it gets exploited

Left undesigned, recommender systems train on the behavior they themselves shape. It is amplified whenever most strategic surprises are feedback loops the org didn't model. Inside organizations that shows up as most strategic surprises are feedback loops the org didn't model. The pattern is the same one Goodhart's Law describes: the measurable proxy attracts the effort, and the purpose behind it quietly loses funding.

How the Lab designs around it

The redesign move is to map loops before tuning metrics. The test of any redesign here is simple: after the change, can you name what the organization is now doing less of? If not, the payoff structure did not actually move.

Famous Experiments

Pending editorial review.

Design Principles

  • Map loops before tuning metrics.

Measurement Approaches

Pending editorial review.

Evidence

Evidence Grade
C (A strongest → E speculative)
Replication
★★☆☆☆
Intervention Confidence
2 / 5
Consensus
Pending editorial review (HBT v1.0 auto-seed).
Limitations
Pending editorial review (HBT v1.0 auto-seed).
Open Research Questions

Pending editorial review.

Primary References

Pending editorial review.

Signature Section

The Perverse Incentive Lens™

How this behavior is exploited — and how to redesign around it.

Exploitation
Recommender systems train on the behavior they themselves shape.
Amplifying Incentives
Most strategic surprises are feedback loops the org didn't model.
Org Failure Modes
Most strategic surprises are feedback loops the org didn't model.
Societal Failure Modes
Pending editorial review (HBT v1.0 auto-seed).
Ethical Considerations
Pending editorial review (HBT v1.0 auto-seed).
Redesign Strategies
Map loops before tuning metrics.
Diagnostic Questions
  • Map loops before tuning metrics.
Warning Signs

Pending editorial review.

Red Flags

Pending editorial review.

Intervention Playbook
Individual
Map loops before tuning metrics.
Team
Pending editorial review (HBT v1.0 auto-seed).
Organization
Pending editorial review (HBT v1.0 auto-seed).
Policy
Pending editorial review (HBT v1.0 auto-seed).
AI Implications
Detection
Recommender systems train on the behavior they themselves shape.
Measurement
Pending editorial review (HBT v1.0 auto-seed).
Mitigation
Pending editorial review (HBT v1.0 auto-seed).
Responsible Use
Pending editorial review (HBT v1.0 auto-seed).

Interactive Mini Network

Click any neighbor to re-center the graph and follow the threads of connection.

HBT-COG-0310 · COG
Feedback Loop
FLBLBalancing LoopRLReinforcing LoopTPTipping PointAcAccountabilityASAdverse SelectionAuAuthorityAwAweBeBelongingCACollective Action Pr…CoCompetence

Knowledge Graph Neighbors

Where Feedback Loop is cited in the corpus

Questions about Feedback Loop

What is Feedback Loop?
Feedback Loop is output of a process re-enters as input. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0310, within the Systems family. The core principle: output of a process re-enters as input. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
What is an example of Feedback Loop?
Most strategic surprises are feedback loops the org didn't model. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-COG-0310).
How is Feedback Loop exploited?
Recommender systems train on the behavior they themselves shape.
How do you design around Feedback Loop?
Map loops before tuning metrics.
Which behavioral dimension does Feedback Loop belong to?
Feedback Loop is classified in the Cognition dimension (COG) of the Human Behavior Taxonomy™, family "Systems", class "Concept". Its permanent identifier is HBT-COG-0310 and its evidence grade is C.

Version History

v1.1.0 · 2026-06-28Initial auto-seed from corpus.