Feedback Loop

A feedback loop is a structural pattern in which a system’s own outputs are routed back to become inputs that shape its future activity. The loop can be *negative*—damping deviations and promoting stability—or *positive*—amplifying changes and driving rapid shifts. By recirculating information about what has already happened, the system gains a form of self‑reference that lets it adjust without external direction.

The importance of feedback loops lies in their ability to endow systems with control, resilience, or runaway dynamics depending on how they are wired. In engineering, closed‑loop controllers keep temperatures steady or motors at precise speeds. In biology, hormonal and neural circuits use negative feedback to maintain homeostasis while positive feedback drives processes like blood clotting. Economic markets, ecosystems, and digital platforms likewise exhibit loops that can smooth fluctuations or trigger bubbles.

Because every domain where a process can observe its own results can instantiate this pattern, feedback loops appear in everything from thermostats and cruise control to predator‑prey interactions, corporate performance reviews, and recommendation algorithms. Recognizing the type of loop at work helps diagnose why a system behaves as it does and informs how to intervene—by weakening an undesirable positive loop or strengthening a stabilizing negative one.