Selfevolution

Selfevolution is a concept referring to processes by which a system accelerates or directs its own evolution through feedback, learning, and modification. It is used across disciplines to describe how individuals, organizations, or machines adapt in response to changing conditions, sometimes taking deliberate action to redesign themselves rather than rely solely on external pressures.

In technology and artificial intelligence, self-evolution denotes self-improving systems that can alter their own structure, parameters, or code to improve performance. This includes meta-learning, automated experimentation, and evolutionary computation, where variants are generated and selected based on performance. In practice, such systems may employ modular architectures, curiosity-driven exploration, and self-editing capabilities within safety constraints.

In biology and culture, evolution is normally understood as changes in heritable traits over generations. Self-evolution in this domain is more often discussed in terms of organisms altering gene expression through learning and epigenetic mechanisms, or cultures and institutions evolving through ideas, practices, and technologies. Some theorists view humanity’s cumulative culture and technology as a form of collective self-evolution, where societies shape their own evolutionary trajectory.

Benefits include faster adaptation, optimization of complex systems, and the emergence of novel capabilities. Risks involve loss of control, unintended consequences, and ethical concerns over autonomy, safety, and governance.

See also: evolutionary computation, self-improvement, evolvable hardware, transhumanism.