Skip to content

Evolution by Emergence --- Core Ideas on One Page

::: center Evolution by Emergence\ Core Ideas in One Page :::

1 Paradigm in a Nutshell

  • Local interactions inside dynamic networks trigger feedback loops; selection amplifies useful patterns → emergence.

  • Mechanism is universal: applies to genes, neurons, economies, AI agents --- even minerals.

  • Result: growing internal complexity that lowers internal friction (energy • bits • time) and boosts robustness.

2 Ten Principles (mnemonic "UNFIC AKHE")

::: description Universality of emergence

Networks are dynamic, not static

Feedback loops drive change

Interdependence & non‑linear causality

Competition & co‑operation duality

(Constrained) Agency --- "forced free will"

Kuhnian leaps (punctuated shifts)

Holistic perspective beats reductionism

Ethical / planetary implications follow :::

3 SCAP Snapshot

Nine Blocks (A--I) lay out duties for any intelligence; a proposed Block J (*Simplicity‑Through‑Complexity*) commits the system to shrink public cognitive load as internal machinery grows.

4 Measuring Progress

  • ICI: \(\text{stable performance}/\text{human cognitive load}\)

  • ICI~AI~: info gain divided by compute/energy --- an internal compass.

  • ECS: learner's improvement per token of teacher explanation.

5 Competition & Cooperation

Extra layers yield speed/efficiency edges (competition), yet long‑term survival hinges on resource restraint and tit‑for‑tat + forgiveness (co‑operation).

6 Tiny Analogy Table

::: center System Added complexity What becomes easier inside

Neural net Deeper specialised layers Fewer FLOPs per correct prediction Ecosystem Extra trophic links Lower nutrient leakage Supply chain Real‑time data brokers Lower transaction cost LLM agent Memory + reasoning modules Fewer tokens per high‑confidence answer :::

::: center Use, remix, fork --- CC‑BY 4.0. For the full argument see book v0.89 and the ongoing GitHub dialogue. :::