Why Life Exists

Functional information measures how rare functional configurations are. Wong and colleagues argue that selection should drive a law of increasing functional information. This is often read as a claim that complexity must increase. We give a cleaner interpretation, which is that survivors tend to be the systems that did not overcommit. We model a system as a policy π, meaning a bundle of commitments expressed in a finite embodied vocabulary. New selection pressures arrive as a set of future requirements drawn from the unobserved outcome set U. A currently viable policy leaves an unobserved buffer Bπ ⊆ U of outcomes it still permits. Under a maximally ignorant novelty model, the survival probability of π is exactly 2|Bπ|−|U|. Under any exchangeable novelty prior, survival remains monotone in |Bπ|. So persistence favours weaker constraints on function, where weakness counts the compatible completions left open. We define degree of function as survival probability and functional information as Hazen and Szostak rarity among currently viable policies. Conditioning on persistence reweights the population toward larger buffers, hence higher functional information. This yields a formal version of Wong’s law under explicit assumptions. In fully enumerated toy worlds, weakness maximisation improves mean log survival probability by 1.674 bits relative to random choice. Weakness and simplicity are not the same thing. Weakness helps a system persist under novelty, because it keeps more futures compatible. Simplicity can help a system persist because there is less to break. That obviates the need for repair. Complexity requires self-repair to persist, increasing weakness. Life is persistent complexity. In between complex life and simple nonlife is the void of the unviable; complexity which is not alive.