Evolutionary Epistemology

Evolutionary Epistemology approaches the growth of knowledge, especially scientific knowledge, in terms of evolutionary mechanisms. In other words, just as biological organisms evolve, so do the natural sciences and their practice and knowledge.

What this means is that the foundation we have today is bad, as it is the best that we know today, but our knowledge will continue to grow and the foundations from which we build, going forward, will continue to get better.

Information

In 2003 the biologist Jack Szostak published a short article(opens a new tab) in Nature proposing the concept of functional information. Szostak wanted to quantify the amount of information or complexity that biological molecules like proteins or DNA strands embody. Classical information theory, developed by the telecommunications researcher Claude Shannon in the 1940s and later elaborated by the Russian mathematician Andrey Kolmogorov, offers one answer. Per Kolmogorov, the complexity of a string of symbols (such as binary 1s and 0s) depends on how concisely one can specify that sequence uniquely.

In 2025 another principle was presented that entities are selected because they are richer in a kind of information that enables them to perform some kind of function. This controversial hypothesis from Robert Haze, Michael Wong and others, argue that the basic laws of physics are not “complete” in the sense of supplying all we need to comprehend natural phenomena; rather, evolution — biological or otherwise — introduces functions and novelties that could not even in principle be predicted from physics alone.