To flop out of neutrality or not to


Math and more generally formal scientific terminologies, are to informal (preconceived) interpretations what walls are to tags in Berlin. They stain easily. Colourlessness is an opportunity and a call for colouring. In science, this stakes the quality of what we’re doing, the precision and aptness of science. This is not to say that math and formal terminology are dispensable. They absolutely are not! It is to say that in themselves they are not sufficient to ensure scientific rigour and relevance.

The following animation about a bird and a man interacting in a building, is designed to pre-emp historical interpretations of a particular mathematical object called Boolean Automata Networks. By imposing a colourful  imagery, it thwarts preconceptions before they even start making implicit the assumptions that are sustaining those interpretations, thus allowing us to look at them straight in the eye.



NB: Even though it is about a very mathematical object, the animation is not (!) an illustration nor a simplification of something that can be said more accurately and completely with the maths. All the information that is conveyed by the math per se is supposed to be conveyed by this animation too. Of course, being  subjected to the tag-wall effect myself, the animation certainly and hopefully exposes my own blind spots and biases.

corpped-man_armchair-redIt is safe to say that wherever you come from, this animation puts you in a position where you instantly, effortlessly (because instinctively) understand specific things  that no amount of sound, complete mathematical proofs would suffice to make you pay attention to, were you looking at them from inside certain traditional scientific frameworks.

What this page is missing:

  • a link to or an explicit description of an example of traditional preconception about BANs. In the meantime, this should do: Perspectives-and-networks.pdf

So in short, there are things that math can prove but not make you care about ( / understand / believe ) because there are things you already care about that math can’t prove (yet). And there are things we can do about all of that.

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