And to @birchlse.bsky.social @evaroseread.bsky.social @simonabbrown.bsky.social @dzakharova.bsky.social @merikatariina.bsky.social for the 2024 Animal Minds ECR workshop at LSE where I presented an initial version of the paper!

Lots of thanks to @alejandrofabregastejeda.com, @sabinaleonelli.bsky.social, @davdjacobharrison.bsky.social, @laukas.bsky.social, Roman Frigg, Guido I. Prieto, Julia Sánchez-Dorado, and Lorenzo Sartori for discussions and comments on the previous draft!

And what’s more, such concepts may be useful for current debates - as we argue predictive understanding is for explainable AI!

We argue that when discussing “understanding” in phil sci and epistemology philosophers have overlooked its predictive aspect - one that practitioners of science refer to systematically. Text mining allows the discovery of concepts and enables a broad look on how they’re used.

We introduce methodological basics of digital philosophy and show how they tie (in our view seamlessly!) with broader practices of conceptual engineers, and then provide a proof-of-principle.