In our Inaugural Sequences reading group, we examined the core definitions of rationalist thought—specifically the distinction between epistemic rationality (forming true beliefs) and instrumental rationality (achieving goals). To lay the groundwork for this, it is helpful to look at the history of cartography and the transition from speculative mapping to actual navigation.
In the 17th century, the Royal Society of London triggered an inflection in mapmaking. For the centuries beforehand, scholastic philosophy had treated knowledge as a Socratic exercise of internal consistency and textual authority. Maps of the era were often speculative works of art, filled with imaginary continents, sea monsters, and ideological borders designed to please patrons rather than guide sailors. A mapmaker was judged by the elegance of his drawing, not the accuracy of his soundings. When the Royal Society began insisting on empirical measurement—demanding that captains return with precise longitudes, currents, and shoreline coordinates—they met resistance. The established thinkers preferred the neat, Socratic perfection of their conceptual globes to the messy, wet, and often contradictory reports of sailors in the real world.
This resistance reveals a deep human failure mode: the Socratic trap. It is the tendency to fall in love with the map (the elegant theory, the clean classification system, the social badges of rationality) while refusing to walk the territory. We build complex mental models of our careers, our relationships, and our cognitive biases, treating the precision of our diagnostics as a victory. But a map, no matter how detailed, is not a journey. If we do not use our models to make better decisions and navigate the concrete challenges of our lives, we are simply speculative cartographers drawing borders on imaginary lands.
In our conversation, we noted the difference between theories of knowledge making which attempted to increase accuracy, vs theories of knowledge making which attempt to increase precision. The scholastic approach is weakest at its foundation; it's only as good as your starting assumptions. My main takeaway was that it is essential to examine the world, including my foundational assumptions, and hold my map accountable to the data I'm actually encountering. Endlessly precising over an assumption that neither is real nor helps me win might be intellectually gratifying, but in the end leaves me both wrong and useless.