Early modern formalizations of what is retrospectively called scientific practice (then a natural philosophical one) centre around geometrical methods and their experimental power. From Galileo to Descartes, Pascal, Newton and Leibniz, commitment to visual mathematical techniques are paramount in bringing to bear an effective accumulation of knowledge. It is a literate rationalism, bodies in space that offer a protocol for mechanical reproduction. Galileo's language of the universe becomes a necessary part of knowledge gathering, of the experimental trials that he put its formal predictions to.
Fast-forwarding from the anticipations of Leibniz to the work of Peirce, Carroll and Wittgenstein, geometric diagrams are infused with symbolic and algebraic universality that progresses with time. The visual proof and model takes a formal role in the development of mathematical foundations; and reasoning, now in a more pragmatic vein, comprises what we ascribe to the new social role of scientist. It is a kinematic rationalism filled with dynamic symbols that allow a bottom-up reconceptualizing of instrumental thought. The fallible process of experimentation is coupled with a career-oriented laboratory logical processing.
Forward again another 100 years, via the anticipations of Pascal, geometrical and graphical categories are probabilistic and evolving. Through the work of Strogatz, Barabasi, Brodie and others, calls for new scientific methodology are coupled with the changing and statistical nature of visual formal categorization. AI predictions, data estimations, this computational rationalism is a mutation of clouds and pictures responsively altered. The laboratory is expanded into an IOT device space, the predictive apparatus a handheld multi-use computer. We can here question how much current institutions operate in past paradigms and the use-value of increasing access and democratizing knowledge.
These developments will be seen with the backdrop of cultural paradigms and open science in mind. Against the religious assumption of exceptionalism, we can picture an evolving role for reason that in turn has much to learn from other paradigmatic forms of invention and understanding. An updated methodological model can arguably provide a more apt response to current technologies and problems, and resist the build-up of bureaucratic ritual and stagnation.
(Upcoming Seminar for the School of Materialist Research)