Epistemic aims, methodological choices, and value trade-offs in model...

Different epistemic aims are satisfied by prioritizing different epistemic values. Axel Gelfert (2013, 2016) argues that trade-offs in modeling such as those between generality, precision, and realism can be understood as demarcation criteria between sciences. I build on Gelfert’s argument by focusing on a pervasive kind of trade-off in computationally intensive modeling – that between accuracy and speed. I use a case study in physics to show how trading off speed and accuracy satisfies different epistemic aims, but rather than demarcating sciences, it transforms the disciplinary boundaries. I argue in favor of an epistemically significant role for speed of generating results, which is often dismissed or downplayed as an extra-scientific element, or conflated with ease of use. The case study is informed by qualitative interviews conducted with practicing modelers in theoretical physics.

References

Gelfert, A. (2013), “Strategies of model-building in condensed matter physics: trade-offs as a demarcation criterion between physics and biology?”, Synthese 190: 253–272.

Gelfert, A. (2016), How to Do Science with Models? A Philosophical Primer. Springer.