Simon Scheller

Analyses of so-called ‘post-truth’ discourse in populist politics have so far largely focussed on sorting it into cases of lying, bullshitting, bubble-like epistemic constraints, or alternative epistemic norms flouting objective truth. We review these proposals and point out problems with each. Some scholars, however, have recently drawn attention to how apparent assertions of facts in these contexts seem to be functionally entangled with expressing or affirming social identities. To get a clearer picture of what such an explanation might amount to, we differentiate four different ways in which social identities might be connected to apparently assertive discourse: signalling, expressive affirmation, dissonance reduction, and identity grounding. Distinguishing and deciding among these will matter not only for providing an accurate analysis of post-truth discourse, but also for determining the exact grounds on which it merits criticism and for what might be done about it.

Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection fit into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the field. Moreover, we argue that philosophers contribute to computational modeling not only by building their own models, but also by thinking about the various applications of the method in philosophy and the sciences. In this context, we note that models in philosophy are usually simple, while models in the sciences are often more complex and empirically grounded. Bridging certain methodological gaps that arise from this discrepancy may prove to be challenging and fruitful for the further development of computational modeling in philosophy and beyond.

Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection ft into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the feld. Moreover, we argue that philosophers contribute to computational modeling not only by building their own models, but also by thinking about the various applications of the method in philosophy and the sciences. In this context, we note that models in philosophy are usually simple, while models in the sciences are often more complex and empirically grounded. Bridging certain methodological gaps that arise from this discrepancy may prove to be challenging and fruitful for the further development of computational modeling in philosophy and beyond.