Kristian González Barman

arXiv2026

Scientific understanding across disciplines: in varietate concordia?

Understanding is a generally acknowledged aim of science, but the way in which understanding is pursued and criteria for when it is achieved differ widely across scientific disciplines. This paper offers a comparative analysis of this disciplinary variation, aimed at revealing differences as well as commonalities in methods and criteria for achieving understanding. Starting point is the contextual theory of scientific understanding (De Regt 2017), which was developed to accommodate contextual variation in criteria for understanding. While this work focused on historical variation and used mainly case studies from the history of physics, the current paper applies the contextual theory to disciplinary variation. We present brief descriptive accounts of how understanding figures in nine scientific disciplines: mathematics, theoretical physics, astrophysics, chemistry, geoscience, biology, neuroscience, psychology, and the engineering sciences. Subsequently, we compare and evaluate these accounts in light of the contextual theory of scientific understanding.

physics.hist-ph↗

arXiv2025

Reinforcement Learning from Human Feedback: Whose Culture, Whose Values, Whose Perspectives?

We argue for the epistemic and ethical advantages of pluralism in Reinforcement Learning from Human Feedback (RLHF) in the context of Large Language Models (LLM). Drawing on social epistemology and pluralist philosophy of science, we suggest ways in which RHLF can be made more responsive to human needs and how we can address challenges along the way. The paper concludes with an agenda for change, i.e. concrete, actionable steps to improve LLM development.

cs.CY↗