Mathematical neutrality in science, technology and society

The interplay between scientific knowledge and society is a central theme in the philosophy of science. Engineering and science crucially rely on mathematical tools, and mathematics might influence society via the sciences or even directly.

Mathematics is usually regarded as a discipline which admits no grey areas in most situations: answers are either correct or incorrect; there is a universal, objective, correct answer. On the other hand, ethical, moral and political questions are usually not “correct” or “incorrect”, they are complicated and full of grey areas. This makes it extremely tempting to see the sciences and mathematics as a good way to settle disputes concerning issues like justice or equity. If the ethical/moral/political question can be reduced to a mathematical question, may the grey areas disappear? Can we make use of modern technologies like AI, Big Data and Machine learning to this end? How can mathematics promote consensus in controversial topics?

Similarly, it is usually considered that mathematics is the universal language of the world, one that describes it “as it is”. According to this view, mathematics is neutral in the production of scientific knowledge: the scientist discovers the mathematical rules of nature (like laws and mathematical models) and applies mathematical methods to which nature owes allegiance (like statistics and algorithms).

Recent scholarship warns about the increasing use of mathematical techniques in order to prescribe policies and produce knowledge under a veil of neutrality, and argues that we should carefully evaluate the consequences of these techniques in science and society.

This Topical Collection aims at contributing to this literature. Topics include but are not limited to:

- The moral responsibility of pure and applied mathematicians

- Value-ladenness of mathematics

- Algorithmic governance

- The mathematization of science: how (not) to use mathematics, and ethical/epistemic consequences

- Statistics in science and society: how (not) to use statistics, and ethical/epistemic consequences

- Ethical concerns about mathematics education

The project and the editors are support by the FWO-project "The Epistemology of Big Data: Mathematics and the Critical Research Agenda on Data Practices" (FWOAL950) and the SNF projects: Mathematizing biology: measurement, intuitions, explanations and big data (P500PH_202892) & Mathematical models and normativity in biology and psychology: descriptions, or rules of description? (P5R5PH_214160).

For further information, or if you are unsure whether your paper idea fits the theme, please contact ideally both of us: jose.antonio.perez.escobar@ens.psl.eu; deniz.sarikaya@vub.be. The deadline for submissions is December 15, 2023.

Papers should be submitted via Global Philosophy’s editorial manager at: https://www.editorialmanager.com/axio/default1.aspx. When the system asks you to “Choose Article Type”, please scroll down in the pull-down menu to choose this topical collection. (Tag S.I. Mathematical neutrality in science, technology and society)

When preparing your paper, please read the journal’s ‘Instructions for authors’ at: https://www.springer.com/journal/10516/submission-guidelines