The news archive of the German Society for Philosophy of Science (GWP).

Submitted by Florian J. Boge (University of Wuppertal).


Synthese Topical Collection on
Simplicity out of Complexity? Physics and the Aims of Science

Extended Deadline: 30 September 2020

Guest Editors
Florian J. Boge (University of Wuppertal)
Paul Grünke (Karlsruhe Institute of Technology)
Martin King (University of Bonn)
Miguel Ángel Carretero Sahuquillo (University of Wuppertal)

The world we live in is notoriously complex: there is an outright zoo of material particles, a vast variety of different species, a whole plethora of stars and galaxies, and so forth. Yet many scientific achievements, such as the Standard Model of particle physics or Darwin’s theory of natural selection, allow us to manage part of this complexity by means of a simple set of laws or general rules.
Simplicity has often been assumed to be an epistemic ideal, most clearly exemplified in physics, with its trend towards encompassing theories that feature only a small number of fundamental laws, capable of explaining a large number of diverse phenomena.
This view of science, with physics at the center stage, has arguably provided the dominant narrative in mainstream philosophy of science throughout the 20th century. Yet many questions arise when one zooms in on the details. For instance: in what sense can the laws of physics be said to be simple, when concrete computations based on them are tedious or even impossible? How do notions of simplicity differ across the sciences, and what are their commonalities? Does the striving for simplification of perceived complexity imply an unjustified reductionism? Is simplicity really an epistemic ideal or just endorsed for pragmatic reasons, and maybe even an unreliable guide to truth? If so, what should it be replaced with?
The aim of this Topical Collection is to bring together contributions from different fields, such as (the philosophy of) physics, biology, economy, psychology, linguistics, or general philosophy of science. Topics may include but are not limited to:

  • epistemic vs. practical: Is simplicity an epistemic goal of science or just a practical benefit? (Why) should theories aim for simplicity, or (why) not?
  • physics vs. other sciences: Does the complexity of the world largely preclude simple science? Is complexity also an aim of the special sciences? Does contemporary physics really aim at simplicity?
  • the concept of simplicity in science: What does it mean to be a ‘simple’ theory? What is simplicity? Can there be a unified account of simplicity or should one embrace pluralism?

We invite contributions from the full spectrum of disciplines and their respective philosophies, scientists and scholars reflecting on their respective and neighboring research fields, as well as historians, philosophers and sociologists of science investigating the epistemologies, practices, and discourses of fellow epistemic communities.

For further information, please contact the guest editors:
Florian J. Boge
Paul Grünke
Martin King
Miguel Ángel Carretero Sahuquillo

The extended deadline for submissions is 30 September 2020
Submit your paper through the Synthese Editorial Manager under a dedicated heading entitled “T.C.: Simplicity out of Complexity? Physics and the Aim of Science”. Please visit Editorial Manager® ( and select this heading when submitting the manuscript.

Submitted papers will be peer-reviewed as per usual journal practice. At least two reviewers will be assigned to each paper and final decisions will be taken by Synthese Editors in Chief, following the recommendation of the Guest Editors, which is based on the reviewers’ reports. Please prepare papers for anonymous reviews.

Submitted by Thomas Müller (University of Konstanz).


Three PhD Positions in Interdisciplinary Project in Philosophy and Physics (f/m/d; part-time 65%, E 13 TV-L or comparable)

The start date is December 1st, 2020, or by agreement. Three positions are available for four years each. Two positions (PhD1, PhD3) will be filled at the University of Konstanz and one (PhD2) at the University of Innsbruck.

The project “The future of creativity in basic research: Can artificial agents be authors of scientific discoveries?“, funded by the VolkswagenStiftung programme “Off the Beaten Track“, studies the role that current and emerging technologies of Artificial Intelligence (AI) can play in basic research, focusing on agency, creativity, and authorship. The project is led by Prof. Thomas Müller at the Department of Philosophy, University of Konstanz, and by Prof. Hans J. Briegel at the Institute of Theoretical Physics, University of Innsbruck. The project connects methods and techniques from philosophy, physics, and AI in an integrated interdisciplinary approach to study the transformative role of new technologies in basic research. See the press release for details:

There are three work packages corresponding to the three PhD positions, two centered on philosophy and based at Konstanz and one centered more on applications in physics and based at Innsbruck: PhD1 (KN): The meaning of experiment in AI-driven research; PhD 2 (IBK): Implementation and case studies; PhD 3 (KN): Agency and attributability of automated research. Each work package will approach our topic from a different perspective: philosophy of science, actual science, and action theory. Methods will vary accordingly, but formal modeling will be used throughout. This includes, to varying degrees, the use of (multi-)agent simulations and the implementation and refinement of machine learning algorithms.

Required background:

  • A completed university degree in a relevant field (philosophy, physics, or computer science / AI)
  • Real research experience will be of advantage
  • Strong communication skills
  • Fluency in English
  • An interest in interdisciplinary research

Application deadline: 9 August 2020
More details and link to the online application:

Submitted by Florian Boge (Wuppertal University).


Call for Papers for a Minds & Machines Special Issue on

Machine Learning: Prediction Without Explanation?

Over the last decades, Machine Learning (ML) techniques have gained central prominence in many areas of science. ML typically aims at pattern recognition and prediction, and in many cases has become a better tool for these purposes than traditional methods. The downside, however, is that ML does not seem to provide any explanations, at least not in the same sense as theories or traditional models do.

This apparent lack of explanation is often also linked to the opacity of ML techniques, sometimes referred to as the ‘Black Box Challenge’. Methods such as heat maps or adversarial examples are aimed at reducing this opacity and opening the black box. But at present, it remains an open question how and what exactly these methods explain and what the nature of these explanations is.
While in some areas of science this may not create any interesting philosophical challenges, in many fields, such as medicine, climate science, or particle physics, an explanation may be desired; among other things for the sake of rendering subsequent decisions and policy making transparent. Moreover, explanation and understanding are traditionally construed as central epistemic aims of science in general. Does a turn to ML techniques hence imply a radical shift in the aims of science? Does it require us to rethink science-based policy making? Or does it mean we need to rethink our concepts of explanation and understanding?

In this Special Issue, we want to address this complex of questions regarding explanation and prediction, as it attaches to ML applications in science and beyond.
We invite papers focusing on but not restricted to the following topics:

  • (How) can ML results be used for the sake of explaining scientific observations?
  • If so, what is the nature of these explanations?
  • Will future science favor prediction above explanation?
  • If so, what does this mean for science-based decision and policy making?
  • What is explained about ML by methods such as saliency maps and adversarials?
  • Does ML introduce a shift from classical notions of scientific explanation, such as causal-mechanistic, covering law-, or unification-based, towards a purely statistical one?
  • (Why) should we trust ML applications, given their opacity?
  • (Why) should we care about the apparent loss of explanatory power?

The Special Issue is guest edited by members of the project The impact of computer simulations and machine learning on the epistemic status of LHC Data, part of the DFG/FWF-funded interdisciplinary research unit The Epistemology of the Large Hadron Collider

For more information, please visit

Deadline for paper submissions: 28 February 2021
Deadline for paper reviewing: 19 April 2021
Deadline for submission of revised papers: 03 May 2021
Deadline for reviewing revised papers: 07 June 2021
Papers will be published in 2021

Submission Details
To submit a paper for this special issue, authors should go to the journal’s Editorial Manager The author (or a corresponding author for each submission in case of co- authored papers) must register into EM.
The author must then select the special article type: “Machine Learning: Prediction without Explanation?” from the selection provided in the submission process. This is needed in order to assign the submissions to the Guest Editor.
Submissions will then be assessed according to the following procedure:
New Submission => Journal Editorial Office => Guest Editor(s) => Reviewers => Reviewers’ Recommendations => Guest Editor(s)’ Recommendation => Editor-in-Chief’s Final Decision => Author Notification of the Decision.
The process will be reiterated in case of requests for revisions.

Guest Editors

  • Dr. Florian J. Boge, postdoctoral researcher, Interdisciplinary Centre for Science and Technology Studies (IZWT), Wuppertal University
  • Paul Grünke, doctoral student, research group “Philosophy of Engineering, Technology Assessment, and Science”, Institute for Technology Assessment and Systems Analysis (ITAS), Karlsruhe Institute of Technology (KIT)
  • Prof. Dr. Dr. Rafaela Hillerbrand, head of the research group “Philosophy of Engineering, Technology Assessment, and Science”, Institute for Technology Assessment and Systems Analysis (ITAS), Karlsruhe Institute of Technology (KIT)

For any further information please contact:
– Dr. Florian J. Boge:
– Paul Grünke:

Submitted by Jürgen Landes (MCMP, LMU Munich).

The Munich Center for Mathematical Philosophy invites participation for the following online conference:

Bayesian Epistemology: Perspectives and Challenges

MCMP, LMU Munich
August 10-14, 2020

The conference on 12-14 August 2020 is preceded by a Summer School on 10-11 August 2020. Both will be held online.

Bayesian epistemology remains the dominant account of rational beliefs, it underpins the dominant account of decision making in science and beyond, as well as many of our statistical methods.
While important applications continue to to emerge, the work on the foundations of Bayesian epistemology never stops and a number of challenges are emerging.
The aim of this conference is bring together scholars exploring applications, challenges and foundations of Bayesian epistemology.

In order to register for the conference, please send an email to with the subject line: Registration: Bayesian Epistemology.

Jürgen Landes (MCMP, LMU Munich)

Submitted by Silvia Jonas (MCMP, LMU Munich).


The Munich Center for Mathematical Philosophy invites registrations for the following event:
Mathematics and Analogical Reasoning
MCMP, LMU Munich
postponed to 27-28 August, 2021

The goal of this conference is to investigate the role of mathematics as a heuristic device for analogical reasoning in science and philosophy.

QUESTIONS we aim to address at the conference include (but are not limited to):

  • How can a positive mathematical analogy generate support for a particular theoretical view about otherwise disconnected physical systems?
  • Can we be sure that epistemic lessons from one domain carry over to another domain, given that there are always known points of disanalogy? If so, how?
  • Does the fact that shared mathematical structures can generate new scientific insights have a bearing on (enhanced) indispensability arguments for mathematical realism?
  • How can a mathematical analogy generate understanding of one system given our understanding of the model system?
  • What is an adequate methodology for analogical reasoning about meta-empirical domains (like mathematics or ethics)?
  • Are the mathematical background assumptions of recent arguments featuring mathematical analogies plausible (specifically in light of recent pluralist developments in set theory)?

More Information is available on the conference website:

The conference also has a PhilEvents website:

In order to register please visit the conference website ( or contact Silvia Jonas ( for further information.

Silvia Jonas (MCMP/LMU Munich)
Mark Colyvan (University of Sydney/MCMP)

Submitted by Erik Curiel (MCMP, LMU Munich).


Topical Issue of Synthese Call for Papers: “All Things Reichenbach”

Guest Editors:
Erik Curiel
Munich Center for Mathematical Philosophy, LMU Munich
Black Hole Initiative, Harvard University

Flavia Padovani
English and Philosophy Department, Drexel University, Philadelphia

Topical Collection Description:

Hans Reichenbach is among the most important philosophers of science of the Twentieth Century and without doubt one of the most prominent philosophers of physics of the first half of the past century. His work has ramified in fundamental ways into virtually every major debate in the philosophy of science and physics. While Reichenbach’s philosophical project is no longer seen as viable as a whole, his work continues to be influential often in unnoticed but deep ways. Although many of his ideas still retain their interest and are discussed in current philosophy of science, he remains, in fact, one of the least understood and least carefully studied philosophical thinkers of his time. Because his own work has not been well understood, his influence is not widely recognized. The primary aim of this collection is to fill this gap by illuminating his contributions to advances in many fields in philosophy, and his legacy in the context of current philosophical research across the discipline as a whole. The theme of the collection, therefore, will be an investigation of his work both in its own context and in its continuing contemporary influence in current philosophy. This collection aims, moreover, at reviving the tradition of inter-disciplinary collaboration that was at the heart of Reichenbach’s vision for intellectual work, promoting the cross-pollination of ideas that discussion across traditional disciplinary boundaries can create and so exploring ways in which his insights can continue to be valuable in current scientific and formal approaches to philosophy. It is, in that spirit, a sequel to the conference “All Things Reichenbach” that took place at the Munich Center for Mathematical Philosophy (LMU Munich) in July 2019 (

Appropriate topics for submission include, among others:

1. geometry, space and relativity
2. the relativized a priori and conventionalism
3. coordination and measurement
4. causality and time
5. statistical mechanics and thermodynamics
6. realism, empiricism and scientific philosophy
7. reasoning, induction and confirmation
8. logic and probability

Any other topic related to Reichenbach is also welcome. As emphasized above, submitted papers can focus on Reichenbach’s own work in its historical context, on the influence of his work in contemporary debates, or on approaches to contemporary problems inspired by his work.

It is the aim of the editors that the selected papers will complement each other, both within each category and across categories.

The link for submitting your manuscript to Synthese, along with instructions for doing so, will be sent soon in a subsequent posting.

For further information, please contact the guest editors:
Erik Curiel
Flavia Padovani

The deadline for submissions is 15 November 2020.

Erik Curiel, Ludwig-Maximilians-Universitat, Munich, Germany
Flavia Padovani, Drexel University, Philadelphia, PA, USA

Submitted by Catherine Herfeld (University of Zurich).


CFP: Synthese Topical Collection: Concept Formation in the Natural and Social Sciences: Empirical and Normative Aspects


Guest Editors:
Georg Brun (University of Bern, Switzerland)
Catherine Herfeld (University of Zurich, Switzerland)
Kevin Reuter (University of Zurich, Switzerland)


Topic overview:
Concept formation has recently become a widely discussed topic in philosophy under the headings of “conceptual engineering”, “conceptual ethics”, and “ameliorative analysis”. Much of this work has been inspired either by the method of explication or by ameliorative projects. In the former case, concept formation is usually seen as a tool of the sciences, of formal disciplines, and of philosophy. In the latter case, concept formation is seen as a tool in the service of social progress. While recent philosophical discussions on concept formation have addressed natural sciences such as physics as well as various life sciences, so far there is only little direct engagement with the social sciences. To address this shortcoming is important because many debates about socially relevant concepts such as power, gender, democracy, risk, justice, or rationality, may best be understood as engaging in conceptual engineering. This topical collection addresses the nature and structure of concept formation in the natural and the social sciences alike, both as a process taking place within science and as an activity that aims at a broader impact in society. This will foster understanding of how concept formation proceeds not only in the natural sciences but also in disciplines such as psychology, cognitive science, political science, sociology and economics. Thereby, we aim at expanding the scope of the philosophical debate about concept formation more generally.


Papers could address questions such as:

  • Which methods of concept formation should be distinguished and why do scholars select them?
  • What are similarities and differences between concept formation in the natural and the social sciences?
  • How does concept formation in the social sciences work in specific cases?
  • How does and how should empirical research into concept use bear on concept formation?
  • How is concept formation shaped by factors such as current language use, measurement, theoretical virtues, and socio-political goals?
  • Do values enter processes of concept formation in science generally, and in the social sciences in particular?

We will consider projects that use either a systematic, a historical, or an empirical approach. We are particularly interested in experimental-philosophical work (e.g., questionnaire studies, corpus analysis) that discusses its use and/or its consequences for explicating or engineering socially-relevant concepts.


The deadline for submissions is 30th September, 2020.


For more information, please contact the guest editors.

Georg Brun:
Catherine Herfeld:
Kevin Reuter: