Causal Reasoning in Physics

In this paper I examine several neo-Russellian arguments for the claim that there is no room for an asymmetric notion of cause in mature physical theories. I argue that these arguments are unsuccessful and discuss an example where an asymmetric causal condition plays an important role in the derivation of a physical law

Correction to: Editorial: symmetries and asymmetries in physics

The article Editorial: symmetries and asymmetries in physics, written by Radin Dardashti, Mathias Frisch, Giovanni Valente, was originally published electronically on the publisher’s internet portal on 3 July 2020 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 16 June 2021 to © The Author(s) 2021 and the article is forthwith distributed under a Creative Commons Attribution

Causal Explanation in Physics

In this chapter I discuss both what influential general theories of scientific explanation imply for the particular issue of causal explanation in physics and whether there are arguments distinct to physics concerning the status of causal explanations

The Babylonian conception and conventionalism about laws in physics

In this paper I discuss two features of laws in physics and ask to what extent these features are compatible with different philosophical accounts of laws of nature. These features are (i) that laws in physics fit what Richard Feynman has dubbed the "Babylonian conception" of physics, according to which laws in physics form an interlocking set of ‘theorems’; and (ii) that the distinction between dynamics and kinematics is to some extent contextual. These features, I argue, put pressure on any philosophical account of laws that presupposes that the laws of physics have a unique quasi-axiomatic structure, such as the Mill-Ramsey-Lewis account of laws and metaphysical accounts of laws that assume that there is a privileged explanatory nomological hierarchy

How models change the world – and what we should do about it

Models that make predictions about the COVID-19 pandemic are complicated by the fact that people change their behaviour in response to these predictions. Lucie White discusses how we can deal with this, based on a recent paper with Philippe van Basshuysen, Donal Khosrowi and Mathias Frisch

Die „Jahrhundert-Herausforderung“ Corona : Ethische und wissenschaftsphilosophische Aspekte

Die Lockdowns während der Pandemie brachten weitreichende Einschränkungen individueller Freiheiten und wurden emotional diskutiert. Unter welchen Umständen sie gerechtfertigt sein könnten, inwieweit wir uns auf wissenschaftliche Expertise und idealisierte Modelle berufen können und wie die digitale Kontaktverfolgung gerechter und effektiver gestaltet werden könnte, untersuchen Forscher am Institut für Philosophie in zwei von der VolkswagenStiftung geförderten Projekten

Big Data, Machine Learning : und diskriminierende Algorithmen?

Computer-Algorithmen werden zunehmend eingesetzt, um menschliche Entscheidungen in wichtigen gesellschaftlichen Bereichen zu unterstützen, anzuleiten oder sogar zu ersetzen. Indessen häufen sich die Hinweise, dass Algorithmen mitunter ebenso voreingenommen und diskriminierend agieren können wie Menschen. In dem interdisziplinären Forschungsprojekt „Bias and Discrimination in Big Data and Algorithmic Processing – BIAS“ arbeiten Wissenschaftler*innen aus Philosophie, Rechtswissenschaft und Informatik daran, diskriminierende Algorithmen zu verstehen und zu verbessern

When is Lockdown Justified?

How could the initial, drastic decisions to implement “lockdowns” to control the spread of COVID-19 infections be justifiable, when they were made on the basis of such uncertain evidence? We defend the imposition of lockdowns in some countries by first, and focusing on the UK, looking at the evidence that undergirded the decision, second, arguing that this provided us with sufficient grounds to restrict liberty given the circumstances, and third, defending the use of poorly-empirically-constrained epidemiological models as tools that can legitimately guide public policy

Identification of the honey bee swarming process by analysing the time course of hive vibrations

Honey bees live in groups of approximately 40,000 individuals and go through their reproductive cycle by the swarming process, during which the old queen leaves the nest with numerous workers and drones to form a new colony. In the spring time, many clues can be seen in the hive, which sometimes demonstrate the proximity to swarming, such as the presence of more or less mature queen cells. In spite of this the actual date and time of swarming cannot be predicted accurately, as we still need to better understand this important physiological event. Here we show that, by means of a simple transducer secured to the outside wall of a hive, a set of statistically independent instantaneous vibration signals of honey bees can be identified and monitored in time using a fully automated and non-invasive method. The amplitudes of the independent signals form a multi-dimensional time-varying vector which was logged continuously for eight months. We found that combined with specifically tailored weighting factors, this vector provides a signature highly specific to the swarming process and its build up in time, thereby shedding new light on it and allowing its prediction several days in advance. The output of our monitoring method could be used to provide other signatures highly specific to other physiological processes in honey bees, and applied to better understand health issues recently encountered by pollinators