8. Seminar zur Philosophie der Physik

Information

Tübingen, 24. – 26. Oktober 2025

Bild © Ramona Fontaine, Untitled

Call for Application

Der Workshop richtet sich insbesondere an Bachelor- und Masterstudierende der Physik und der Philosophie, aber auch an Studierende anderer Fachrichtungen. In Fachvorträgen und Diskussionsgruppen wird den Teilnehmer*innen das Forschungsgebiet der Philosophie der Physik vorgestellt. Schwerpunkt ist das Thema Information. Vorkenntnisse in Physik oder Philosophie waren nicht erforderlich.

Neben englischsprachigen Fachvorträgen von Christopher Timpson (Oxford) zum Informationsbegriff in der Quanteninformation, Javier Anta (Sevilla) zur Philosophie der Information und Saaskhi Dulani (John’s Hopkins) zum Informationsparadoxon schwarzer Löcher wird es deutschsprachige, moderierte Kleingruppendiskussionen auf Basis vorbereitender Lektüre (beispielsweise zu Wheeler’s `It from Bit') und eine Podiumsdiskussionen zur Frage: `Was ist Philosophie der Physik?' geben.

Die Übernachtungskosten der Teilnehmer*innen werden vollständig übernommen. Auf Anfrage kann zusätzlich auch eine (anteilige) Übernahme der Reisekosten geprüft werden.

Bewerbungsfrist: 15. September 2025 (Rückmeldung unsererseits erfolgt bis zum 20. September)

Kontakt: seminar(at)philosophiederphysik.de

Webseite: www.philosophiederphysik.de

Organisation: Maren Bräutigam (Köln), Niels Linnemann (Genf), Kian Salimkhani (Nijmegen), Annica Vieser (Genf), Karla Weingarten (Nijmegen)

Hosts: Sophie Atzpodien und Michael Herrmann

Der Workshop wird unterstützt durch das Forum für Wissenschaftskulturen der Universität Tübingen.

Vorläufiges Programm

Hier schon mal ein grobes Programm für die Planung.

Vorträge

Benjamin Jantzen (Virginia Tech): Information and dynamics: competing metaphors for biological intelligence
It is fashionable to consider organism behavior---the variable response of a living thing in a dynamic environment---in terms of information. Organisms are said to harvest or take in information from the environment that is then processed to generate a behavioral response. This informational perspective in turn supports a number of theses concerning behavior, such as the idea that large brains are needed for "complex" behavioral repertoires, or that adaptive behavior involves the storage of states reflecting bits of information about the world external to the organism. There are reasons to be suspicious of these and other consequences of informational thinking, and thus of the underlying metaphor. Here, I will focus just on the connection between internal and external states in producing adaptive behavior.
There is a long tradition of describing organisms as information processors, and their internal states as engaged in storage of information and its transformation by computation. Broadly speaking, this perspective divides behavior along the boundary of the organism. Information enters by why of sensation, is transformed by computation, and exits in the form of behaviors, whether physiological or mechanical. Such a view demands that enough information be passed in from sensory systems at a high enough rate and be transformed quickly enough via computation to produce responsive, adaptive behavior. It thus puts constraints on the relation between the world outside and the world inside an organism. Rate-distortion theory, for instance, tells us, when given some measure of performance as a function of internal and external states, how many bits of mutual information between internal states and the environment are needed to optimize performance. It is presumed that this mutual information between external and internal states is like matter or energy that the organism must then harvest to survive.
However, I argue that two classes of system for realizing adaptive behavior---reservoir computers and systems exhibiting "strong anticipation"---put pressure on this view, or at least on the utility of information talk as anything more than metaphorical. In both cases, it seems that a straightforward application of information theoretic approaches yield contradictory judgments on the amount of information the system must harvest from its environment, and that it's probably best to view these cases in dynamical, rather than information-theoretic terms. This in turn suggests ways of improving our quantitative study and application of such systems by selecting more appropriate metrics of their behavioral capacities.

Diskussionsgruppen

(A) Niels Linnemann und Annica Vieser: It from bit
(B) Oxana Shaya: What are resources in quantum computing?
(C) Sophie Atzpodien: tba