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    Campus der Universität Bielefeld
    Campus der Universität Bielefeld
    © Uni Bielefeld / Philipp Ottendörfer

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CUDE Lecture Series: Coping with Uncertainty in Dynamic Economies

In this lecture series, the principal investigators of the Research Training Group 2865 "Coping with Uncertainty in Dynamic Economies" present current research results on the programmes's topics and relate them to their own current research. Our goal is to familiarize doctoral candidates with the current state of affairs and to stimulate new research in this area.

Further information can be found on the ekVV-page of the CUDE Lecture Series.


International Conference: Navigating Uncertainty - Preparing Society for the Future

June 05 - 07, 2023, Center for Interdisciplinary Research (ZiF), Bielefeld University

Various researcher in social sciences and humanities have, over time, developed a variety of theoretical and empirical approaches to study and interpret the impact of uncertainty on (individual) decisions and social phenomena. With this conference, we wanted to bring them together in a place of interdisciplinary exchange. The conference “Navigating Uncertainty: Preparing Society for the Future” provided a platform for interdisciplinary exchange on the systematic analysis of different ways individuals and institutions deal with uncertainty and of the resulting societal implications.


Uncertainty Talks

Universität Bielefeld
© Uni Bielefeld / Philipp Ottendörfer

Uncertainty has an impact on almost all aspects of human life. For a long time, it has been viewed as an omnipresent threat that needs to be controlled and kept in check. In contrast, our ambition is to broaden and advance research on uncertainty by taking an approach that focuses on different modes of navigating uncertainty. The "Uncertainty Talks" contribute to the interdisciplinary understanding of this research approach by providing different perspectives on this analysis. The public lectures are usually held in the plenary hall of the Center for Interdisciplinary Research (ZiF).

In his monumental “The evolution of knowledge”, Jürgen Renn describes a sequence of three punctuated equilibria along the way humans have so far dealt with knowledge – and therefore with uncertainty, too. First comes a period where our ancestors lived in small non-sedentary communities (1). The evolution of biological features ranging from the shape of human bodies to the functioning of our brains enabled them to learn about the world they lived in. With the neolithic revolution, knowledge was then increasingly connected to the material infrastructures of cities, ships, tools, and more (2). People lived in stratified societies with a central authority – be it an individual or an institutionalized collective - claiming control over some territory. Of course, uncertainty was a normal aspect of life, but when it led to doubts threatening the social order, sophisticated explanations combined with violence could often make such doubts ineffective. Those explanations were elaborated by elites whose works of art and scientific knowledge rightly impress us today. The transition to the third phase started nearly a millennium ago in Europe (3). There, craftmanship evolved into a division of labor based on lifetime learning that begun with apprenticeships for different occupations. It is often overlooked that academic knowledge and institutions developed hand in hand with this culture of lifetime learning in a community of practice. A key achievement of the resulting fabric of science and technology was the ability to manage the risks and uncertainties of investing capital, using concepts of probability and optimization. Paradoxically, this ability has led humankind to the global risks and uncertainties of the Anthropocene. Developing concepts and institutions adequate to this challenge will take a long process of inquiry. An illustrative example is given by the future of the car as means of transport and cult object.

 

Can data make room for uncertainty? And if so, what kind? This talk will discuss some humanists' concerns about the growth of data-driven scholarship. Digital humanists, so the argument, stand to benefit from taking some of these objections seriously. They point to real epistemological differences between "data" as the term is used and the traditional practices of humanistic scholarship. Understanding this tension can help understand both data and the humanities more fully — and point to some exciting future directions for data-engaged scholarship.

 

Bis heute sind individuelles und institutionelles Handeln von Rationalisierungsprozessen der Moderne geprägt. Dessen ungeachtet, lehnen Menschen vernünftige Schutzimpfungen ab, hängen Verschwörungstheorien an oder vertrauen blind der Wissenschaft. Um den Umgang mit riskanten Unsicherheiten zu verstehen, ist es daher nützlich, neben rationalen Umgangsweisen weitere Modi des Umgangs mit Unsicherheit einzubeziehen, wie etwa Vertrauen, Intuition und Gefühl sowie Hoffnung und Glaube. Dabei wäre es voreilig, solche Umgangsweisen als subjektive Irrationalitäten abzutun. Vielmehr ermöglichen sie erst in ihrem Zusammenspiel vernünftig mit Unsicherheiten umzugehen. Zudem sind auch auf institutioneller Ebene nicht nur Prozesse der Rationalisierung und Verzauberung zu beobachten. Die Subjektivierung abstrakten Wissens kann als Voraussetzung für deren lebensweltliche Wirksamkeit verstanden werden.

Ungewissheit ist etwas, was wir nicht mögen. Einst waren es Horoskope und Globuli, die Gewissheit versprachen, heute sind es Algorithmen, die als allwissend vermarktet werden: Google kennt uns besser als wir selbst, Online-Partner*innenbörsen finden für uns die idealen romantischen Partner*innen, und IBM Watson wird die Medizin revolutionieren. Regierungen von China bis zu Deutschland versprechen uns Sicherheit, wenn wir uns nur mehr überwachen lassen. Wie können wir lernen, vernünftig mit Ungewissheit umgehen?

Real-world decisions differ in many ways from those studied in laboratories and textbooks. We must often make massively consequential choices when, whether we know it or not, data is incomplete, the options are ambiguous, the future may not resemble the past, and the axioms of standard decision theory are not satisfied. Such decisions often require both commitment and flexibility over time. Above all, such decision-making is about taking action in the face of potentially paralyzing uncertainty. While choices like monetary gambles may be amenable to standard analyses, it is far less clear how career choices, climate change, pandemic mitigation, and most government policy can be effectively understood in this way. Conviction Narrative Theory is a theory of decision-making that sets out how human cognitive, affective and social capacities are well adapted for such decisions and identifies the implications for research and decision-makers.

Entscheidungen sind Versuche, die Zukunft zu binden. Sie finden in einer Gegenwart statt und zielen darauf, einen bestimmten Zustand in der Zukunft herzustellen. Deshalb finden Entscheidungen immer unter Bedingungen von Unsicherheit statt. Es gilt sogar: Eine Entscheidung kann nur eine Entscheidung sein, wenn sie die Kontingenz ihrer selbst schon mitliefert, wenn also genauso gut auch anders hätte entscheiden werden können. Wenn das per se gilt, stellt sich die Frage, ob die Unsicherheitsbedingung für Entscheidungen überhaupt steigerbar ist oder ob es anderer Kategorien bedarf, um besonders schwierige Entscheidungslagen beschreiben zu können.


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