Andreas Kaminski

This volume explores the complex landscape of disinformation and its broader implications on trust within society. It tackles questions such as: What constitutes disinformation or fake news? What are the ramifications of its detrimental effects? Are we navigating through a post-truth era? Which emerging technologies could potentially mitigate or exacerbate the adverse effects of disinformation? What kind of audience trust does disinformation tap into? What kind of effect can it have on trust relationships? How can we effectively address the challenges posed by disinformation? Contributors to this volume investigate these inquiries from diverse, primarily philosophical perspectives, while also incorporating insights from a range of interdisciplinary approaches. Readers will be introduced to a vital and ongoing debate aimed at dissecting the phenomenon of fake news, its consequences, and viable strategies for countering its spread. It invites readers to critically engage with the subject matter, encouraging a deeper comprehension of both the challenges and opportunities presented by the digital age.

Numerous ethical guidelines and regulatory frameworks have been developed to assess and shape digital systems. However, these efforts often rest on the dubious assumption that individuals and organisations possess the necessary _capacities_ to assess such systems in terms of justice, reliability, and other normative standards – especially given the growing complexity and corresponding opacity of many digital models. This issue is therefore of central importance to both legal and ethical debates surrounding AI and digital systems in general. The contributors to this volume propose a new approach to digital governance to enhance the capacity to evaluate and shape digital systems.

With the focus topic “The Human Factor”, the Jahrbuch Technikphilosophie 2023 aims to investigate on the one hand the manifold arrangements of the deficiency in the technical field (and especially “new” technologies): How do machine worlds, user interfaces, implementation strategies, or even entire large-scale technological ecosystems model, compensate, and even parody “the” human being – that is, “their” version of ourselves? How does technology discriminate? How does it educate? To what extent can it “reduce” the human? On the other hand, it is necessary to take a new look at what “human” actually means in precisely this context, and to reexamine anthropology as part of theories of technology and discourses on technology. Criticism of technology must therefore also be criticism of man. With contributions by Fabian Anicker, Petra Gehring, Axel Gelfert, Martina Heßler, Andreas Kaminski, Ruth Karl, Katerina Krtilova, Joachim Landkammer, Kevin Liggieri, Felix Maschewski, Nicola Mößner, Anna-Verena Nosthoff, Felix Reda, Jean Paul Sartre, Björn Schembera, Stefan Schöberlein, Marcel Siegler, Florian Sprenger and Martin Warnke.

The phrase ‘trust in science’ raises the question of how trust can have a place here, especially when it is not ‘merely’ about public trust in science, but about trust in science itself. Does this not constitute a category mistake? Or perhaps a fact that nonetheless violates central epistemic norms? An intuitive strategy to address these concerns is to epistemologize trust itself. Accordingly, trust in science would itself be a matter of knowledge. However, epistemic trust (in science) presents both a conceptual and a practical problem. Normative positions that seem to offer a solution to these difficulties like the assurance view face their own conceptual and practical problems. This paper demonstrates how theory development leads to a virtue theory of trust, which, by unifying the epistemic and normative dimensions, allows for solving the conceptual problems. However, it too is confronted with challenging practical issues.

Trust is a central pillar of the scientific enterprise. Much work in the philosophy of science can be seen as coping with the problem of establishing trust in a certain theory, a certain model, or even science as a whole. However, trust in science is threatened by various developments. With the advent of more complex models and the increasing usage of computer methods such as machine learning and computer simulation, it seems increasingly challenging to establish trust in science. How and on what basis can an appropriate trust in science be built? We are interested in how trust is established in such cases of increasing complexity (of models and communication) and what could be appropriate measures to alleviate doubt.

Die Phänomenologie hat bedeutsame Beiträge zur Technikphilosophie hervorgebracht. Dabei sprach, als Edmund Husserl sie begründete, nicht viel dafür, dass sie uns Einsichten in Technik vermitteln könne. Wie kommt es dazu? Wie entwickelt sich die Technikphänomenologie in der Nachfolge Husserls weiter? Was sind ihre Erträge?Der Beitrag führt zunächst in wichtige Begriffe phänomenologischer Untersuchungen bei Husserl ein und entwickelt von diesen ausgehend seine Überlegungen zur Technik. Anschließend werden die technikphänomenologischen Beiträge von Martin Heidegger, Maurice Merleau-Ponty und Hans Blumenberg sowie die Weiterentwicklung zur Postphänomenolgie bei Don Ihde vorgestellt.

Searching for- and finding the right word is, especially if we want to be precise, enlightening regarding the realtion of language and thought. My thesis is that in the searching for- and finding of words we can see that language and thought are neither identical nor can they be separated. They represent a differentiated unity; furthermore, starting from the relation of language and thought a fundamental difference between the language pratices of humans like us and the way in which Large Language Models ‘find’ words comes to light.

Trust is a central pillar of the scientific enterprise. Much work in the philosophy of science can be seen as coping with the problem of establishing trust in a certain theory, a certain model, or even science as a whole. However, trust in science is threatened by various developments. With the advent of more complex models and the increasing usage of computer methods such as machine learning and computer simulation, it seems increasingly challenging to establish trust in science. How and on what basis can an appropriate trust in science be built? We are interested in how trust is established in such cases of increasing complexity (of models and communication) and what could be appropriate measures to alleviate doubt.

Blumenberg has sometimes described his work as a phenomenology of history. The connection between history and phenomenology is particularly striking in the context of Blumenberg’s contributions to the philosophy of technology. In the course of his analysis of Husserl’s Krisis, Blumenberg develops, as my contribution aims to show, a conception of history in which complete technologization leads to a perfected lifeworld. Blumenberg formulates this partly explicitly within the framework of a three-stage model of history, but there are also implicit insights in Blumenberg’s texts that seem to work with such a structuring of history.

Broken trust elicits two types of responses: On the one hand, an epistemic response: How could I be so mistaken? How can I learn to trust more appropriately? On the other hand, a moral response: How could you deceive me so deeply and hurt me so profoundly? Even though the response in a given case may be more epistemically or morally emphasized, their interrelation raises two theoretically challenging questions: (1) How can a unity of the epistemic and normative dimensions of trust be reflected in theories; thus far, these dimensions tend to diverge in predominant approaches that model trust either epistemically or normatively (e.g. evidential vs. assurance view). (2) How can it be understood that it is constitutive of trust that it can be broken, and that it is constitutive of trust that there is no risk in the very essence of trusting. The present paper proposes a response to these two questions.

The thematic focus of this yearbook is concerned with the various relations of „art“ and „technology“. It seeks to interrogate and reflect their conceptual filiations, their complementarities and mutual stimulations, and contrasts and tensions. The very notion of the „work“ challenges us to explode or triangulate the dichotomy of art and technology. This connects to further problems in and for the philosophy of technology, such as the relation of arts and crafts, the question of Kitsch or camp in art and technology, or the role of play as a basic modality of artful technical production. Finally, of course, comes design, packaging, marketing and the aesthetic effects of works. With contributions by Katrin Becker, Rainer Becker, Andreas Beinsteiner, Hans Blumenberg, Johanna Dombois, Daniel Martin Feige, Nico Formanek, Petra Gehring, Sebastian Hallensleben, Andreas Hauschke, Dawid Kasprowicz, Viet Anh Nguyen Duc, Regina Oehler, Anika Reineke, Dirk Rustemeyer, Bernhard Siebert, Larissa Ullmann, Claudia Wiesemann, Ryan Mitchell Wittingslow and Konstanze Wolter.

Unter der Leitdifferenz „Steuern – Regeln“ werden in der herkömmlichen Technikphilosophie die beiden Operationsmodi „klassischer“ Technik gefasst und beschrieben. Dies geschieht in zweierlei Hinsicht: zum einen in der Absicht, die sich seit der neolithischen Revolution ausprägende menschliche Technik im Unterschied zur „Zufallstechnik“ (Ortega y Gasset) höherer Spezies oder der Urmenschen zu spezifizieren; zum anderen mit dem Ziel, das Verhältnis von Technik und (Natur-)Wissenschaft genauer freizulegen. Indessen fordern aktuelle Technologien, historische Zustandsbeschreibungen einer „Technoscience“ sowie neue epistemische Praktiken die Zweiteilung von „Steuern“ und „Regeln“ heraus. Mit Blick auf sogenannte „new emerging sciences and technologies“ (NEST) und andere Entwicklungen in den Informations-, Kognitions-, Nano- und Biotechnologien fragt dieser Band danach, wer oder was als Subjekt von Steuerungs- und Regelungsprozessen konzeptualisiert werden kann. Im Kontext großtechnischer Systeme sowie der Organisation großer sozialer Gebilde werden die Steuerungsmöglichkeiten dabei zunehmend problematisch, denn insbesondere digitale Informationstechnologien eröffnen neue, vielfältige Optionen zur Manipulation und Regulation von Prozessen oder Zuständen (z.B. Monitoring, Big Data, Profiling), während gegenläufige Konsequenzen derselben Entwicklung (z.B. Datenflut, Akzeleration, Automatisierung, ‚Eigenlogik’ soziotechnischer Infrastrukturen) die Möglichkeiten einer koordinierten Steuerung zunehmend in Frage stellen.