DESIGN AND TECHNOSCIENCE – WHAT’S UP WITH RESPONSIBILITY?

DS 84: Proceedings of the DESIGN 2016 14th International Design Conference

Year: 2016
Editor: Marjanovic Dorian, Storga Mario, Pavkovic Neven, Bojcetic Nenad, Skec Stanko
Author: Kornwachs, K.
Series: DESIGN
Section: KEYNOTE PRESENTATION
Page(s): 2205-2212

Abstract

„Quia parvus error in principio magnus est in fine, secundum philosophum ...“ (A small error at the outset can lead to great errors in the final conclusions as the Philosopher says ...). (Thomas de Aquinas 1255). Today, nearly every discipline has been converted into a science. The borderlines between the pure or epistemic sciences on the one hand, and the action sciences or applied science on the other hand have become fuzzy. Thus all disciplines have more or less theoretical, empirical and practical issues as well. Any given science can act as an ancillary discipline to any other science.Whilst practical design seems to be only a matter of technology, the study of possibly alternative design is a task for the technological sciences. Yet today, design is done in a scientific and computer aided way as never before. The thinking in alternatives requires that the practical design has become also a scientific, not only a practical task. “The technological sciences establish the cognitive requirements for technological innovation and the application of technological knowledge, and provide us with a basis for considering the impact and repercussions of technology.” Here we call the set of technological sciences Technoscience. We speak about Engineering and Technology as multi-faceted disciplines. With this definition of Acatech (2012) in mind, we take a look to Design Thinking and the Modus 2 of science, according to Helga Novotny (2203). The Modus 2 of science integrates knowledge about theoretical and empirical conditions, knowledge about phenomena and facts as well as knowledge about norms, values, and goals. Together with knowledge about technical practice and knowledge how to shape and design, we have knowledge that we cannot formalize and model completely.

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