The new possibilities of Big Data and Artificial Intelligence Technologies allow finding unexpected structures and relations in data sets, generated in different fields and contexts. This can be done either to figure out new scientific hypotheses or to find relations which can be used to establish new business models.
A result generated by Big Data or AI can only be interpreted meaningfully by knowing the original research question. Thus, a model with a pre-theoretic hypothesis is necessary. Nevertheless one can find the tendency to substitute the scientific methods by pure numerical methods. This tendency is driven by the development of business models that aims to market a multifunctional use of data once collected in a wide variety of contexts. Some examples in the field of Human Resource Management will be given. It can be shown that the use of such procedures is not reliable. Such procedures should be used in a way that supports decisions, not to automate or substitute them.
About the speaker
Klaus Kornwachs is a permanent Honorary Professor for Philosophy at University Ulm, Germany since 1990, and a member of the German Academy for Science and Engineering. He held the Chair for Philosophy of Technology at Brandenburg Technical University of Cottbus from 1992 to 2011. He studied Physics, Mathematics and Philosophy, and won 1991 the Research Award for Technical Communication of the Alcatel-SEL Foundation. He was Guest Professor at Vienna, Budapest and Dalian. His main fields in research are philosophy of technology, analytical philosophy, philosophy of sciences and general system theory. For publications see http://kornwachs.de.