KI‑Systeme: Aktuelle Trends und Entwicklungen aus Perspektive der Technikfolgenabschätzung

Bernhard G. Humm; Stephan Lingner; Jan C. Schmidt; Karsten Wendland

doi:10.14512/tatup.30.3.11

Authors

Bernhard G. Humm Fachbereich Informatik, Hochschule Darmstadt (DE) https://orcid.org/0000-0001-7805-1981 bernhard.humm@h-da.de
Stephan Lingner Institut für qualifizierende Innovationsforschung und -beratung GmbH (IQIB) (DE) stephan.lingner@iqib.de
Jan C. Schmidt Fachbereich Gesellschaftswissenschaften, Hochschule Darmstadt (DE) jan.schmidt@h-da.de
Karsten Wendland Institute for Technology Assessment and Systems Analysis (ITAS), Karlsruhe Institute of Technology (KIT) (DE) https://orcid.org/0000-0003-4812-0928 karsten.wendland@kit.edu

DOI:

https://doi.org/10.14512/tatup.30.3.11

Keywords:

Artificial Intelligence, AI, Machine Learning, Big Data, Technology Assessment

Abstract

Artificial intelligence (AI) is on everyone’s lips – as well as the associated technologies of machine learning and big data. The enormous dynamics and consequences of these developments become already evident in numerous areas of application in business, society and science. In this context, technology assessment (TA) of AI initially has the task of transforming any excessive public expectations and fears to the factual level. In a second step, TA can provide impulses for the further, desirable design of AI based on reasonable development goals of AI and legitimate societal values. If TA conducts this orientation task close to the technological core, it can consider wide scopes of options for action in the early phases of technology development. Related thoughts are put into concrete terms in this article and will be related to the authors’ contributions to this topical focus.

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