In a data economy, businesses have large amounts of data available that enable them to make data-based decisions (Data-Driven Management, “DDM”). This applies not only to tech companies, but increasingly to data-intensive SMEs and Start-ups. In many cases, automated systems (e.g. Artificial Intelligence) are used to prepare or make business decisions on the basis of data. However, accessing and analyzing data requires a broad spectrum of competences and skills: Technical understanding and organisational knowledge is required. Furthermore, accessing and analyzing data requires a broad spectrum of legal knowledge, as companies and employees need to know how data can be used in accordance with legal provisions (IP rights, data protection etc), which unintended side-effects occur (e.g. discrimination) and which legal risks (e.g. liability) DDM entails and how they can be avoided. Therefore, a competent handling of automated systems and related technologies for DDM constitutes a key competence in a data economy. OBJECTIVES: DDM4SME develops and provides education on potentials, challenges and (legal and societal) risks of DDM. Knowledge will be provided on the legal, societal, technical and organizational dimension and on how DDM can be implemented in order to avoid risks and drawbacks (e.g. liability and discrimination). Thereby, the objective of DDM4SME is to provide education which fosters employability of learners and increases competitiveness of businesses. Furthermore, the education provided by DDM4SME shall fister constructive, but critical thinking towards autonomous systems.
|Name der begünstigten Einrichtung||Donau-Universität Krems|
|Projektleitung||Zentrum für Geistiges Eigentum, Medien- und Innovationsrecht|
|Förderrahmen & Förderprogramm||Erasmus+, KA2 - Strategische Partnerschaften|