Learning to Transform by Implementing AI into Administrative Decisions – Disruptive Mindset as the Key for Agility in the Crisis

Abstract

The Objectives of the research paper are investigations in how a disruptive Mindset can have effects on interaction by representatives of German Authorities in times of crisis. The interdisciplinary focus of human transformative learning maybe sets linking options to machine learning approaches to speed up qualified decision making. The Approach is in addition to an introduction of implementation strategies for AI technology in the local governance of German Municipalities, what competencies of persons in charge are required to get use of technological possibilities. In this respect, the investigation bases on findings of three studies in field of “scenarios for AI in the public sector”, “AI as impact on competencies in the field of corporate finance” and “competencies in a digitalized working environment”. The Results concern the understanding what preconditions for human and AI-oriented learning systems are necessary in suitable scenarios of public sector performance. Also, convergent competence structures, based on transformative learning theories, should show a way for implementation based on models for interaction in critical situations. The Value of the paper lies in the combined View of administrative requirements in relation to learning-strategies considering technological scenarios of AI for professionalize the decision-making processes in times of Covid-19 pandemic crises.