Employee Acceptance for AI Based Knowledge Transfer: Conception, Realization and Results of an ELSI+UX Workshop

Abstract

German companies are currently facing challenges like the Demographic Change. Due to the retirement of many long-standing employees, companies risk losing tacit experimental know-how. This specific type of knowledge is difficult to capture and transfer to unexperienced workers. The objective of the research project “KI_eeper - Know how to keep” is to solve this challenge by using Artificial Intelligence (AI) for the development of a self-learning assistance system. Knowledge transfer as well as AI can cause fears among workforces, which hampers user acceptance of new AI-based tools. Therefore, the employees got proactively involved from an early development stage on through different measures, like e. g. workshops and process analyses. In particular the ELSI+UX workshop openly embraces potential challenges of AI implementation and the fears of employees. Furthermore, the employees get the chance to provide direct feedback about the technical solution of how user-friendly it is for their work process. This contribution focuses on the conception and realization of an ELSI+UX workshop. In the workshop the ethical, legal and social implications (ELSI) as well as user experience (UX) of the technical conception were assessed by the employees. This approach promoted substantial progress of the project and nurtured user acceptance of the AI system.