The use of algorithms in human resource management and to support or take over managerial tasks has profound effects on the employees in an organization. The aim is to analyse these effects and, based on this, to derive organizational practices for the successful implementation of algorithms in organizations.
Artificial intelligence (AI) has long been a part of the workplace. Current developments in AI are increasingly enabling interactions between humans and AI at work. In the process, the relationship between humans and AI is also changing to the effect that AI no longer acts only as a tool, but also as a social actor, e.g. as a member of a team. The impact on individuals and teams in the work context implied by the different roles of AI is the focus of this project.
Her research includes data mining, data management, and data processing for crowdsourcing platforms by applying machine learning techniques in conjunction with natural language processing techniques. The goal is to determine the user engagement and its effects on the crowdsourcing platform by predicting the most advantageous parameters.
Christopher Johnson is a research assistant and doctoral candidate within the Faculty of Business and Economics and member of the “Diginomics” graduate group at the University of Bremen. His research focuses on (corporate) responsibility and ethics in a digital society under the supervision of Prof. Dr. Benjamin Mueller (Professor for Digital Business, esp. Management of Digital Transformations) and Prof. Dr. Julia Kensbock (Professor for Management and Organiazation in the digital society).
Multi Agent Systems (MAS), a part of Distributed Artificial Intelligence (DAI) and a subfield of Artificial Intelligence (AI), provides an avenue to develop and analyze models and theories of interactivity in human societies. Whereas traditional AI concentrates on agents as “intelligent stand-alone systems”, DAI concentrates on agents as “intelligent connected systems” and on intelligence as a property of systems that interact. This interaction between intelligent agents helps to provide succinct description and understanding about the collective behavior of intelligent agents in a social system. This opens the possibility to apply multi agent analysis to complex social systems; such as financial markets. As MAS begins to gain practical use in finance, its application can help to provide deep insights into the underlying phenomenon of the cross-section of asset returns. This project from a finance perspective provides a value addition as there are only few applications of agent-based models in finance.
Fateme Rezaei Badafshani has been a research assistant and doctoral candidate in the Diginomics Research Group and in the team of Prof. Dr. Julia Kensbock (Professorship for Management and Organization in a Digitalized Society) and Dr. Katharina Klug at the University of Bremen since May 2023. She is working on the quality of interaction and required psychological skills in the virtual workplace.
New technologies, such as artificial intelligence (AI), are increasingly used in the work context and have a strong impact on employees and their work. The aim of this research project is to investigate the effects of digital transformation on employees, especially in the context of the use of AI in human resource management, and to develop implications for a successful and beneficial use of new technologies for employees.