We initially present some findings on the importance of artificial intelligence for current HFE research based on a bibliometric study of the proceedings of the most recent annual conference of the Human Factors / Ergonomics Society in Germany (GfA, 2024). Given that importance we discuss the duality of AI as a tool and a player in work systems and based on extant research suggest that the aspects of hierarchy and emotion are considered when designing roles for AI. Using these aspects as dimensions we span a portfolio and suggest ‘colleague’, ‘copilot’, ‘companion’, and ‘controller’ as potential roles for AI in work systems thereby contributing to the discussion and analysis of yet to be properly defined “AI-infused” work systems.

Current influences such as the Corona pandemic, war in Ukraine and the resulting energy crisis, delivery and supply bottlenecks, and climate change are calling on the state, society, and business to deliver cooperative and sustainable concepts in response. In addition to developments in the areas of demography and decarbonization, in particular potentials of internal as well as cross-company digitalization of processes and structures lead to a profound transformation of our working world. Promising innovations are also promised by hybrid AI approaches, new network architectures and AI simulations using quantum computers. The presentation will show how hybrid AI methods can be used to combine the knowledge and experience of experts (e.g., specialists) with data-based approaches that use machine learning methods to analyze statistical correlations and derive recommendations for new business models and forms of human-machine interaction for process optimization.

The digital transformation of entire economic sectors and occupational profiles as well as the introduction of new forms of human-machine collaboration through the increased use of cognitive systems require completely new approaches. The key to success in coping with this change, which can be seen in all industries, is to break up old structures and venture something new. The ability to adapt and innovate is becoming a central success-critical factor in entrepreneurial activity. In order to continue to achieve market success and ensure sustainable growth in an extremely dynamic and disruptive environment, companies and organizations are called upon to proactively shape change. In addition to the establishment of flexible working models and agile processes, the increased generation and integration of knowledge into and around technical systems in the course of targeted competence development of employees is indispensable. The introduction and use of technical systems thus must go hand in hand with the flexibilization of innovation and collaboration processes as well as the development of employee skills in order to generate the currently missing socio-technological link – for companies´ added value and for the benefit of people. In this paper, the authors present an overview of currently used creativity techniques and innovation methods and work out the strengths and weaknesses of the respective tools. Furthermore, the resulting need for action for the optimization of innovation processes in the interaction of established techniques and possibilities of cognitive systems is presented.

Business model innovations (BMIs) are a promising approach to be successful in hyper-competition. There are several approaches for the systematic development of BMI. Within these approaches, however, companies are faced with major challenges, especially, in the decision-making process. On the one hand, certain information is not available, and on the other hand, cause-and-effect relationships within the innovation networks or systems are not known. In certain contexts, simulations can close this gap. Thus, this paper addresses the research question of how simulations can be systematically integrated into BMI approaches. Therefore, BMI processes and different simulation applications are reviewed, the aspect of BMI prototyping is identified and an extended BMI approach is developed, which systematically integrates simulations.

Communication in a pandemic is difficult and complex. It is characterized by volatile situations associated with a high degree of uncertainty and, in some cases, social divergence in groups and societies. Orientation is expected, by politicians and individuals, from science. However, sciences are only fulfilling the expectations to a limited extent. We demonstrate that there are severe weaknesses in holistic and interdisciplinary communication in the pandemic and show that established tools from management are neglected and overlooked.We then analyze the specific needs of scientific reasoning in pandemic situations such as •a rational approach integrating both estimates and explicit evidence;•expressing and quantifying uncertainty; •considering interdisciplinary aspects in advice and decision making;•the ability to deal with ethical aspects;•simple updates with new findings and evidence.In a third step we compare from literature and own experience existing methods from management science for their suitability against those needs. We find that many of the interdisciplinary tools are deterministic, like Multi Criteria Analyses, and do not support uncertainty. The frequently adopted linear computation of utility values leads to ethical issues. Foresight methods like Delphi or Scenario methods deal with uncertainty and subjectivity. But they are not designed to integrate strong evidence. Strategic planning tools like roadmaps are comprehensible but disappoint in volatile situations. Probabilistic decision making with expected utilities is too complex and suffers from missing data. Heuristics at the other hand are simple but do not allow for comprehensive reasoning. We then argue in a fourth step to use probability in communication and to apply it to decision making in the pandemic. We propose a simple one-step method with a calculus based on Bayes’ theorem and calculate the probabilities of alternative courses of action being the best un der given conditios. With examples we show how arguments from various scientific disciplines can be integrated in decision making and adjusted as new evidence appears. Furthermore, we provide a role model and show by examples how scientists, scientific consultants and decision makers can cooperate and communicate using the method.We conclude that the method fulfils the identified needs to a high degree and is worth to be further developed. We show its epistemic and scientific limitations and give an outlook how likelihood functions may be used to replace negotiated likelihoods by parametric and model based values.

Many companies and regions in Europe consider innovation to be their key competitive advantage. To enable these actors to successfully incorporate innovation into their strategic planning, this article seeks to scope dynamics of industrial innovation by analyzing historical developments and forecasting future trends. The insight into historical developments provides the basis for learnings and a d...

In times of digital transformation and often-disruptive markets, companies have to continuously optimize their existing business models and at the same time promote new products and services as well as organizational structures and working processes. Human creativity in combination with artificial intelligence and cognitive systems are key enablers for organizations to optimize their business and better predict and control their innovation processes. Optimized symbiotic interaction between humans and machines needs a methodological approach in order to design and evaluate enhanced innovation processes for generating new ideas and implementing innovative hybrid working scenarios. In this paper, the authors present key elements for the optimization of innovation processes based on established creativity techniques and potentials of cognitive systems.

The digitization of industrial value chain, so-called "Industry 4.0", is one of the most important economic and social development in the last years. It allows the high-wage countries, for example Germany, to maintain their business responsiveness and competitiveness. While research and development units are organizationally, personally and methodically aligned for innovation projects development, the development and introduction of innovations in a manufacturing environment face a great challenge. The process is often unstructured and has an unclear target. Especially the procedure to introduce human-centered Industry 4.0 applications focuses not only on a technical side of the question. To solve this problem, a socio-technical approach should be taken under consideration. Furthermore, employees have to be involved in the design and implementation phase. This paper presents a new approach to establish a method to introduce human-centered cyber-physical use-cases to manufacturing. After the definition of procedure models, successful and less successful projects are analyzed. This is the base to define requirements for this presented approach. Therefore a modular innovation framework is developed, which includes a systematic procedure with project phases, results of each phase, a toolkit with methods and checklists. Additionally, work functions and role models are examined. Special emphasis is given to employee work engagement. At last, the usability of this procedure is discussed.

In times of digital transformation, enterprises are facing great challenges in terms of management and work organization. In particular, the rapid progress in the field of artificial intelligence and cognitive systems requires a rethinking of by whom and how work activities will carried out in the future. The automation of routine processes and intelligent algorithms in some cases even allow new approaches and perspectives. For not only machines or intelligent algorithms are going to execute tasks, new forms of human-machine interaction represent valuable enablers of positioning the central role of humans. Therefore, it does not only require technological but also cultural development. By using new technologies and methods, tasks and jobs will change in the future: qualification requirements will transform, previous jobs will be lost and new job profiles will emerge. The demand for highly qualified staff will greatly increase. Especially digital competence will be in more demand than ever as will be the ability to control complexity and human creativity. Nevertheless, how to get there and how to create the missing socio-technological link? In this paper, the authors present selected currently available technological solutions in the field of artificial intelligence leading to new forms of human-machine interaction. In addition, the authors point out future demands on the skills of both employees and managers as well as appropriate training opportunities.

A "worker journey" (as already known from the customer journey) was created here. In this journey the daily routine of intralogistics activities are presented under the influence of digitalisation technologies. The changes that took place and their plausibility were evaluated using a two-stage Delphi study. Respondents were experts from companies in German industry who are already actively involved in the topic of Industry 4.0, not only in the context of intralogistics. Result of this reflection and evaluation is a innovative picture of the work of this profession in the future. The results go even further and gives discussion approach for organizationally interesting questions such as "How is the number of employed people changing?", "How likely is automation in this work field?", "What qualification measures are necessary?" and "What opportunities do skilled and unskilled employees have?".

Background: The paper presents recent results of the ongoing collaborative research project "MyCPS" (Human-centered development and application of Cyber-Physical Systems). Methods: Within the scope of the project, 14 partners, amongst seven industrial partners, develop methods and tools to set-up applications of intelligent digitalization and automation of industrial processes. Results: Within the paper they are over 385 use cases evaluated according to comparative criteria. Furthermore, use cases were classified due to their development stage of industry 4.0 goals and promises. The three levels 'information', 'interaction' and 'intelligence' are used to differentiate applications according to their degree of maturity in industry 4.0 terms. Conclusion: In MyCPS, special emphasis is the role of the workforce and the interactions of the technology-led use cases with employees. Thereby, the analysis helps enterprises and researchers to self-assess key-aspects of the development of industry 4.0 use cases.