Sensing & Sensibility
As digital transformation continues, everyday technologies will fundamentally change: they will become proactive, autonomous and more and more opaque for humans. Taking production management as an example, this research project will examine how a cooperation between humans and algorithmic agents can and ought to be designed. Potential designs will be examined with regard to three potentially competing objectives: performance, satisfaction and accountability. In general, we will create examples of different types of human-algorithm-cooperation and explore their impact on the efficiency and effectiveness of the result, the work satisfaction and wellbeing of the humans involved and societal and regulatory implications. While production management serves as an example, the project will address broader issues of how to design human-algorithm-cooperation between the priorities of industry, workers, and society at large.
Objective
This project is divided into three main research fields. These research fields correspond with three models we want to develop for the design of human and non-human cooperation. Parallel to the development of the individual models, interdependencies are revealed and cross-sectional questions are answered. The aim is to evaluate all three models in a common setting (explorative study). The main concern here is to consider the models not as separate from each other, but as an integral part of the other models.
Satisfaction model
Human algorithm cooperation must not only be optimized with regard to performance but also in terms of providing meaningful work to all humans involved. So far, automation fundamentally impacted work setting, leading to profound changes in the emotional and cognitive responses to work. For example, classic automation forced people into supervisory control positions, where work satisfaction is no longer created by participating in the production itself, but by solving complex problems arising from failures of automation Instead of following the automation's notion of completely substituting the human in the process (which mostly fails), the leading model must be to determine meaningful forms of human algorithm cooperation. The overarching question is :How should human algorithm cooperation be designed to lead to fulfilling and meaningful work setting?
The main goal of this research field is to create a better understanding of the experiential costs and potential strategies of modeling interaction with algorithmic agents along the line of human algorithm cooperation. Since algorithms may become an inevitable part of work environment, the impact of their particular embedding into work must not only be scrutinized in terms of functional or efficiency gains, but also in terms of positively or negatively impacting job satisfaction and wellbeing through its use.
Board
Faculty IV: Chair for International Production Engineering and Management (IPEM)
Faculty I: Chair for Digital Media and Methods (DMM)
Faculty II: Chair for Ubiquitous Design (UD)
