Veränderte Kompetenzanforderungen an Mitarbeitende infolge zunehmender Automatisierung – Eine Arbeitsfeldbetrachtung

The Job Perception Inventory: considering human factors and needs in the design of human-AI work

Introduction

Artificial intelligence (AI) is seen as a driver of change, especially in the context of business, due to its progressive development and increasing connectivity in operational practice. Although it changes businesses and organizations vastly, the impact of AI implementation on human workers with their needs, skills, and job identity is less considered in the development and implementation process. Focusing on humans, however, enables unlocking synergies as well as desirable individual and organizational outcomes.

Methods

The objective of the present study is (a) to develop a survey-based inventory from the literature on work research and b) a first validation with employees encountering an AI application. The Job Perception Inventory (JOPI) functions as a work-analytical tool to support the human-centered implementation and application of intelligent technologies. It is composed of established and self-developed scales, measuring four sections of work characteristics, job identity, perception of the workplace, and the evaluation of the introduced AI.

Results

Overall, the results from the first study from a series of studies presented in this article indicate a coherent survey inventory with reliable scales that can now be used for AI implementation projects.

Discussion

Finally, the need and relevance of the JOPI are discussed against the background of the manufacturing industry.

I vs. robot: Sociodigital self-comparisons in hybrid teams from a theoretical, empirical, and practical perspective

This article in the journal Gruppe. Interaktion. Organisation. (GIO) introduces sociodigital self-comparisons (SDSC) as individual evaluations of own abilities in comparison to the knowledge and skills of a cooperating digital actor in a group. SDSC provide a complementary perspective for the acceptance and evaluation of human-robot interaction (HRI). As social robots enter the workplace, in addition to human-human comparisons, digital actors also become objects of comparisons (i.e., I vs. robot). To date, SDSC have not been systematically reflected in HRI. Therefore, we introduce SDSC from a theoretical perspective and reflect its significance in social robot applications. First, we conceptualize SDSC based on psychological theories and research on social comparison. Second, we illustrate the concept of SDSC for HRI using empirical data from 80 hybrid teams (two human actors and one autonomous agent) who worked together in an interdependent computer-simulated team task. SDSC in favor of the autonomous agent corresponded to functional (e.g., robot trust, or team efficacy) and dysfunctional (e.g., job threat) team-relevant variables, highlighting the two-sidedness of SDSC in hybrid teams. Third, we outline the (practical) potential of SDSC for social robots in the field and the lab.

Automation as an equal team player for humans? - A view into the field and implications for research and practice

The practical reality and feasibility of Human-Autonomy Teaming (HAT) are analyzed from an experts' point of view, considering current possibilities of various fields. We aim to find out whether the topics discussed scientifically are also practically relevant, to identify requirements for successful HAT, and to derive further research needs. Intensive guideline-based interviews with 28 experts from different industries are conducted and compared to the results of our literature review. The topics discussed scientifically are also practically relevant. Today's technology is far from being able to meet the practical requirements for successful HAT, as postulated in the literature. Contrary to the Human-Automation Interaction, the concept of HAT is hardly applied in the field. Identified key aspects for successful HAT are converted into a model. Future research needs with practical impact exist especially in the area of heterarchy, system knowledge, anticipation of mental states, and consideration of human needs and emotions.