Presentation @ ECIS2021 about CV-based Hybrid Intelligence

We are happy to announce that our recent conference paper got accepted for presentation at the 29th European Conference on Information Systems (ECIS 2021).

Together with Jannis Walk, Kai Heinrich, Michael Vössing, and Niklas Kühl, we were looking into a collection of computer vision (CV) projects from industry to accumulate prescriptive knowledge about the design of CV-based hybrid intelligence systems.

If you are already interested in our results before the official presentation at ECIS 2021, you can find the paper as a preprint on ResearchGate and arXiv.


Computer vision (CV) techniques try to mimic human capabilities of visual perception to support labor-intensive and time-consuming tasks like the recognition and localization of critical objects. Nowadays, CV increasingly relies on artificial intelligence (AI) to automatically extract useful information from images that can be utilized for decision support and business process automation. However, the focus of extant research is often exclusively on technical aspects when designing AI-based CV systems while neglecting socio-technical facets, such as trust, control, and autonomy. For this purpose, we consider the design of such systems from a hybrid intelligence (HI) perspective and aim to derive prescriptive design knowledge for CV-based HI systems. We apply a reflective, practice-inspired design science approach and accumulate design knowledge from six comprehensive CV projects. As a result, we identify four design-related mechanisms (i.e., automation, signaling, modification, and collaboration) that inform our derived meta-requirements and design principles. This can serve as a basis for further socio-technical research on CV-based HI systems.