Utilizing systems development methods – a conceptual framework

There are not many frameworks of method utilization or use in organization based on empirical studies nor is there a common understanding of these issues. This paper investigates how systems development methods are utilized in practice and proposes a framework to conceive method utilization. The explanatory value of the framework is illustrated by providing an analysis of a case study. The framework highlights several issues of method utilization based on a three years long field study. The framework has two dimensions. The first dimension covers three levels in organizations at which methods can be utilized. They are the organizational level, the project level, and the individual level. The second dimension covers three aspect of utilization of the method that can take place at each level. The three aspects are adoption, adaptation, and use. Thereby the framework provides nine perspectives on method utilization that allow us to understand and guide method utilization in a broader sense than we have found in the literature, which primarily deals with a subset of the nine perspectives. Furthermore, the paper introduces a distinction between method use and method utilization to emphasize a broad view on method utilization. Method utilization includes adoption, adaptation, and use at different levels in development organizations. Method use is strictly defined as the use of methods for systems development

Scaling Participation -- What Does the Concept of Managed Communities Offer for Participatory Design?

This paper investigates mechanisms for scaling participation in participatory design (PD). Specifically, the paper focuses on managed communities, one strategy of generification work. We first give a brief introduction on the issue of scaling in PD, followed by exploring the strategy of managed communities in PD. This exploration is underlined by an ongoing case study in the healthcare sector, and we propose solutions to observed challenges. The paper ends with a critical reflection on the possibilities managed communities offer for PD. Managed communities have much to offer beyond mere generification work for large-scale information systems, but we need to pay attention to core PD values that are in danger of being sidelined in the process

Ground Truth Or Dare: Factors Affecting The Creation Of Medical Datasets For Training AI

One of the core goals of responsible AI development is ensuring high-quality training datasets. Many researchers have pointed to the importance of the annotation step in the creation of high-quality data, but less attention has been paid to the work that enables data annotation. We define this work as the design of ground truth schema and explore the challenges involved in the creation of datasets in the medical domain even before any annotations are made. Based on extensive work in three health-tech organisations, we describe five external and internal factors that condition medical dataset creation processes. Three external factors include regulatory constraints, the context of creation and use, and commercial and operational pressures. These factors condition medical data collection and shape the ground truth schema design. Two internal factors include epistemic differences and limits of labelling. These directly shape the design of the ground truth schema. Discussions of what constitutes high-quality data need to pay attention to the factors that shape and constrain what is possible to be created, to ensure responsible AI design