The user experience of our daily interactions is increasingly shaped with the aid of AI, mostly as the output of recommendation engines. However, it is less common to present users with possibilities to navigate or adapt such output. In this paper we argue that adding such algorithmic controls can be a potent strategy to create explainable AI and to aid users in building adequate mental models of the system. We describe our efforts to create a pattern library for algorithmic controls: the algorithmic affordances pattern library. The library can aid in bridging research efforts to explore and evaluate algorithmic controls and emerging practices in commercial applications, therewith scaffolding a more evidence-based adoption of algorithmic controls in industry. A first version of the library suggested four distinct categories of algorithmic controls: feeding the algorithm, tuning algorithmic parameters, activating recommendation contexts, and navigating the recommendation space. In this paper we discuss these and reflect on how each of them could aid explainability. Based on this reflection, we unfold a sketch for a future research agenda. The paper also serves as an open invitation to the XAI community to strengthen our approach with things we missed so far.
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Informal learning spaces create opportunities for children and youth to develop their talents and to experience new social roles. In recent years, several public libraries in the Netherlands have established makerspaces to empower youth by facilitating the development of their digital skills in conjunction with their creativity. The Amsterdam Public Library created a network of makerspaces (Maakplaats021) and provided training for the makerspace-coaches. These coaches – former librarians or other professionals – have a central role in the makerspace and fulfill several functions. This contribution describes informal learning of children in these makerspaces and distills critical features that enforce learning through the lens of children aged 8–12 and their makerspace-coaches.
There is an increasing attention for youth social work professionals to collaborate with volunteers, parents, and other professionals. Collaboration can contribute to positive outcomes for youth. The present study contributes to understanding differences in the extent to which youth social work professionals collaborate with volunteers, parents, and other professionals. The survey was conducted with Dutch professionals working in youth care (n = 112), education (n = 67), and youth work (n = 89). Index for Interdisciplinary Collaboration was used to assess interdependence in and reflection on the collaboration process. Significant differences were found in the extent to which professionals working in different fields experience interdependence and reflection on the collaboration process with different partners. Future researchers should be aware that the degree to which professionals collaborate with others might depend on the context, work field, and the collaboration partner. Youth social work professionals and local governments can use this study to identify strong and weak collaborative partnerships in order to better organize collaboration between different partners with the final aim of improving support of young people.
