Over the last decade, design for behaviour change has become increasingly recognised as a strategy for enabling social change. Despite this, we are far from understanding its implementation, especially through the private and public sectors. This study has surveyed private and public sector stakeholders with regard to their current knowledge of, and approach to, design for behaviour change. The aim was to identify the challenges for professional stakeholders in understanding, accessing and implementing design for behaviour change. Underpinned by a literature review of design for behaviour change theories and approaches, an online survey and two focus groups with private and public sector stakeholders were conducted with particular focus on small and medium size enterprises (SMEs). The results identified that there is a significant disconnect between available theoretical knowledge of design for behaviour change and its practical implementation. Reasons for this include a lack of awareness and common language, of evidence based examples, and of evaluation methods and inter-sector collaborations. In response, a set of recommendations has been developed to propose ways forward for the wider understanding and application of design for behaviour change.@en

What if things had a voice? What if we could talk directly to things instead of using a mediating voice interface such as an Alexa or a Google Assistant? In this paper, we share our insights from talking to a pair of boots, a tampon, a perfume bottle, and toilet paper among other everyday things to explore their conversational capabilities. We conducted Thing Interviews using a more-than-human design approach to discover a thing’s perspectives, worldviews and its relations to other humans and nonhumans. Based on our analysis of the speculative conversations, we identified some themes characterizing the emergent qualities of people’s relationships with everyday things. We believe the themes presented in the paper may inspire future research on designing everyday things with conversational capabilities at home. @en

In this paper, we explore the use of metaphors for people working with artificial intelligence, in particular those that support designers in thinking about the creation of AI systems. Metaphors both illuminate and hide, simplifying and connecting to existing knowledge, centring particular ideas, marginalising others, and shaping fields of practice. The practices of machine learning and artificial intelligence draw heavily on metaphors, whether black boxes, or the idea of learn-ing and training, but at the edges of the field, as design engages with computational practices, it is not always apparent which terms are used metaphorically, and which associations can be safely drawn on. In this paper, we look at some of the ways metaphors are deployed around machine learning and ask about where they might lead us astray. We then develop some qualities of useful metaphors, and finally explore a small collection of helpful metaphors and practices that illuminate different aspects of machine learning in a way that can support design thinking.@en