Computational systems and objects are becoming increasingly closely integrated with our daily activities. Ubiquitous and pervasive computing first identified the emerging challenges of studying technology used on-themove and in widely varied contexts. With IoT, previously sporadic experiences are interconnected across time and space in numerous and complex ways. This increasing complexity has multiplied the challenges facing those who study human experience to inform design. This paper describes the results of a study that used a chatbot or 'Ethnobot' to gather ethnographic data, and considers the opportunities and challenges in collecting this data in the absence of a human ethnographer. This study involved 13 participants gathering information about their experiences at the Royal Highland Show. We demonstrate the effectiveness of the Ethnobot in this setting, discuss the benefits and drawbacks of chatbots as a tool for ethnographic data collection, and conclude with recommendations for the design of chatbots for this purpose.
1 This paper introduces the methodological exploration of a design led approach towards utilizing human-food-interactions in teaching art appreciation. In workshops participants express emotional and cognitive responses towards works of art, then interpret and re-imagine those responses into the creation of representational-food dishes. From this we deconstruct and analyze the multi-sensory and multi-modal experience of food in its complex network of taste, colour, texture, and emotions.
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