Matthew Tobias Harris’s research while affiliated with Queen Mary University of London and other places

Critical but often overlooked research questions in artificial intelligence (AI) applied to music involve the impact of the results for music. How and to what extent does such research contribute to the domain of music? How are the resulting models useful for music practitioners? In this article, we describe how we are addressing such questions by engaging composers, musicians, and audiences with our research. We first describe two websites we have created that make our AI models accessible to a wide audience. We then describe a professionally recorded album that we released to expert reviewers to gauge the plausibility of AI-generated material. Finally, we describe the use of our AI models as tools for co-creation. Evaluating AI research and music models in these ways illuminate their impact on music making in a range of styles and practices.

Drawing as a form of analytical inscription can provide researchers with highly flexible methods for exploring embodied interaction. Graphical techniques can combine spatial layouts, trajectories of action and anatomical detail, as well as rich descriptions of movement and temporal effects. This paper introduces some of the possibilities and challenges of adapting graphical techniques from life drawing and still life for interaction research. We demonstrate how many of these techniques are used in interaction research by illustrating the postural configurations and movements of participants in a ballet class. We then discuss a prototype software tool that is being developed to support interaction analysis specifically in the context of a collaborative data analysis session.

How does talk work, and can we engage the public in a dialogue about the scientific study of talk? This article presents a history, critical evaluation and empirical illustration of the public science of talk. We chart the public ethos of conversation analysis that treats talk as an inherently public phenomenon and its transcribed recordings as public data. We examine the inherent contradictions that conversation analysis is simultaneously obscure yet highly cited; it studies an object that people understand intuitively, yet routinely produces counter-intuitive findings about talk. We describe a novel methodology for engaging the public in a science exhibition event and show how our ‘conversational rollercoaster’ used live recording, transcription and public-led analysis to address the challenge of demonstrating how talk can become an informative object of scientific research. We conclude by encouraging researchers not only to engage in a public dialogue but also to find ways to actively engage people in taking a scientific approach to talk as a pervasive, structural feature of their everyday lives.