Collaborative music-making with digital audio workstations:the ‘nth member’ as a heuristic device for understanding the role of technologies in audio composition

This article examines amateur music-making using a digital audio workstation (DAW), showing how audio and software are used as resources for creating compositions. The article has two aims. Firstly, to depict how digital music-making is formed from routine interactional techniques. Secondly, to probe how researchers might account for such multi-modal activity through a heuristic device: the ‘nth member’. Whereas sociology has typically been concerned with the cultural facets of how music is made and consumed, we explore the material practices of collaborative song creation utilising conversation analytic techniques – ‘turn-taking’ and ‘next-selection’ – to capture two key interactional moments

What would Wittgenstein say about social media?

Much of the excitement in social media analytics revolves around, a) capturing large-scale collections of naturally-occurring talk, b) repurposing them as data, and, c) finding ways to speak sociologically about them. Researchers have raised concerns over the use of social media data in research (for example, boyd and Crawford, 2012; Housley et al, 2014; Tinati et al, 2014), exploring the ontological and epistemological grounding of the emerging field. We contribute to this debate by drawing on Wittgensteinian philosophy to elucidate hitherto neglected aspects; namely that it is not just social scientists who are in the business of analysing social media, but users themselves. We explore how mainstream social media analytics research (1) overinflates the importance of sociological theories, concepts and methodologies (which do not typically feature in the accounts of social media users), (2) downplays the extent to which social media platforms already exhibit order prior to any sociological accounting of them, and, (3) thereby produces findings which explain social scientific perspectives rather than the phenomena themselves. We reformulate the ontological and epistemological basis of social media analytics research from a Wittgensteinian perspective concerned with what it makes sense to say about social media, as members of society and as researchers studying those members. Such a project aims to explore social media users’ language as a practice embedded within the context of social life and online communication. This reflects the everyday use of language as an evolving toolkit for undertaking social interaction, pointing towards an alternative conception of social media analytics

The New Ghosts in the Machine: ‘Pragmatist’ AI and the Conceptual Perils of Anthropomorphic Description

Algorithms are becoming interwoven with increasingly many aspects of our affairs. That process of interweaving has brought with it a language laden with anthropomorphic descriptions of the technologies involved, which variously hint at ‘human-esque’ or ‘conscious-like’ activity occurring within or behind their operations. Indeed, the term ‘Artificial Intelligence’ (AI) seems to refer to a quality that is thought to be largely human; namely, intelligence. However, while anthropomorphic descriptions may be useful or harmless, when taken at face value they generate a false picture of algorithms as well as of our own thinking and reasoning practices by treating them as analogues of one another rather than as distinct. Focusing on the algorithm, and what it is misleadingly said to be and to be like, in this article we outline three “perspicuous representations” (Wittgenstein 1953: §122) of AI in specific contexts. Drawing on Wes Sharrock’s ethnomethodological and Wittgensteinian work, our aim is to demonstrate that by attending to the particular, occasioned and locally accountable, not to say highly specified, usages of language that accompany the ‘New AI’ in particular, we can avoid being haunted by the new task performing ghosts currently being discursively conjured up in our algorithmic machines

Thinking Like a Machine

As part of ongoing research bridging ethnomethodology and computer science, in this article we offer an alternate reading of Alan Turing’s 1936 paper, “On Computable Numbers”. Following through Turing’s machinic respecification of computation, we hope to contribute to a deflationary position on AI by showing that the activities attributed to AIs are achieved in the course of methodic hands-on work with computational systems and not in isolation by them. Turing’s major innovation was a demonstration that mathematical and logical operations could be broken down into elementary, mechanically executable operations, devoid of intellectual content. Drawing out lessons from a re-enactment of Turing’s methods as a means of reflecting on contemporary artificial intelligence (AI), including the way those methods disappear into the technology, we will suggest the interesting question raised in “On Computable Numbers” is less about the possibilities of designing machines that “can think” (cf. Turing, 1950), but the practical work we do, and which is made possible, when we ourselves set out to think like machines.</jats:p