tl;dr – AI and the acceleration of research communication

AI is forecast to become increasingly central to many aspects of life and work. The same trends can also be detected in research. Drawing on a recent study of expert perceptions of AI uses in research and taking the recently launched tl;dr tool as a salient example, Jennifer Chubb and David Beer discuss AI’s emerging role and its potential to act as a narrator and bridging tool to communicate research to different audiences

We need better AI imagery for better science communication

Current images of AI – widely used and available in stock libraries – are dominated by tropes such as white humanoid robots, blue backgrounds, glowing brains and science fiction imagery. Research into narratives as forms of sense-making AI has shown that these can impede the public understanding of AI, mask human agency, and reinforce damaging stereotypes. Dr Jenn Chubb and AI policy researcher Raziye Buse Çetin, appointed advisors to the Better Images of AI project, make the case to imagine more helpful visual representations of AI to improve science communication

Boundaries Between Research Ethics and Ethical Research Use in Artificial Intelligence Health Research

The governance of ethically acceptable research in higher education institutions has been under scrutiny over the past half a century. Concomitantly, recently, decision makers have required researchers to acknowledge the societal impact of their research, as well as anticipate and respond to ethical dimensions of this societal impact through responsible research and innovation principles. Using artificial intelligence population health research in the United Kingdom and Canada as a case study, we combine a mapping study of journal publications with 18 interviews with researchers to explore how the ethical dimensions associated with this societal impact are incorporated into research agendas. Researchers separated the ethical responsibility of their research with its societal impact. We discuss the implications for both researchers and actors across the Ethics Ecosystem

Instrumentalism and Epistemic Responsibility:Researchers and the Impact Agenda in the UK and Australia

The management and measurement of the non-academic impact of research has emerged as a strong and consistent theme within the higher education research environment in the UK. This has been mirrored in other national contexts, particularly in Australia, where research impact policy is evolving at a similar pace. The impact agenda - a move to assess the ways in which investment in academic research delivers measurable socio-economic benefit - has sparked discussion and in some instances controversy, amongst the academic community and beyond. Critics argue that it is symptomatic of the marketisation of knowledge and that it threatens traditional academic norms and ideals, whilst its advocates welcome the opportunity to increase the visibility of research beyond academia. In this thesis, I explore the response of academics in the UK and Australia to impact in these two respective national contexts. Adopting a case study approach and using interviews with mid-senior career academics (n=51), I drew my findings both inductively and deductively using thematic analysis. The thesis contributes to the relatively small but emerging body of scholarly research into academics’ attitudes towards research impact. Analysis indicates that considerations of research impact have profound effects on academic behaviour and identity. Increased focus on justifying the value of research affects how academics feel about their roles and responsibilities. An association with knowledge and its utility dominates academic perceptions and is seen to be in direct tension with a strong sense of epistemic responsibility. Whilst responsibility emerges as a key motivation for engagement with the impact agenda, the pressures of an increasingly competitive research environment can be seen to negatively affect the integrity of academics. These effects span disciplinary and national boundaries and reveal two distinctive cultures where affinities between academics whose research has a less instrumental nature, appear to contrast with views expressed predominantly from those with an instrumental focus. Analysis reveals complex diversity across the disciplines in how impact is understood and contextualised, indicative of a new clustering of academic disciplines, distinct from the traditional divide between arts and sciences yet reminiscent of a pure/applied distinction. Despite a persistent theme of resistance, it is perhaps in the acknowledgement and understanding of the diversity in disciplinary responses that the potential for the impact agenda to bring enhanced intellectual credibility to applied research can be explored, providing greater motivation for the disciplines to work together for maximum impact. These findings have significant implications for national governments, policy makers and funders, as well as for leaders of academic institutions and of course, for the academic community

Epistemic corruption and the research impact agenda

Contemporary epistemologists of education have raised concerns about the distorting effects of some of the processes and structures of contemporary academia on the epistemic practice and character of academic researchers. Such concerns have been articulated using the concept of epistemic corruption. In this article, we lend credibility to these theoretically motivated concerns using the example of the research impact agenda during the period 2012–2014. Interview data from UK and Australian academics confirm that the impact agenda system, at its inception, facilitated the development and exercise of epistemic vices. As well as vindicating theoretically motivated claims about epistemic corruption, inclusion of empirical methods and material can help us put the concept to work in ongoing critical scrutiny of evolving forms of the research impact agenda

Reverse Mathematics, Computability, and Partitions of Trees

We examine the reverse mathematics and computability theory of a form of Ramsey’s theorem in which the linear n-tuples of a binary tree are colored