An increasingly popular solution to the anti-scientific climate rising on social media platforms has been the appeal to more critical thinking from the user's side. In this paper, we zoom in on the ideal of critical thinking and unpack it in order to see, specifically, whether it can provide enough epistemic agency so that users endowed with it can break free from enclosed communities on social media (so called epistemic bubbles). We criticise some assumptions embedded in the ideal of critical (...) thinking online and, instead, we propose that a better way to understand the virtuous behaviour at hand is as critical engagement, namely a mutual cultivation of critical skills among the members of an epistemic bubble. This mutual cultivation allows members within an epistemic bubble (in contrast, as we will show, with the authority-based models of epistemic echo chambers) to become more autonomous critical thinkers by cultivating self-trust. We use the model of relational autonomy as well as resources from work on epistemic self-trust and epistemic interdependence to develop an explanatory framework, which in turn may ground rules for identifying and creating virtuous epistemic bubbles within the environments of social media platforms. (shrink)

This volume celebrates the various facets of Alan Turing (1912–1954), the British mathematician and computing pioneer, widely considered as the father of computer science. It is aimed at the general reader, with additional notes and references for those who wish to explore the life and work of Turing more deeply. -/- The book is divided into eight parts, covering different aspects of Turing’s life and work. -/- Part I presents various biographical aspects of Turing, some from a personal point of (...) view. -/- Part II presents Turing’s universal machine (now known as a Turing machine), which provides a theoretical framework for reasoning about computation. His 1936 paper on this subject is widely seen as providing the starting point for the field of theoretical computer science. -/- Part III presents Turing’s working on codebreaking during World War II. While the War was a disastrous interlude for many, for Turing it provided a nationally important outlet for his creative genius. It is not an overstatement to say that without Turing, the War would probably have lasted longer, and may even have been lost by the Allies. The sensitive nature of Turning’s wartime work meant that much of this has been revealed only relatively recently. -/- Part IV presents Turing’s post-War work on computing, both at the National Physical Laboratory and at the University of Manchester. He made contributions to both hardware design, through the ACE computer at the NPL, and software, especially at Manchester. Part V covers Turing’s contribution to machine intelligence (now known as Artificial Intelligence or AI). Although Turing did not coin the term, he can be considered a founder of this field which is still active today, authoring a seminal paper in 1950. -/- Part VI covers morphogenesis, Turing’s last major scientific contribution, on the generation of seemingly random patterns in biology and on the mathematics behind such patterns. Interest in this area has increased rapidly in recent times in the field of bioinformatics, with Turing’s 1952 paper on this subject being frequently cited. -/- Part VII presents some of Turing’s mathematical influences and achievements. Turing was remarkably free of external influences, with few co-authors – Max Newman was an exception and acted as a mathematical mentor in both Cambridge and Manchester. -/- Part VIII considers Turing in a wider context, including his influence and legacy to science and in the public consciousness. -/- Reflecting Turing’s wide influence, the book includes contributions by authors from a wide variety of backgrounds. Contemporaries provide reminiscences, while there are perspectives by philosophers, mathematicians, computer scientists, historians of science, and museum curators. Some of the contributors gave presentations at Turing Centenary meetings in 2012 in Bletchley Park, King’s College Cambridge, and Oxford University, and several of the chapters in this volume are based on those presentations – some through transcription of the original talks, especially for Turing’s contemporaries, now aged in their 90s. Sadly, some contributors died before the publication of this book, hence its dedication to them. -/- For those interested in personal recollections, Chapters 2, 3, 11, 12, 16, 17, and 36 will be of interest. For philosophical aspects of Turing’s work, see Chapters 6, 7, 26–31, and 41. Mathematical perspectives can be found in Chapters 35 and 37–39. Historical perspectives can be found in Chapters 4, 8, 9, 10, 13–15, 18, 19, 21–25, 34, and 40. With respect to Turing’s body of work, the treatment in Parts II–VI is broadly chronological. We have attempted to be comprehensive with respect to all the important aspects of Turing’s achievements, and the book can be read cover to cover, or the chapters can be tackled individually if desired. There are cross-references between chapters where appropriate, and some chapters will inevitably overlap. -/- We hope that you enjoy this volume as part of your library and that you will dip into it whenever you wish to enter the multifaceted world of Alan Turing. (shrink)

Famous examples of conceivability arguments include (i) Descartes’ argument for mind-body dualism, (ii) Kripke's ‘modal argument’ against psychophysical identity theory, (iii) Chalmers’ ‘zombie argument’ against materialism, and (iv) modal versions of the ontological argument for theism. In this paper, we show that for any such conceivability argument, C, there is a corresponding ‘mirror argument’, M. M is deductively valid and has a conclusion that contradicts C's conclusion. Hence, a proponent of C—henceforth, a ‘conceivabilist’—can be warranted in holding that C's premises (...) are conjointly true only if she can find fault with one of M's premises. But M's premises are modelled on a pair of C's premises. The same reasoning that supports the latter supports the former. For this reason, a conceivabilist can repudiate M's premises only on pain of severely undermining C's premises. We conclude on this basis that all conceivability arguments, including each of (i)–(iv), are fallacious. (shrink)

While resilience is a major concept in development, climate adaptation, and related domains, many doubts remain about how to interpret this term, its relationship with closely overlapping terms, or its normativity. One major view is that, while resilience originally was a descriptive concept denoting some adaptive property of ecosystems, subsequent applications to social contexts distorted its meaning and purpose by framing it as a transformative and normative quality. This article advances an alternative philosophical account based on the scrutiny of C.S. (...) Holling’s original work on resilience. We show that resilience had a central role among Holling’s proposals for reforming environmental science and management, and that Holling framed resilience as an ecosystem’s capacity of absorbing change and exploiting it for adapting or evolving, but also as the social ability of maintaining and opportunistically exploiting that natural capacity. Resilience therefore appears as a transformative social-ecological property that is normative in three ways: as an intrinsic ecological value, as a virtue of organizations or management styles, and as a virtuous understanding of human–nature relations. This interpretation accounts for the practical relevance of resilience, clarifies the relations between resilience and related terms, and is a firm ground for further normative work on resilience. (shrink)

This chapter looks closely at the use of resilience as a value in pandemic discourses, and particularly at how it reflects the moral complexity of the situation the pandemic presents: an extended crisis where shocks and stressors interact and have an uncertain end. We review key aspects of how resilience has been conceptualised, generally speaking, focusing on its normative implications. Insofar as resilience is suggested as a goal, or used to evaluate individuals, groups and systems, the rhetorical use of resilience (...) in the pandemic has moral implications that we unpack. Asking questions such as resilience to what, of what, and for whom, drives our analysis of the multiple scales at which morally relevant factors must be considered, in terms of distance and certainty, and across space and over time. Further, we highlight the importance of particularly challenging, intersecting scales both within and beyond the pandemic, such as the interaction between other- and self-regarding concerns and the tension between transformation and conservation, as we consider when to take up opportunities for improving ourselves, our society and our systems, in times of extended crises and radical change. Given that a ‘return to normal’ is neither universally desirable nor likely, we recommend in this chapter ways to address resilience as a value that can shape approaches to policy and behaviour while also being explicit about the normative—evaluative and also prescriptive—implications of its use. (shrink)

Serendipity is fundamental to science. This quirky and intriguing phenomenon permeates across scientific disciplines, including the medical sciences, psychological sciences, management and organizational sciences, innovation science, philosophy and library and information sciences. Why is it so ubiquitous? Because of what it facilitates and catalyzes: scientific discoveries from velcro to Viagra, innovation of all forms, unexpected encounters of useful information, novel and important ideas, and deep reflection on how we, as individuals, organizations, communities and societies can take leaps forwards by seizing (...) unexpected opportunities and ‘making our own luck.’. (shrink)

Australia is a leading AI nation with strong allies and partnerships. Australia has prioritised the development of robotics, AI, and autonomous systems to develop sovereign capability for the military. Australia commits to Article 36 reviews of all new means and method of warfare to ensure weapons and weapons systems are operated within acceptable systems of control. Additionally, Australia has undergone significant reviews of the risks of AI to human rights and within intelligence organisations and has committed to producing ethics guidelines (...) and frameworks in Security and Defence. Australia is committed to OECD’s values-based principles for the responsible stewardship of trustworthy AI as well as adopting a set of National AI ethics principles. While Australia has not adopted an AI governance framework specifically for Defence; Defence Science has published ‘A Method for Ethical AI in Defence’ (MEAID) technical report which includes a framework and pragmatic tools for managing ethical and legal risks for military applications of AI. (shrink)