This article, taking a social semiotic approach, analyses two pieces of music written, shared and exalted by two pre-1945 European fascist movements – the German NSDAP and the British Union of Fascists. These movements, both political and cultural, employed mythologies of unity, common identity and purpose in order to elide the realities of social distinction and political–economic inequalities between bourgeois and proletarian groups in capitalist societies. Visually and inter-personally, the fascist cultural project communicated a machine-like certainty about a vision for (...) a new society based on discipline, conformity and the might of the nation. In this article, we are interested in the ways that these very same discourses are also communicated through sound and music in two songs: The Horst Wessel Lied and the BUF marching song, two songs that used the same melody. We analyse the discourses communicated by the semiotic choices made in melody, arrangements, sound qualities, rhythms as well as in lyrics. The article first identifies some of the underlying semiotic resources for meaning making in sound and then shows how these are used in order to communicate specific ideas, values and attitudes. (shrink)

In this article, we carry out a Multimodal Critical Discourse Analysis of a sample from a larger corpus of Romanian news articles that covered the controversial camp evictions and repatriation of Romanian Roma migrants from France that began in 2010 and continue to the time of writing in 2017. These French government policies have been highly criticized both within France and by international political and aid organizations. However, the analysis shows how these brutal, anti-humanitarian events became recontextualized in the Romanian (...) Press to represent the French government’s actions as peaceful and consensual. In addition, the demonization of the Roma in the press serves as a strategy to continuously disassociate them from their Romanian counterparts. While there is a long history of discrimination against the Roma in Romania, these particular recontextualizations can be understood in the context of the Romanian government’s need to gloss over its failure to comply with the Schengen accession requirements and acquire full European Union membership. (shrink)

While there has been extensive work on the textual realizations of climate change in the media, there has been little on the way such discourses are realized and promoted visually. This article addresses this using Multimodal Critical Discourse Analysis to examine a new collection of images from the globally operating Getty Images intended for use in promotions, advertisements and editorials. Getty is promoting this collection in terms of Green Issues being a `marketing opportunity'. In this article we consider the results (...) of these issues being recontextualized through this process, where they are shaped to fit the culture of branding. Analysis is of the images and the search terms where Getty lay out what can be said with the images. (shrink)

There has been criticism of how Fair-Trade products represent workers in remote parts of the world where packaging offers an encounter with distant others which romanticizes and homogenizes them as a pre-modern form of ethnicity. Such workers are shown as always engaged in authentic, simple, honest decontextualized manual labor. And they are depicted as highly appreciative of, and empowered by, the act of ethical shopping. This paper shows that a close social semiotic analysis of Fair-Trade packaging reveals a different set (...) of meanings which sit alongside the decontextualized ones. Designs integrate these workers into more contemporary kinds of modernist, rational, design chic, which communicates its own kind of honesty and authenticity. We consider how this, too, shapes how such consumers encounter distant others and its consequence for the meaning of the act of ethical shopping, where consumers can buy into moral alignment offered by products. (shrink)

The United Nations ‘Transforming our world: the 2030 Agenda for Sustainable Development’ lays out 17 Sustainable Development Goals to address a range of global issues related to the future of the planet and human well-being. Critics, however, argue that the Agenda, a complex product of multi-stakeholder governance, in its drive to accommodate many competing voices, is overloaded with weakly defined, overlapping and contradictory issues, concepts and buzzwords. These serve to gloss over actual concrete global problems and forces, concealing an underlying (...) free-trade ideology. In this paper, using Multimodal Critical Discourse Analysis, we draw attention to the nature of the documents used to communicate the Agenda. These documents comprise an edifice of self-referential texts that rely heavily on infographics, bullet points, charts and tables. Such formats appear to helpfully simplify, distil information and break things down into workable components. But, we show, through the affordances of these formats, the the vagueness of buzzwords, contradictions and lack of clear causalities can be glossed over, presenting the Agenda as a highly technical, engaging, and above all moral process. These formats are important, therefore, for the legitimization and rhetorical power of the Agenda, necessary for its take-up by governments and organizations around the world. (shrink)

Name der Zeitschrift: Semiotica - Journal of the International Association for Semiotic Studies / Revue de l'Association Internationale de Sémiotique Jahrgang: 2013 Heft: 197 Seiten: 119-140.

It has become common to find diagrams and flow-charts used in our organizations to illustrate the nature of processes, what is involved and how it happens, or to show how parts of the organization interrelate to each other and work together. Such diagrams are used as they are thought to help visualization and simplify things in order to represent the essence of a particular situation, the core features. In this paper, using a social semiotic approach, we show that we need (...) to develop a much more critical sense of how these diagrams and flowcharts can easily abstract, conceal and substitute actual causalities, work roles and relationships. We demonstrate this using the example of a series of interrelated flows-charts used to implement a new system of target-based learning in preschool/kindergartens in Sweden – a system which works highly in favor of a rapidly privatizing education sector. Here, the flow charts shape how school processes and learning are presented to devalue the former system and value the new. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

ABSTRACTIn Critical Discourse Studies and in other linguistics oriented scholarly journals we now see more research which draws upon multimodality as part of carrying out analyses of how text...

Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.

We are very grateful for the responses given to our article and for the editor of this journal for inviting us to have this kind of interaction. We simply need to have this kind of open discussion...

Among the categories of the telecom and internet frauds, the online romance scam is of particular concern for its sharp rise of victim numbers and the huge amount of cost. A social semiotic approach could be used to investigate the victim identity of the online romance scam from the aspects of the (re)construction and interpretation of discursive practices. The range of papers in this section shows that the study of text, context and the way that people use semiotic resources to (...) produce communication, to create and manage events and to interpret them. (shrink)

The notion of a ‘machinery of death’ not only underwrites abolitionist discourse but also informs what Derrida's Death Penalty refers to as an anesthesial drive that can be traced back at least as far as Guillotin. I read it here as a symptom of a more complex relation to the technological that functions across the line dividing life from death, and which is concentrated in the question of the instant that capital punishment requires. Further indications of such a relation include (...) the forms of automatic machinism that regulate, on one hand, the generalisable certainty that death occurs, and on the other, the discursive contagion that the death penalty generates. But it can be analysed most productively in the way in which the putative instantaneity of an execution reveals how life is severed from, but also perhaps tethered to death by means of a machinery of time; how that machinery of time ‘abandons’ its indifference in order to decide the moment of death by execution, and at the same time, by contriving an instant at which death takes over from life, produces the uncanny result of having life and death meet on the same knife-edge. (shrink)

One of the enduring concerns of moral philosophy is deciding who or what is deserving of ethical consideration. Much recent attention has been devoted to the "animal question" -- consideration of the moral status of nonhuman animals. In this book, David Gunkel takes up the "machine question": whether and to what extent intelligent and autonomous machines of our own making can be considered to have legitimate moral responsibilities and any legitimate claim to moral consideration. The machine question poses a (...) fundamental challenge to moral thinking, questioning the traditional philosophical conceptualization of technology as a tool or instrument to be used by human agents. Gunkel begins by addressing the question of machine moral agency: whether a machine might be considered a legitimate moral agent that could be held responsible for decisions and actions. He then approaches the machine question from the other side, considering whether a machine might be a moral patient due legitimate moral consideration. Finally, Gunkel considers some recent innovations in moral philosophy and critical theory that complicate the machine question, deconstructing the binary agent--patient opposition itself. Technological advances may prompt us to wonder if the science fiction of computers and robots whose actions affect their human companions could become science fact. Gunkel's argument promises to influence future considerations of ethics, ourselves, and the other entities who inhabit this world. (shrink)

ABSTRACT The law, in its majestic equality, forbids the rich as well as the poor to sleep under bridges, to beg in the streets, and to steal bread. (Jacques Anatole François Thibault).

ABSTRACT In this paper we explore how a public national media outlet, the British BBC, represents an international legal case which has a highly political nature. The case is US versus Huawei/meng Wanzhou, which took place between 2018 and 2021. Accusations were that the Chinese technology company committed fraud, leading the global HSBC bank to breach US sanctions against Iran. The charges were made by the US using what is called an ‘extraterritorial law’, which, while rejected as law by governments (...) around the world, is policed by US economic powers and control over international finance. Using Critical Discourse Analysis we show that, while the BBC presents much detail of legal process, the actual nature of the law the US uses to bring criminal charges against international companies and banks, is neither considered nor questioned. Our interest is how such a law, which has a huge influence over global trade and politics, is presented to the public in this particular case. We contribute to the position that the nature of laws, how they are used and known, must always be understood within the prevailing discourses of the moment. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

StyleLikeU is a hugely successful online social media platform that presents itself as a social justice movement related to body acceptance. Presenting moving personal stories, it offers a site for what it calls ‘diverse individuals’ to share their experiences as part of promoting individual self-acceptance in the face of a world that prioritizes one kind of body over another, which take the form of ableism, racism, sexism, homophobia, transphobia, ageism, sizeism and prejudice against disfigurement. Drawing out the discursive script carried (...) across the platform, we show how, beneath the rhetoric of progressiveness, social justice becomes a kind of personal therapy, related to empowerment and transformation, which erases actual differences in personal circumstances and the very forces of injustice. We place StyleLikeU into broader scholarly concerns about the neoliberal colonization of identity politics, diversity and intersectionality in institutions and in branding, drawing attention to how this can form one part of what are now presented as social justice movements. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealisedexplanation gamein which players collaborate to find the best explanation(s) for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal patterns of (...) variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a (conditionally) optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative supervised learning (...) methods—namely lasso penalties, bagging, and boosting—offer subtler, more interesting analogies to human reasoning as both an individual and a social phenomenon. Despite the temptation to fall back on anthropomorphic tropes when discussing AI, however, I conclude that such rhetoric is at best misleading and at worst downright dangerous. The impulse to humanize algorithms is an obstacle to properly conceptualizing the ethical challenges posed by emerging technologies. (shrink)

One of the more compelling features of Denis Dutton’s The Art Instinct is its theoretical parsimony. Utilizing what essentially amounts to one explanatory principle—that of Darwinian selection—Dutton advances a theory of aesthetics that is at once general enough to account for cross-cultural variations in artistic production and sufficiently nuanced to promote insights into individual artworks. In doing this, Dutton’s work could not offer a greater contrast to some of the more vocal trends in contemporary aesthetic theory, where ponderous theorizing and (...) rebarbative jargons have violently opposed the idea—otherwise so modest—that aesthetic activities might draw on the evolved capacities of the human imagination. On .. (shrink)

According to the most popular theories of intentionality, a family of theories we will refer to as “functional intentionality,” a machine can have genuine intentional states so long as it has functionally characterizable mental states that are causally hooked up to the world in the right way. This paper considers a detailed description of a robot that seems to meet the conditions of functional intentionality, but which falls victim to what I call “the composition problem.” One obvious way to escape (...) the problem (arguably, the only way) is if the robot can be shown to be a moral patient – to deserve a particular moral status. If so, it isn’t clear how functional intentionality could remain plausible (something like “phenomenal intentionality” would be required). Finally, while it would have seemed that a reasonable strategy for establishing the moral status of intelligent machines would be to demonstrate that the machine possessed genuine intentionality, the composition argument suggests that the order of precedence is reversed: The machine must first be shown to possess a particular moral status before it is a candidate for having genuine intentionality. (shrink)

A growing body of literature critical of ethics review boards has drawn attention to the processes used to determine the ethical merit of research. Citing criticism on the bureaucratic nature of ethics review processes, this literature provides a useful provocation for (re)considering how the ethics review might be enacted. Much of this criticism focuses on how ethics review boards _deliberate,_ with particular attention given to the lack of transparency and opportunities for researcher recourse that characterise ethics review processes. Centered specifically (...) on the conduct of ethics review boards convened within university settings, this paper draws on these inherent criticisms to consider the ways that ethics review boards might enact more communicative and deliberative practices. Outlining a set of principles against which ethics review boards might establish strategies for engaging with researchers and research communities, this paper draws attention to how _Deliberative communication_, _Engagement with researchers_ and the _Distribution of responsibility_ for the ethics review might be enacted in the day-to-day practice of the university human ethics review board. This paper develops these themes via a conceptual lens derived from Habermas’ (The theory of communicative action. Volume 1: Reason and the rationalization of society, 1984 ) articulation of ‘communicative action’ and Fraser’s (Social Text, 25(26), 56–80, 1990 ) consideration of ‘strong publics’ to cast consideration of the role that human ethics review boards might play in supporting university research cultures. _Deliberative communication_, _Engagement with researchers_ and the _Distribution of responsibility_ provide useful conceptual prompts for considering how ethics review boards might undertake their work. (shrink)

As machine learning has gradually entered into ever more sectors of public and private life, there has been a growing demand for algorithmic explainability. How can we make the predictions of complex statistical models more intelligible to end users? A subdiscipline of computer science known as interpretable machine learning (IML) has emerged to address this urgent question. Numerous influential methods have been proposed, from local linear approximations to rule lists and counterfactuals. In this article, I highlight three conceptual challenges that (...) are largely overlooked by authors in this area. I argue that the vast majority of IML algorithms are plagued by (1) ambiguity with respect to their true target; (2) a disregard for error rates and severe testing; and (3) an emphasis on product over process. Each point is developed at length, drawing on relevant debates in epistemology and philosophy of science. Examples and counterexamples from IML are considered, demonstrating how failure to acknowledge these problems can result in counterintuitive and potentially misleading explanations. Without greater care for the conceptual foundations of IML, future work in this area is doomed to repeat the same mistakes. (shrink)

§1. Mathematics and the physical world. Genuine scientific knowledge cannot be certain, nor can it be justified a priori. Instead, it must be conjectured, and then tested by experiment, and this requires it to be expressed in a language appropriate for making precise, empirically testable predictions. That language is mathematics.This in turn constitutes a statement about what the physical world must be like if science, thus conceived, is to be possible. As Galileo put it, “the universe is written in the (...) language of mathematics”. Galileo's introduction of mathematically formulated, testable theories into physics marked the transition from the Aristotelian conception of physics, resting on supposedly necessary a priori principles, to its modern status as a theoretical, conjectural and empirical science. Instead of seeking an infallible universal mathematical design, Galilean science usesmathematics to express quantitative descriptions of an objective physical reality. Thus mathematics became the language in which we express our knowledge of the physical world — a language that is not only extraordinarily powerful and precise, but also effective in practice. Eugene Wigner referred to “the unreasonable effectiveness of mathematics in the physical sciences”. But is this effectiveness really unreasonable or miraculous?Numbers, sets, groups and algebras have an autonomous reality quite independent of what the laws of physics decree, and the properties of these mathematical structures can be just as objective as Plato believed they were. (shrink)

Cognitive neuroscientists are turning to an increasingly rich array of neurodynamical systems to explain mental phenomena. In these explanations, cognitive capacities are decomposed into a set of functions, each of which is described mathematically, and then these descriptions are mapped on to corresponding mathematical descriptions of the dynamics of neural systems. In this paper, I outline a novel explanatory schema based on these explanations. I then argue that these explanations present a novel type of dynamicism for the philosophy of mind (...) and neuroscience, componential dynamicism, that focuses on the parts of cognitive systems that fill certain functional roles in producing cognitive phenomena. (shrink)

In 1738, Jacques Vaucanson unveiled his masterpiece before the court of Louis XV: a gilded copper duck that ate, drank, quacked, flapped its wings, splashed about, and, most astonishing of all, digested its food and excreted the remains. The imitation of life by technology fascinated Vaucanson's contemporaries. Today our technology is more powerful, but our fascination is tempered with apprehension. Artificial intelligence and genetic engineering, to name just two areas, raise profoundly disturbing ethical issues that undermine our most fundamental beliefs (...) about what it means to be human. In The Vital Machine, David Channell examines the history of our relationship with technology and argues that, while the resolution of these issues may not be imminent, a philosophical framework for dealing with them is already in place. The source of our fears, he suggests, lies in an outmoded distinction between organic life and machines, a distinction rooted in the two world-views that have defined and guided Western civilization: the mechanical and the organic. The mechanical view holds that the universe is basically a machine--we can understand it by breaking it down into its smallest components. Even organisms are machines. The organic view claims that there is something more, some vital, directive force. The whole is more than just the sum of its parts. Even machines are organisms. Channell presents these polar views in a fascinating chronicle of human thought and achievement, ranging over the discoveries of Galileo, Copernicus, Newton, and Einstein, the philosophies of Plato, Descartes, Kant, and Marx, the fields of alchemy, physics, astrology, and biology. We see not only how the two views progressed independently, but also how they influenced each other, not only how they persisted, but also how they changed. Most fascinating of all, we follow the emergence of a third, all-embracing world view as developments in genetics, relativity, quantum mechanics, and computer intelligence force both science and philosophy to come to a more complex understanding of the universe. As a central metaphor for this third view Channell proposes "the vital machine." And in this stimulating work by the same name, he reveals how this new metaphor may provide us with the philosophical understanding we need to address the ethical issues our science has created. (shrink)

Cognitive neuroscientists are turning to an increasingly rich array of neurodynamical systems to explain mental phenomena. In these explanations, cognitive capacities are decomposed into a set of functions, each of which is described mathematically, and then these descriptions are mapped on to corresponding mathematical descriptions of the dynamics of neural systems. In this paper, I outline a novel explanatory schema based on these explanations. I then argue that these explanations present a novel type of dynamicism for the philosophy of mind (...) and neuroscience, componential dynamicism, that focuses on the parts of cognitive systems that fill certain functional roles in producing cognitive phenomena. (shrink)

Cognitive neuroscientists are turning to an increasingly rich array of neurodynamical systems to explain mental phenomena. In these explanations, cognitive capacities are decomposed into a set of functions, each of which is described mathematically, and then these descriptions are mapped on to corresponding mathematical descriptions of the dynamics of neural systems. In this paper, I outline a novel explanatory schema based on these explanations. I then argue that these explanations present a novel type of dynamicism for the philosophy of mind (...) and neuroscience, componential dynamicism, that focuses on the parts of cognitive systems that fill certain functional roles in producing cognitive phenomena. (shrink)

This essay responds to the machine question in the affirmative, arguing that artifacts, like robots, AI, and other autonomous systems, can no longer be legitimately excluded from moral consideration. The demonstration of this thesis proceeds in four parts or movements. The first and second parts approach the subject by investigating the two constitutive components of the ethical relationship—moral agency and patiency. In the process, they each demonstrate failure. This occurs not because the machine is somehow unable to achieve what is (...) considered necessary and sufficient to be a moral agent or patient but because the characterization of agency and patiency already fail to accommodate others. The third and fourth parts respond to this problem by considering two recent alternatives—the all-encompassing ontocentric approach of Luciano Floridi’s information ethics and Emmanuel Levinas’s eccentric ethics of otherness. Both alternatives, despite considerable promise to reconfigure the scope of moral thinking by addressing previously excluded others, like the machine, also fail but for other reasons. Consequently, the essay concludes not by accommodating the alterity of the machine to the requirements of moral philosophy but by questioning the systemic limitations of moral reasoning, requiring not just an extension of rights to machines, but a thorough examination of the way moral standing has been configured in the first place. (shrink)

According to Karl Popper, the evolution of science, logically, methodologically, and even psychologically, is an involved interplay of acute conjectures and blunt refutations. Like biological evolution, it is an endless round of blind variation and selective retention. But unlike biological evolution, it incorporates, at the stage of selection, the use of reason. Part I of this two-part paper begins by repudiating the common beliefs that Hume’s problem of induction, which compellingly confutes the thesis that science is rational in the way (...) that most people think that it is rational, can be solved by assuming that science is rational, or by assuming that Hume was irrational (that is, by ignoring his argument). The problem of induction can be solved only by a non-authoritarian theory of rationality. It is shown also that because hypotheses cannot be distilled directly from experience, all knowledge is eventually dependent on blind conjecture, and therefore itself conjectural. In particular, the use of rules of inference, or of good or bad rules for generating conjectures, is conjectural. Part II of the paper expounds a form of Popper’s critical rationalism that locates the rationality of science entirely in the deductive processes by which conjectures are criticized and improved. But extreme forms of deductivism are rejected. The paper concludes with a sharp dismissal of the view that work in artificial intelligence, including the JSM method cultivated extensively by Victor Finn, does anything to upset critical rationalism. Machine learning sheds little light on either the problem of induction or on the role that logic plays in the development of scientific knowledge. (shrink)

According to Karl Popper, the evolution of science, logically, methodologically, and even psychologically, is an involved interplay of acute conjectures and blunt refutations. Like biological evolution, it is an endless round of blind variation and selective retention. But unlike biological evolution, it incorporates, at the stage of selection, the use of reason. Part I of this two-part paper begins by repudiating the common beliefs that Hume’s problem of induction, which compellingly confutes the thesis that science is rational in the way (...) that most people think that it is rational, can be solved by assuming that science is rational, or by assuming that Hume was irrational (that is, by ignoring his argument). The problem of induction can be solved only by a non-authoritarian theory of rationality. It is shown also that because hypotheses cannot be distilled directly from experience, all knowledge is eventually dependent on blind conjecture, and therefore itself conjectural. In particular, the use of rules of inference, or of good or bad rules for generating conjectures, is conjectural. Part II of the paper expounds a form of Popper’s critical rationalism that locates the rationality of science entirely in the deductive processes by which conjectures are criticized and improved. But extreme forms of deductivism are rejected. The paper concludes with a sharp dismissal of the view that work in artificial intelligence, including the JSM method cultivated extensively by Victor Finn, does anything to upset critical rationalism. Machine learning sheds little light on either the problem of induction or on the role that logic plays in the development of scientific knowledge. (shrink)

The paper adopts an inter-theoretical socio-cultural and -material perspective on the relationship between human + machine learning to propose a new way to investigate the human + machine assistive assemblages emerging in professional work (e.g. medicine, architecture, design and engineering). Its starting point is Hutchins’s (1995a) concept of ‘distributed cognition’ and his argument that his concept of ‘cultural ecosystems’ constitutes a unit of analysis to investigate collective human + machine working and learning (Hutchins, Philos Psychol 27:39–49, 2013). It argues that: (...) (i) the former offers a way to reveal the cultural constitution of and enactment of human + machine cognition and, in the process, the limitations of the computational and connectionist assumptions about learning that underpin, respectively, good old-fashioned AI and deep learning; and (2) the latter offers a way to identify, when amplified with insights from Socio-Materialism and Cultural-Historical Activity Theory, how ML is further rearranging and reorganising the distributed basis of cognition in assistive assemblages. The paper concludes by outlining a set of conjectures researchers that could use to guide their investigations into the ongoing design and deployment of HL + ML assemblages and challenges associated with the interaction between HL + ML. (shrink)

Prediction-based decisions, which are often made by utilizing the tools of machine learning, influence nearly all facets of modern life. Ethical concerns about this widespread practice have given rise to the field of fair machine learning and a number of fairness measures, mathematically precise definitions of fairness that purport to determine whether a given prediction-based decision system is fair. Following Reuben Binns (2017), we take ‘fairness’ in this context to be a placeholder for a variety of normative egalitarian considerations. We (...) explore a few fairness measures to suss out their egalitarian roots and evaluate them, both as formalizations of egalitarian ideas and as assertions of what fairness demands of predictive systems. We pay special attention to a recent and popular fairness measure, counterfactual fairness, which holds that a prediction about an individual is fair if it is the same in the actual world and any counterfactual world where the individual belongs to a different demographic group (cf. Kusner et al. (2018)). (shrink)

In his stimulating book SHADOWS OF THE MIND, Roger Penrose presents arguments, based on Gödel's theorem, for the conclusion that human thought is uncomputable. There are actually two separate arguments in Penrose's book. The second has been widely ignored, but seems to me to be much more interesting and novel than the first. I will address both forms of the argument in some detail. Toward the end, I will also comment on Penrose's proposals for a "new science of consciousness".

It is the height of banality to observe that people, not bullets, fight kinetic wars. The machinery of kinetic warfare is obviously relevant to the conduct of each particular act of warfare, but the reasons for, and meanings of, those acts depend critically on the fact that they are done by humans. Any attempt to understand warfare—its causes, strategies, legitimacy, dynamics, and resolutions—must incorporate humans as an intrinsic part, both descriptively and normatively. Humans from general staff to “boots on the (...) ground” play key roles in all aspects of kinetic warfare, and the literature about it reflects this focus. 2 In contrast, many discussions of cyberwarfare and cyber-conflict focus principally on the technical aspects of machines, systems, and data, 3 and human agents are included only as collateral effects, or as loci of moral responsibility. (shrink)

Consciousness is widely perceived as one of the most fundamental, interesting and difficult problems of our time. However, we still know next to nothing about the relationship between consciousness and the brain and we can only speculate about the consciousness of animals and machines. Human and Machine Consciousness presents a new foundation for the scientific study of consciousness. It sets out a bold interpretation of consciousness that neutralizes the philosophical problems and explains how we can make scientific predictions about the (...) consciousness of animals, brain-damaged patients and machines. Gamez interprets the scientific study of consciousness as a search for mathematical theories that map between measurements of consciousness and measurements of the physical world. We can use artificial intelligence to discover these theories and they could make accurate predictions about the consciousness of humans, animals and artificial systems. Human and Machine Consciousness also provides original insights into unusual conscious experiences, such as hallucinations, religious experiences and out-of-body states, and demonstrates how 'designer' states of consciousness could be created in the future. Gamez explains difficult concepts in a clear way that closely engages with scientific research. His punchy, concise prose is packed with vivid examples, making it suitable for the educated general reader as well as philosophers and scientists. Problems are brought to life in colourful illustrations and a helpful summary is given at the end of each chapter. The endnotes provide detailed discussions of individual points and full references to the scientific and philosophical literature."--Publisher's website. (shrink)

This paper is a review of the work that has been carried out on machine consciousness. A clear overview of this diverse field is achieved by breaking machine consciousness down into four different areas, which are used to understand its aims, discuss its relationship with other subjects and outline the work that has been carried out so far. The criticisms that have been made against machine consciousness are also covered, along with its potential benefits, and the work that has been (...) done on analysing systems for signs of consciousness. Some of the social and ethical issues raised by machine consciousness are examined at the end of the paper. (shrink)

Infinite time Turing machines extend the operation of ordinary Turing machines into transfinite ordinal time. By doing so, they provide a natural model of infinitary computability, a theoretical setting for the analysis of the power and limitations of supertask algorithms.

Although Gilles Deleuze is one of France’s most celebrated twentieth-century philosophers, his theories of cinema have largely been ignored by American scholars. Film theorist D. N. Rodowick fills this gap by presenting the first comprehensive study, in any language, of Deleuze’s work on film and images. Placing Deleuze’s two books on cinema—_The Movement-Image _and _The Time-Image_—in the context of French cultural theory of the 1960s and 1970s, Rodowick examines the logic of Deleuze’s theories and the relationship of these theories to (...) his influential philosophy of difference. Rodowick illuminates the connections between Deleuze’s writings on visual and scientific texts and describes the formal logic of his theory of images and signs. Revealing how Deleuzian views on film speak to the broader network of philosophical problems addressed in Deleuze’s other books—including his influential work with Félix Guattari—Rodowick shows not only how Deleuze modifies the dominant traditions of film theory, but also how the study of cinema is central to the project of modern philosophy. (shrink)

As non-biological machines come to be designed in ways which exhibit characteristics comparable to human mental states, the manner in which the law treats these entities will become increasingly important both to designers and to society at large. The direct question will become whether, given certain attributes, a non-biological machine could ever be viewed as a legal person. In order to begin to understand the ramifications of this question, this paper starts by exploring the distinction between the related concepts of (...) human, person, and property. Once it is understood that person in the legal sense can apply to a non-biological entity such as a corporation, the inquiry then goes on to examine the folk psychology view of intentionality and the concept of autonomy. The conclusion reached is that these two attributes can support the view that a non-biological machine, at least in theory, can be viewed as a legal person. (shrink)

Infinite time Turing machines extend the operation of ordinary Turing machines into transfinite ordinal time. By doing so, they provide a natural model of infinitary computability, a theoretical setting for the analysis of the power and limitations of supertask algorithms.

The application of machine learning algorithms to healthcare data can enhance patient care while also reducing healthcare worker cognitive load. These algorithms can be used to detect anomalous physiological readings, potentially leading to expedited emergency response or new knowledge about the development of a health condition. However, while there has been much research conducted in assessing the performance of anomaly detection algorithms on well-known public datasets, there is less conceptual comparison across unsupervised and supervised performance on physiological data. Moreover, while (...) heart rate data are both ubiquitous and noninvasive, there has been little research specifically for anomaly detection of this type of data. Considering that heart rate data are indicative of both potential health complications and an individual’s physical activity, this is a rich source of largely overlooked data. To this end, we employed and evaluated five machine learning algorithms, two of which are unsupervised and the remaining three supervised, in their ability to detect anomalies in heart rate data. These algorithms were then evaluated on real heart rate data. Findings supported the effectiveness of local outlier factor and random forests algorithms in the task of heart rate anomaly detection, as each model generalized well from their training on simulated heart rate data to real world heart rate data. Furthermore, results support that simulated data can help configure algorithms to a degree of performance when real labeled data are not available and that this type of learning might be especially helpful in initial deployment of a system without prior data. (shrink)

Given the pervasiveness of AI systems and their potential negative effects on people’s lives (especially among already marginalised groups), it becomes imperative to comprehend what goes on when an AI system generates a result, and based on what reasons, it is achieved. There are consistent technical efforts for making systems more “explainable” by reducing their opaqueness and increasing their interpretability and explainability. In this paper, we explore an alternative non-technical approach towards explainability that complement existing ones. Leaving aside technical, statistical, (...) or data-related issues, we focus on the very conceptual underpinnings of the design decisions made by developers and other stakeholders during the lifecycle of a machine learning project. For instance, the design and development of an app to track snoring to detect possible health risks presuppose some picture or another of “health”, which is a key notion that conceptually underpins the project. We take it as a premise that these key concepts are necessarily present during design and development, albeit perhaps tacitly. We argue that by providing “justificatory explanations” about how the team understands the relevant key concepts behind its design decisions, interested parties could gain valuable insights and make better sense of the workings and outcomes of systems. Using the concept of “health”, we illustrate how a particular understanding of it might influence decisions during the design and development stages of a machine learning project, and how making this explicit by incorporating it into ex-post explanations might increase the explanatory and justificatory power of these explanations. We posit that a greater conceptual awareness of the key concepts that underpin design and development decisions may be beneficial to any attempt to develop explainability methods. We recommend that “justificatory explanations” are provided as technical documentation. These are declarative statements that contain at its simplest: (1) a high-level account of the understanding of the relevant key concepts a team possess related to a project’s main domain, (2) how these understandings drive decision-making during the life-cycle stages, and (3) it gives reasons (which could be implicit in the account) that the person or persons doing the explanation consider to have plausible justificatory power for the decisions that were made during the project. (shrink)

We extend in a natural way the operation of Turing machines to infinite ordinal time, and investigate the resulting supertask theory of computability and decidability on the reals. Everyset. for example, is decidable by such machines, and the semi-decidable sets form a portion of thesets. Our oracle concept leads to a notion of relative computability for sets of reals and a rich degree structure, stratified by two natural jump operators.