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)

This article argues against the claim that democracy is a necessary condition of political legitimacy. Instead, I propose a weaker set of conditions. First, I explain the case for the necessity of democracy. This is that only democracy can address the ‘egalitarian challenge’, i.e. ‘if we are all equal, why should only some of us wield political power?’. I show that if democracy really is a necessary condition of political legitimacy, then (what I label) the problems of domestic justice and (...) of international legitimacy become intractable. I then argue that the egalitarian challenge is addressed where the requirements of (1) horizontal equality, (2) acceptable vertical inequality, and (3) publicity, are met and where (4) citizens have some institutionalized opportunity for a voice in decisions. I show that these conditions can be realized in non-democratic form and conclude by explaining how the four conditions can be employed to make the problems of domestic justice and of international legitimacy more tractable. Overall, my ambitions are limited. I do not offer an all-things-considered case against democracy but I do show that (some) forms of non-democratic government are permissible. (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)

This electronic document serves as a guide on how to get a LAMP stack running on a Google Compute Engine virtual machine instance running Debian.

Whitehead believed that education must give us ideas that are usable in our actual lives. This line of thought is naturally provoked by the significant abundance of inert ideas that people pile up though education. The main reason for that, I claim, is the wrong focus of traditional education. It aims at producing individuals that would deliver high results on exams and tests. I take Whitehead’s claim the education must put emphasis on usable ideas as my starting point. I give (...) a specific interpretation of useable ideas as abilities or functions. This provides a ground for connecting Whiteheadian thought to an already existing educational platform, offered by Nel Noddings. Noddings develops a cognitive theory of education which places cognitive structures (I assume a robust analogy between structures, functions, and abilities) in the center of educational concern. At the end of the paper, I estimate some consequences from adopting the terminology of functions for connecting between human and machine learning. (shrink)

By looking at the politics of classification within machine learning systems, this article demonstrates why the automated interpretation of images is an inherently social and political project. We begin by asking what work images do in computer vision systems, and what is meant by the claim that computers can “recognize” an image? Next, we look at the method for introducing images into computer systems and look at how taxonomies order the foundational concepts that will determine how a system interprets (...) the world. Then we turn to the question of labeling: how humans tell computers which words will relate to a given image. What is at stake in the way AI systems use these labels to classify humans, including by race, gender, emotions, ability, sexuality, and personality? Finally, we turn to the purposes that computer vision is meant to serve in our society—the judgments, choices, and consequences of providing computers with these capacities. Methodologically, we call this an archeology of datasets: studying the material layers of training images and labels, cataloguing the principles and values by which taxonomies are constructed, and analyzing how these taxonomies create the parameters of intelligibility for an AI system. By doing this, we can critically engage with the underlying politics and values of a system, and analyze which normative patterns of life are assumed, supported, and reproduced. (shrink)

Gödei's Theorem seems to me to prove that Mechanism is false, that is, that minds cannot be explained as machines. So also has it seemed to many other people: almost every mathematical logician I have put the matter to has confessed to similar thoughts, but has felt reluctant to commit himself definitely until he could see the whole argument set out, with all objections fully stated and properly met. This I attempt to do.

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)

Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which (...) they are presumptuous. After elaborating this moral concern, I explore the possibility that carefully procuring the training data for image recognition systems could ensure that the systems avoid the problem. The lesson of this paper extends beyond just the particular case of image recognition systems and the challenge of responsibly identifying a person’s intentions. Reflection on this particular case demonstrates the importance (as well as the difficulty) of evaluating machine learning systems and their training data from the standpoint of moral considerations that are not encompassed by ordinary assessments of predictive accuracy. (shrink)

Legal documents, like contracts or laws, are subject to interpretation. Different people can have different interpretations of the very same document. Large parts of judicial branches all over the world are concerned with settling disagreements that arise, in part, from these different interpretations. In this context, it only seems natural that during the annotation of legal machine learning data sets, disagreement, how to report it, and how to handle it should play an important role. This article presents an analysis (...) of the current state-of-the-art in the annotation of legal machine learning data sets. The results of the analysis show that all of the analysed data sets remove all traces of disagreement, instead of trying to utilise the information that might be contained in conflicting annotations. Additionally, the publications introducing the data sets often do provide little information about the process that derives the “gold standard” from the initial annotations, often making it difficult to judge the reliability of the annotation process. Based on the state-of-the-art, the article provides easily implementable suggestions on how to improve the handling and reporting of disagreement in the annotation of legal machine learning data sets. (shrink)

Large language models (LLMs) represent the currently most relevant incarnation of artificial intelligence with respect to the future fate of democratic governance. Considering their potential, this paper seeks to answer a pressing question: Could LLMs outperform humans as expert advisors to democratic assemblies? While bearing the promise of enhanced expertise availability and accessibility, they also present challenges of hallucinations, misalignment, or value imposition. Weighing LLMs’ benefits and drawbacks compared to their human counterparts, I argue for their careful integration to augment (...) democracy’s ability to address complex policy issues. The paper posits that time-tested democratic procedures like deliberation and aggregation by voting provide safeguards effective against both human and machine advisor imperfections. Additional protective measures include custom LLM training for the advisory role, boosting representatives’ competencies in query formulation, or implementation of adversarial proceedings in which LLM advisors could debate each other and provide dissenting opinions. These could further mitigate the risks that LLMs present in advisory roles and empower human decision-makers toward increased autonomy and quality of their collective choices. My conceptual exploration offers a roadmap for the co-evolution of AI and democratic institutions, setting the stage for an empirical research agenda to finetune the implementation specifics. (shrink)

This paper develops an account of how the implementation of ML models into healthcare settings requires revising the methodological apparatus of philosophical bioethics. On this account, ML models are cognitive interventions that provide decision-support to physicians and patients. Due to reliability issues, opaque reasoning processes, and information asymmetries, ML models pose inferential problems for them. These inferential problems lay the grounds for many ethical problems that currently claim centre-stage in the bioethical debate. Accordingly, this paper argues that the best way (...) to make progress in remedying these ethical problems is to distil their epistemic core and to identify appropriate epistemic norms as guardrails. The viability of this approach will be highlighted based on four key issues: trust, responsibility, paternalism, and fairness. In that respect, the paper also contributes to a more pronounced view of the specific methodological challenges for ethical theorizing, when the point of reference are complex statistical models that make predictions, rather than individual agents, acting for reasons. (shrink)

This study investigates the performance of 21 monolingual and 56 bilingual children aged 5;6-9;0 on German-LITMUS-sentence-repetition (SRT; Hamann et al., 2013) and nonword-repetition-tasks (NWRT; Grimm et al., 2014), which were constructed according to the LITMUS-principles (Language Impairment Testing in Multilingual Settings; Armon-Lotem et al., 2015). Both tasks incorporate complex structures shown to be cross-linguistically challenging for children with Specific Language Impairment (SLI) and aim at minimizing bias against bilingual children while still being indicative of the presence of language impairment across (...) language combinations. Given the great variability in bilingual language exposure and the potential effect of language experience on language performance in bilingual children, we examined whether background variables related to bilingualism, particularly, the degree language dominance as measured by relative amount of use and exposure, could compromise the diagnostic accuracy of the German-LITMUS-SRT and NWRT. We further investigated whether a combination of the two tasks provides better diagnostic accurracy. To address this, we used an unsupervised machine learning algorithm, the Partitioning-Around-Medoids (PAM), for deriving a clinical category for the children as ±language-impaired based on performance scores on SRT and/or NWRT while withholding information about their clinical status based on standardized assessment in L1/L2. Subsequently, we calculated diagnostic accuracy and investigated which background variables (age of onset, length of exposure, degree of language-dominance, socio-economic-status, and risk factors for SLI) best explained clinical-group-membership yielded from the PAM-analysis based on NWRT and/or SRT scores. Results show that although language-dominance influences the performance of bilingual typically-developing children, especially in the SRT, the diagnostic accuracy of the tools is not compromised by language dominance: while risk factors for SLI were significant predictors for clinical group membership in all models, language dominance did not contribute at all to explaining clinical cluster membership as typically-developing or SLI based on any of the combinations of the SRT and NWRT variables. Additionally, results confirm that a combination of SRT scored by correct target structure and the structurally more complex language-dependent part of the NWRT yields better diagnostic accuracy than single measures and is only sensitive for risk factors for SLI and not to dominance levels or SES. (shrink)

Lake et al. propose three criteria which, they argue, will bring artificial intelligence (AI) systems closer to human cognitive abilities. In this paper, we explore the application of these criteria to a particular domain of human cognition: our capacity for moral reasoning. In doing so, we explore a set of considerations relevant to the development of AI moral decision-making. Our main focus is on the relation between dual-process accounts of moral reasoning and model-free/model-based forms of machine learning. We also (...) discuss how work in embodied and situated cognition could provide a valu- able perspective on future research. (shrink)

Machine learning and essentialism have been connected in the past by various researchers, in order to state that the main paradigm in machine learning processes is equivalent to choosing the “essential” attributes for the machine to search for. Our goal in this paper is to show that there are connections between machine learning and essentialism, but only for some kinds of machine learning, and often not including deep learning methods. Similarity-based approaches, more connected to the (...) overall prototype theory, spanning from psychology and linguistics, seem more suited for pattern recognition and complex deep-learning issues, while for classification problems, mostly for unsupervised learning, essentialism seems like the best choice. In order to illustrate the difference better, we will connect both paths to their sources in other disciplines and see how human psychology influences our decision in machine-learning modeling as well. This leads to a philosophically very interesting consequence: even in the setting of supervised machine learning, essences are not present in data, but in targets, which in turn means that the categories which purport to be essences are in fact human-made, and hand-coded in the targets. The success of machine learning, therefore, does not give any substantial evidence for the independent existence of essential properties. Our stance here is to state that neither the existence nor the lack of “essential” properties in machine learning can lead to metaphysical, i.e., ontological claims. (shrink)

Mahadevan proposes that we are at the cusp of imagination science, one of whose primary concerns will be the design of imagination machines. Programs have been written that are capable of generating jokes, producing line-drawings that have been exhibited at such galleries as the Tate, composing music in several styles reminiscent of such greats as Vivaldi and Mozart, proving geometry theorems, and inducing quantitative laws from empirical data. In recent years, Dartmouth has been hosting Turing Tests in creativity in three (...) categories: short stories, sonnets, and dance music DJ sets. In this post, I will provide a brief and non-exhaustive survey of some plausible responses to these imagination machines and the related prospects for our understanding of the imagination. (shrink)

An early work that lays the foundation for establishing a “polemical” dimension to psychoanalysis. We certainly have the unconscious that we deserve, an unconscious for specialists, ready-made for an institutionalized discourse. I would rather see it as something that wraps itself around us in everyday objects, something that is involved with day-to-day problems, with the world outside. It would be the possible itself, open to the socius, to the cosmos...—from The Machinic Unconscious: Essays in Schizoanalysis In his seminal solo-authored work (...) The Machinic Unconscious, Félix Guattari lays the groundwork for a general pragmatics capable of resisting the semiotic enslavement of subjectivity. Concluding that psychoanalytic theory had become part and parcel of a repressive, capitalist social order, Guattari here outlines a schizoanalytic theory to undo its capitalist structure and set the discipline back on its feet. Combining theoretical research from fields as diverse as cybernetics, semiotics, ethnology, and ethology, Guattari reintroduces into psychoanalysis a “polemical” dimension, at once transhuman, transsexual, and transcosmic, that brings out the social and political—the “machinic”—potential of the unconscious. To illustrate his theory, Guattari turns to literature and analyzes the various modes of subjectivization and semiotization at work in Proust's In Search of Lost Time, examining the novel as if he were undertaking a scientific exploration in the style of Freud or Newton. Casting Proust's figures as abstract mental objects, Guattari maps the separation between literature and science, elaborating along the way such major Deleuze-Guattarian concepts as “faciality” and “refrain,” which would be unpacked in their subsequent A Thousand Plateaus: Capitalism and Schizophrenia. Never before available in English, The Machinic Unconscious has for too long been the missing chapter from Deleuze and Guattari's Anti-Oedipus project: the most important political extension of May 1968 and one of the most important philosophical contributions of the twentieth century. (shrink)

The creation of artificial moral systems requires us to make difficult choices about which of varying human value sets should be instantiated. The industry-standard approach is to seek and encode moral consensus. Here we argue, based on evidence from empirical psychology, that encoding current moral consensus risks reinforcing current norms, and thus inhibiting moral progress. However, so do efforts to encode progressive norms. Machine ethics is thus caught between a rock and a hard place. The problem is particularly acute (...) when progress beyond prevailing moral norms is particularly urgent, as is currently the case due to the inadequacy of prevailing moral norms in the face of the climate and ecological crisis. (shrink)

In philosophical logic and metaphysics there is a long-standing debate around the most appropriate structures to represent indeterministic scenarios concerning the future. We reconstruct here such a debate in a computational setting, focusing on the fundamental difference between moment-based and history-based structures. Our presentation is centered around two versions of an indeterministic scenario in which a programmer wants a machine to perform a given task at some point after a specified time. One of the two versions includes an (...) assumption about the future behaviour of the machine that cannot be encoded in any programming instruction; such version has models over history-based structures but no model over a moment-based structure. Therefore, our work adds a new stance to the debate: moment-based structures can be said to rule out certain indeterministic scenarios that are computationally unfeasible. (shrink)

The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence (...) from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory? Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society. (shrink)

Machine learning (ML) systems play an increasingly relevant role in medicine and healthcare. As their applications move ever closer to patient care and cure in clinical settings, ethical concerns about the responsibility of their use come to the fore. I analyse an aspect of responsible ML use that bears not only an ethical but also a significant epistemic dimension. I focus on ML systems’ role in mediating patient–physician relations. I thereby consider how ML systems may silence patients’ voices and (...) relativise the credibility of their opinions, which undermines their overall credibility status without valid moral and epistemic justification. More specifically, I argue that withholding credibilitydue tohow ML systems operate can be particularly harmful to patients and, apart from adverse outcomes, qualifies as a form of testimonial injustice. I make my case for testimonial injustice in medical ML by considering ML systems currently used in the USA to predict patients’ risk of misusing opioids (automated Prediction Drug Monitoring Programmes, PDMPs for short). I argue that the locus of testimonial injustice in ML-mediated medical encounters is found in the fact that these systems are treated asmarkers of trustworthinesson which patients’ credibility is assessed. I further show how ML-based PDMPs exacerbate and further propagate social inequalities at the expense of vulnerable social groups. (shrink)

Table of Contents Foreword .................................................................................................... ......................................... xiv Preface .................................................................................................... .............................................. xv Acknowledgment .................................................................................................... .......................... xxiii Section 1 On the Cusp: Critical Appraisals of a Growing Dependency on Intelligent Machines Chapter 1 Algorithms versus Hive Minds and the Fate of Democracy ................................................................... 1 Rick Searle, IEET, USA Chapter 2 We Can Make Anything: Should We? .................................................................................................. 15 Chris Bateman, University of Bolton, UK Chapter 3 Grounding Machine Ethics within the Natural System ........................................................................ 30 Jared Gassen, JMG Advising, USA Nak Young Seong, Independent Scholar, (...) South Korea Section 2 From the Outside In: Intelligent Machine Technologies as a Window on Human Morality both as Evolved and as Evident in Internet Discourse, Today Chapter 4 The Emergence of Arti cial Autonomy: A View from the Foothills of a Challenging Climb ............. 51 Fernando da Costa Cardoso, Universidade Nova de Lisboa, Portugal Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Chapter 5 Semantic Analysis of Bloggers Experiences as a Knowledge Source of Average Human Morality .... 73 Rafal Rzepka, Hokkaido University, Japan Kenji Araki, Hokkaido University, Japan Section 3 From the Inside Out: The Ethics of Human Enhancement from Moral Perception to Competition in the Workplace Chapter 6 Machine Ethics Interfaces: An Ethics of Perception of Nanocognition ............................................... 97 Melanie Swan, Kingston University, UK Chapter 7 Ethical Concerns in Human Enhancement: Advantages in Corporate/Organizational Settings ......... 124 Ben Tran, Alliant International University, USA Section 4 From Far to Near and Near to Far: The Ethics of Distancing Technologies in Education and Warfare Chapter 8 Responsibility and War Machines: Toward a Forward-Looking and Functional Account ................. 152 Jai Galliott, Macquarie University, Australia Chapter 9 Ethical Responsibilities of Preserving Academicians in an Age of Mechanized Learning: Balancing the Demands of Educating at Capacity and Preserving Human Interactivity ................... 166 James E. Willis III, Indiana University, USA Viktoria Alane Strunk, Independent Scholar, USA Section 5 Wrapping Things Up, then Unwrapping Them Again: Integral Visions of Morality in a Technological World, Over Evolutionary Time, with Revolutionary Means, and with Open Questions about the Final Purpose of It All Chapter 10 Bridging Two Realms of Machine Ethics ........................................................................................... 197 Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Ari Saptawijaya, Universidade Nova de Lisboa, Portugal & Universitas Indonesia, Indonesia Chapter 11 Robots in Warfare and the Occultation of the Existential Nature of Violence ................................... 225 Rick Searle, IEET, USA Chapter 12 Self-Referential Complex Systems and Aristotle’s Four Causes ........................................................ 239 Aleksandar Malecic, University of Nis, Serbia Related References .................................................................................................... ........................ 261 Compilation of References .................................................................................................... ........... 292 About the Contributors .................................................................................................... ................ 325 Index .................................................................................................... ............................................... 329 . (shrink)

Harun Farocki's films make use of a category of images the director calls “operational”, a term describing images, either photographic or computer-generated, that perform or participate in tasks, usually in military or industrial settings. Treatments of Farocki's films have frequently used the notion of the operational image uncritically, and without comparing Farocki's definition of these images with existing semiotic categories. This article seeks to situate Farocki's operational imagery within a theory of visual communication, and to explore the implications of automated (...) and instrumental imagery for theories of communication in general. Abandoning the focus in much Farocki scholarship on the representative properties of operational imagery, this article focuses on the world-shaping abilities of images that are integral to war and labour. Drawing primarily on Farocki's Eye / Machine I–III series ( Auge / Maschine, 2000–2003) the article then elaborates on the ways in which the world-shaping capacity of operational images conditions human perception and action. In particular, the limitations imposed by operational images upon human actors who interact with them, or live in environments orchestrated by them, reduce the essential role played by indeterminacy and interpretation in communication. (shrink)

In this paper Lucas comes back to Gödelian argument against Mecanism to clarify some points. First of all, he explains his use of Gödel’s theorem instead of Turing’s theorem, showing how Gödel’ theorem, but not Turing’s theorem, raises questions concerning truth and reasoning that bear on the nature of mind and how Turing’s theorem suggests that there is something that cannot be done by any computers but not that it can be done by human minds. He considers moreover how Gödel’s (...) theorem can be interpreted as a sophisticated form of the Cretan paradox, posed by Epimenides, able to escape the viciously self-referential nature of the Cretan paradox, and how it can be used against Mechanism as a schema of disproof. Finally, Lucas suggests some answers to the most recurrent criticisms against his argument: criticisms about the implicit idealisation in the way he set up the context between mind and machine; questions concerning modality and finitude, issues of transfinite arithmetic; questions concerning the need of formalizing rational inference and some questions about consistency. (shrink)

This article explores some of the ways in which the conceptual apparatus of A Thousand Plateaus, and especially its machinic metaphysics, can be connected to recent developments in computer modelling and social simulation, which provide new tools for thinking that are becoming increasingly popular among philosophers and social scientists. Conversely, the successful deployment of these tools provides warrant for the flat ontology articulated in A Thousand Plateaus and therefore contributes to the ‘reversal of Platonism’ for which Deleuze had called in (...) his earlier works, such as Logic of Sense. The first major section offers a brief exposition of some key concepts in A Thousand Plateaus in order to set the stage for the second and third major sections, which argue that the fabrication of a metaphysics of immanence can be accelerated by connecting its conceptual apparatus more explicitly to insights derived from philosophical analyses of computational modelling and simulation and the social scientific use of ‘assemblage theory’. The article concludes with a summary of the argument and a brief consideration of some of the potential ethical and political implications of this interdisciplinary engagement. (shrink)

The advantages and disadvantages of machine translation have been the subject of increasing debate among human translators lately because of the growing strides made in the last year by the newest major entrant in the field, Google Translate. The progress and potential of machine translation has been debated much through its history. But this debate actually began with the birth of machine translation itself. Behind this simple procedure lies a complex cognitive operation. To decode the meaning of (...) the source text in its entirety, the translator must interpret and analyze all the features of the text. The success of encoding of war rivals texts during WWII pushed the language experts to believe that translation of foreign languages could be realized based on these encoding principles. The cold war coincided with the invention of computers, and “cracking Russian” was one of the first tasks these machines were set. The competition towards establishing more business with different parts of the world incited advanced countries in technology to look for easy and quick ways for communication. Nevertheless, machine translation has proved helpful in more urgent situations as well. But, in my opinion, although computer scientists have toiled for decades to produce machine translation comparable to that rendered by humans, they have yet to succeed. (shrink)

Rule-based ethical theories like Kant's appear to be promising for machine ethics because of the computational structure of their judgments. On one formalist interpretation of Kant's categorical imperative, for instance, a machine could place prospective actions into the traditional deontic categories (forbidden, permissible, obligatory) by a simple consistency test on the maxim of action. We might enhance this test by adding a declarative set of subsidiary maxims and other "buttressing" rules. The ethical judgment is then an outcome of (...) the consistency test. While this kind of test can generate results, it may be vacuous in the sense that it would do no more than forbid obviously contradictory maxims of action. It is also possible that the kind of inference in such a rule-based system may be non-monotonic. I discuss these challenges to a rule-based machine ethics, starting from the framework of Kantian ethics. (shrink)

As art produced by autonomous machines becomes increasingly common, and as such machines grow increasingly sophisticated, we risk a confusion between art produced by a person but mediated by a machine, and art produced by what might be legitimately considered a machine artist. This distinction will be examined here. In particular, my argument seeks to close a gap between, on one hand, a philosophically grounded theory of art and, on the other hand, theories concerned with behavior, intentionality, expression, (...) and creativity in natural and artificial agents. This latter set of theories in some cases addresses creative behavior in relation to visual art, music, and literature, in the frequently overlapping contexts of philosophy of mind, artificial intelligence, and cognitive science. However, research in these areas does not typically address problems in the philosophy of art as a central line of inquiry. Similarly, the philosophy of art does not typically address issues pertaining to artificial agents. (shrink)

Machines are often employed in Heidegger’s philosophy as instances to illustrate specific features of modern technology. But what is it about machines that allows them to fulfill this role? This essay argues there is a unique ontological force to the machine that can be understood when looking at distinctions between techne and mechane in ancient Greek sources and applying these distinctions to a reading of Heidegger’s early thought on equipment and later thought on poiesis. Especially with respect to Heidegger’s (...) appropriation of Aristotle’s conception of dunamis, it becomes apparent from a Heideggerian perspective that machines provide an increase in capacity to its human users, but only so at a cost. This cost involves a problem of knowledge where the set of operations required in machine use results in the loss of understanding our dependency on being. The essay then concludes with a discussion of how this relation to machinic capacity is not merely pessimistic and deterministic, but indicates what might constitute a free relation to machines. (shrink)

What is life? Is it just the biologically familiar--birds, trees, snails, people--or is it an infinitely complex set of patterns that a computer could simulate? What role does intelligence play in separating the organic from the inorganic, the living from the inert? Does life evolve along a predestined path, or does it suddenly emerge from what appeared lifeless and programmatic? In this easily accessible and wide-ranging survey, Claus Emmeche outlines many of the challenges and controversies involved in the dynamic and (...) curious science of artificial life. Emmeche describes the work being done by an international network of biologists, computer scientists, and physicists who are using computers to study life as it could be, or as it might evolve under conditions different from those on earth. Many artificial-life researchers believe that they can create new life in the computer by simulating the processes observed in traditional, biological life-forms. The flight of a flock of birds, for example, can be reproduced faithfully and in all its complexity by a relatively simple computer program that is designed to generate electronic "boids." Are these "boids" then alive? The central problem, Emmeche notes, lies in defining the salient differences between biological life and computer simulations of its processes. And yet, if we can breathe life into a computer, what might this mean for our other assumptions about what it means to be alive? The Garden in the Machine touches on every aspect of this complex and rapidly developing discipline, including its connections to artificial intelligence, chaos theory, computational theory, and studies of emergence. Drawing on the most current work in the field, this book is a major overview of artificial life. Professionals and nonscientists alike will find it an invaluable guide to concepts and technologies that may forever change our definition of life. (shrink)

Full ectogenesis as the complete externalization of human reproduction by bypassing the bodily processes of gestation and childbirth can be considered the culmination of genetic and reproductive technologies. Despite its still being a hypothetical scenario, it has been discussed for decades as the ultimate means to liberate women from their reproductive tasks in society and hence finally end fundamental gender injustices generally. In the debate about the application of artificial wombs to achieve gender equality, one aspect is barely mentioned but (...) is of crucial relevance from a medical‐ethical perspective: whether and how could full ectogenesis be justified as a proper use of medicine? After characterizing the technology as a special form of human enhancement and as an extension of medical practice that goes beyond the traditional field of medicine, this paper critically assesses the theoretical possibilities of legitimizing this extension. We identify two ways of justification: either one argues that ectogenesis fulfils a proper goal of medicine (a justification we call pathologization), or one argues that the application of ectogenesis achieves a non‐medical goal (which we call medicalization). Because it is important from a medical‐ethical point of view to avoid an inappropriate instrumentalization or misuse of medicine and thus an undue medicalization of non‐medical problems, a set of necessary conditions has to be met. It is doubtful whether full ectogenesis for non‐medical purposes could fulfil these conditions. Rather, its comprehensive usage could be seen as a revolutionary modification of what it means to be human. (shrink)

This study focuses on a traditional business ethics question and aims to use advanced techniques to improve the performance of corporate fraud prediction. Based on the GONE framework, we adopt the machine learning model to predict the occurrence of corporate fraud in China. We first identify a comprehensive set of fraud-related variables and organize them into each category (i.e., Greed, Opportunity, Need, and Exposure) of the GONE framework. Among the six machine learning models tested, the Random Forest (RF) (...) model outperforms the other five models in corporate fraud prediction. Based on the RF model, we show that Exposure variables play a more important role in predicting corporate fraud than other input variables. These results highlight the importance of Exposure variables in corporate fraud prediction and promote the practical use of the machine learning model in solving business ethics questions. (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)

We certainly have the unconscious that we deserve, an unconscious for specialists, ready-made for an institutionalized discourse. I would rather see it as something that wraps itself around us in everyday objects, something that is involved with day-to-day problems, with the world outside. It would be the possible itself, open to the socius, to the cosmos...--from The Machinic Unconscious: Essays in SchizoanalysisIn his seminal solo-authored work The Machinic Unconscious, Félix Guattari lays the groundwork for a general pragmatics capable of resisting (...) the semiotic enslavement of subjectivity. Concluding that psychoanalytic theory had become part and parcel of a repressive, capitalist social order, Guattari here outlines a schizoanalytic theory to undo its capitalist structure and set the discipline back on its feet. Combining theoretical research from fields as diverse as cybernetics, semiotics, ethnology, and ethology, Guattari reintroduces into psychoanalysis a "polemical" dimension, at once transhuman, transsexual, and transcosmic, that brings out the social and political--the "machinic"--potential of the unconscious.To illustrate his theory, Guattari turns to literature and analyzes the various modes of subjectivization and semiotization at work in Proust's In Search of Lost Time, examining the novel as if he were undertaking a scientific exploration in the style of Freud or Newton. Casting Proust's figures as abstract mental objects, Guattari maps the separation between literature and science, elaborating along the way such major Deleuze-Guattarian concepts as "faciality" and "refrain," which would be unpacked in their subsequent A Thousand Plateaus: Capitalism and Schizophrenia.Never before available in English, The Machinic Unconscious has for too long been the missing chapter from Deleuze and Guattari's Anti-Oedipus project: the most important political extension of May 1968 and one of the most important philosophical contributions of the twentieth century. (shrink)

Existing evaluation metrics for machine translation lack crucial robustness: their correlations with human quality judgments vary considerably across languages and genres. We believe that the main reason is their inability to properly capture meaning: A good translation candidate means the same thing as the reference translation, regardless of formulation. We propose a metric that evaluates MT output based on a rich set of features motivated by textual entailment, such as lexical-semantic (in-)compatibility and argument structure overlap. We compare this metric (...) against a combination metric of four state-of-theart scores (BLEU, NIST, TER, and METEOR) in two different settings. The combination metric outperforms the individual scores, but is bested by the entailment-based metric. Combining the entailment and traditional features yields further improvements. (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.

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 this article I explore various facets of Nozick’s famous thought experiment involving the experience machine. Nozick’s original target is hedonism—the view that the only intrinsic prudential value is pleasure. But the argument, if successful, undermines any experientialist theory, i.e. any theory that limits intrinsic prudential value to mental states. I first highlight problems arising from the way Nozick sets up the thought experiment. He asks us to imagine choosing whether or not to enter the machine and uses (...) our choice (or rather the choice he assumes most people will have) as evidence against experientialist theories. But for this strategy to succeed it must be possible to distinguish between self-interested and non-self-interested reasons for declining to enter the machine, and there is no obvious way to do this without begging the question against the hedonist. In successive sections I then (a) consider a common misconception of Nozick’s conclusion (that he thinks machine life is the worst life), (b) consider different intuitions about what is important to well-being but missing from machine life, and finally (c) explain what “the experience requirement” is, and describe its relationship to debates about experientialist theories. (shrink)

Is ethics a computable function? Can machines learn ethics like humans do? If teaching consists in no more than programming, training, indoctrinating… and if ethics is merely following a code of conduct, then yes, we can teach ethics to algorithmic machines. But if ethics is not merely about following a code of conduct or about imitating the behavior of others, then an approach based on computing outcomes, and on the reduction of ethics to the compilation and application of a set (...) of rules, either a priori or learned, misses the point. Our intention is not to solve the technical problem of machine ethics, but to learn something about human ethics, and its rationality, by reflecting on the ethics that can and should be implemented in machines. Any machine ethics implementation will have to face a number of fundamental or conceptual problems, which in the end refer to philosophical questions, such as: what is a human being (or more generally, what is a worthy being); what is human intentional acting; and how are intentional actions and their consequences morally evaluated. We are convinced that a proper understanding of ethical issues in AI can teach us something valuable about ourselves, and what it means to lead a free and responsible ethical life, that is, being good people beyond merely “following a moral code”. In the end we believe that rationality must be seen to involve more than just computing, and that value rationality is beyond numbers. Such an understanding is a required step to recovering a renewed rationality of ethics, one that is urgently needed in our highly technified society. (shrink)

Gödel's theorem seems to me to prove that Mechanism is false, that is, that minds cannot be explained as machines. So also has it seemed to many other people: almost every mathematical logician I have put the matter to has confessed to similar thoughts, but has felt reluctant to commit himself definitely until he could see the whole argument set out, with all objections fully stated and properly met.1 This I attempt to do.