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 (...) class='Hi'>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 introduce the concept of implied optical perspective in deep learning computer vision systems. Taking the BBC's experimental television programme “Made by Machine: When AI met the Archive” as a case study, we trace a conceptual and material link between the system used to automatically “watch” the television archive and a specific type of photographic practice. From a computational aesthetics perspective, we show how deep learning machine vision relies on photography, its technical regimes (...) and epistemic advantages, and we propose a novel way to identify the latent camera through which the BBC archive was seen by machine. (shrink)

Machine vision is one of the main applications of artificial intelligence. In China, the machine vision industry makes up more than a third of the national AI market, and technologies like face recognition, object tracking and automated driving play a central role in surveillance systems and social governance projects relying on the large-scale collection and processing of sensor data. Like other novel articulations of technology and society, machine vision is defined, developed and explained by (...) different actors through the work of imagination. In this article, we draw on the concept of sociotechnical imaginaries to understand how Chinese companies represent machine vision. Through a qualitative multimodal analysis of the corporate websites of leading industry players, we identify a cohesive sociotechnical imaginary of machine vision, and explain how four distinct visual registers contribute to its articulation. These four registers, which we call computational abstraction, human–machine coordination, smooth everyday, and dashboard realism, allow Chinese tech companies to articulate their global ambitions and competitiveness through narrow and opaque representations of machine vision technologies. (shrink)

The presence of vegetation on railway tracks threatens track safety and longevity. However, vegetation inspections in Sweden are currently being carried out manually. Manually inspecting vegetation is very slow and time consuming. Maintaining an even quality standard is also very difficult. A machine vision-based approach is therefore proposed to emulate the visual abilities of the human inspector. Work aimed at detecting vegetation on railway tracks has been split into two main phases. The first phase is aimed at detecting (...) vegetation on the tracks using appropriate image analysis techniques. The second phase is aimed at detecting the rails in the image to determine the cover of vegetation that is present between the rails as opposed to vegetation present outside the rails. Results achieved in the current work indicate that the machine vision approach has performed reasonably well in detecting the presence/absence of vegetation on railway tracks when compared with a human operator. (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)

Information security is perceived as an important and vital aspect for the survival of any business. Preserving user identity and limiting the access of web resources only to the humans and restricting ‘bots’ is an ever challenging area of study. With the increase in computing power and development of newer approaches towards circumvention and reverse-engineering, the recognition gap present between the machines and the humans is said to be decreasing. Turing test and its modified versions are in place to deal (...) with such problems and ways to resolve them by developing complex algorithms for bot prevention systems like CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart). This paper will deal with the use of “Machine Vision” for judging the ability of the machines to compete with humans in breaking sequences of security systems like CAPTCHA. Reverse Turing test will be put to practise here. Complex image recognition technologies and novel approaches towards using Human interactive proofs (HIP) are discussed. The progress of Turing test over the past 60 years has been paid due attention at the end. After all this experimentation, it can be said that the current machine vision is quite poor and is far worse than it is expected to be. (shrink)

After a century of cinema, accounts of this cultural form see it as divided between documentation and animation (the real and the magical). Yet the challenge that cinema presented in terms of a relocation of perception from the eye to the machine has become occluded. The shock of cinema in its earliest manifestations resided in the body of the spectator, no longer the site of primary perception, but dependent on an other (the camera, the projector) lacking in human qualities. (...) This article argues that the newly configured body–machine relationship provided by cinema became a marginalized feature of cinematic culture, an ex-centric cinema relegated to the sub-fields of science and educational film. In the mid-20th century the project surfaces spectacularly in the work of pioneering designers Charles and Ray Eames, most poignantly in their film Powers of Ten (first made in 1968, remade in 1977), a journey into the cosmos and back again into the body of a man. Bringing together discourses of space travel, cartography, physics and cinema, the film moves us towards an understanding of visual culture as an apparatus of calculated possibilities, where visualization replaces representation. If we take the Powers of Ten as a non-representational film, an ex-centric cinematic practice, we uncover non-linear and non-representational ways of apprehending the relationship between bodies and matter. This literal line of flight is one path that cinema may have taken. Its presence, however, is detectable outside of the cinema, in the software programs of electronic cartography copyrighted as Google Earth. The human body is not made virtual by its engagement with calculated visualization but is in turn part of the field of enquiry, equally porous, and definable in various scales and in different dimensions. (shrink)

This article investigates the concept of the ground truth as both an epistemic and technical figure of knowledge that is central to discussions of machine vision and media techniques of visuality. While ground truth refers to a set of remote sensing practices, it has a longer history in operational photography, such as aerial reconnaissance. Building on a discussion of this history, this article argues that ground truth has shifted from a reference to the physical, geographical ground to the (...) surface of the images echoing earlier points raised by philosopher Jean-Luc Nancy that there is a ground of the image that is central to the task of analysis beyond representational practices. Furthermore, building on the practices of pattern recognition, composite imaging, and different interpretational techniques, we discuss contemporary practices of machine learning that mobilizes geographical earth observation datasets for experimental purposes, including tests such as “fake geography” as well as artistic practices, to show how ground truth is operationalized in such contexts of AI and visual arts. (shrink)

In many critical investigations of machine vision, the focus lies almost exclusively on dataset bias and on fixing datasets by introducing more and more diverse sets of images. We propose that machine vision systems are inherently biased not only because they rely on biased datasets but also because theirperceptual topology, their specific way of representing the visual world, gives rise to a new class of bias that we callperceptual bias. Concretely, we define perceptual topology as the (...) set of those inductive biases in machine vision systems that determine its capability to represent the visual world. Perceptual bias, then, describes the difference between the assumed “ways of seeing” of a machine vision system, our reasonable expectations regarding its way of representing the visual world, and its actual perceptual topology. We show how perceptual bias affects the interpretability of machine vision systems in particular, by means of a close reading of a visualization technique called “feature visualization”. We conclude that dataset bias and perceptual bias both need to be considered in the critical analysis of machine vision systems and propose to understand critical machine vision as an important transdisciplinary challenge, situated at the interface of computer science and visual studies/Bildwissenschaft. (shrink)

This study is to explore the gesture recognition and behavior tracking in swimming motion images under computer machine vision and to expand the application of moving target detection and tracking algorithms based on computer machine vision in this field. The objectives are realized by moving target detection and tracking, Gaussian mixture model, optimized correlation filtering algorithm, and Camshift tracking algorithm. Firstly, the Gaussian algorithm is introduced into target tracking and detection to reduce the filtering loss and (...) make the acquired motion posture more accurate. Secondly, an improved kernel-related filter tracking algorithm is proposed by training multiple filters, which can clearly and accurately obtain the motion trajectory of the monitored target object. Finally, it is proposed to combine the Kalman algorithm with the Camshift algorithm for optimization, which can complete the tracking and recognition of moving targets. The experimental results show that the target tracking and detection method can obtain the movement form of the template object relatively completely, and the kernel-related filter tracking algorithm can also obtain the movement speed of the target object finely. In addition, the accuracy of Camshift tracking algorithm can reach 86.02%. Results of this study can provide reliable data support and reference for expanding the application of moving target detection and tracking methods. (shrink)

This article uses Memo Akten’s art installation Learning to See to challenge the belief that machine learning and machine vision are neutral and objective technologies. Furthermore, this article follows Bernard Stiegler to contend that not only machine vision but also human vision is the result of constant training processes that rely directly on technology. From this perspective, human vision is always already technical. Likewise, in an age dominated growingly by machine learning technologies, (...) it is possible to speak not only of machine vision but also of a machinic imagination and a machinic unconscious, two notions that can be illustrated through Akten’s art installation. (shrink)

In the original publication of the article, the following paragraphs have been indented wrongly in the published article.

La vision par ordinateur est un des domaines de l’intelligence artificielle qui connaît les succès les plus fulgurants. Depuis une vingtaine d’années, les machines n’ont cessé de progresser dans leur capacité à extraire des informations à partir d’images et à identifier des objets. Mais faut-il en conclure que ces machines sont littéralement des machines voyantes, ou ne s’agit-il que d’une façon imagée de décrire des capacités de détection? Le présent article se propose de fournir les bases d’une réponse raisonnée (...) à cette question. Nous examinons successivement trois types de conditions d’attribution de la vision, et soutenons que le critère fonctionnaliste, en termes de représentations internes de stimuli visuels exploitables à diverses fins, doit être préféré aux critères behavioriste ou phénoménologique. Ce critère fonctionnaliste est ensuite appliqué à une des technologies les plus utilisées dans le domaine de la vision par ordinateur, celle des réseaux de neurones et plus particulièrement des réseaux convolutifs. Nous soutenons alors que de tels réseaux sont bien capables de voir, précisément dans la mesure où ils sont entraînés pour produire des représentations à partir de données visuelles. Ces représentations ont des traits spécifiques associés à un entraînement réussi : elles sont hiérarchiques, versatiles et robustes. De telles propriétés ont un intérêt théorique au-delà de leur domaine d’origine : nous suggérons pour finir qu’elles pourraient être utilisées pour spécifier la nature de la fonction de représentation et résoudre certains des problèmes classiques auxquels font face les théories téléosémantiques de la représentation comme celle de Dretske. (shrink)

A brilliant and comprehensive history of the creation of the modern Western mind. Soul Machine takes us back to the origins of modernity, a time when a crisis in religious authority and the scientific revolution led to searching questions about the nature of human inner life. This is the story of how a new concept—the mind—emerged as a potential solution, one that was part soul and part machine, but fully neither. In this groundbreaking work, award-winning historian George Makari (...) shows how writers, philosophers, physicians, and anatomists worked to construct notions of the mind as not an ethereal thing, but a natural one. From the ascent of Oliver Cromwell to the fall of Napoleon, seminal thinkers like Hobbes, Locke, Diderot, and Kant worked alongside often-forgotten brain specialists, physiologists, and alienists in the hopes of mapping the inner world. Conducted in a cauldron of political turmoil, these frequently shocking, always embattled efforts would give rise to psychiatry, mind sciences such as phrenology, and radically new visions of the self. Further, they would be crucial to the establishment of secular ethics and political liberalism. Boldly original, wide-ranging, and brilliantly synthetic, Soul Machine gives us a masterful, new account of the making of the modern Western mind. (shrink)

An early proponent of the social sciences, Frédéric Le Play, was the occupant of senior positions within the French state in the mid- to late 19th century. He was writing at a time when science was ascending. There was for him no doubt that scientific observation, correctly applied, would allow him unmediated access to the truth. It is significant that Le Play was the organizer of a number of universal expositions because these expositions were used as vehicles to demonstrate the (...) ascendant position of western civilization. The fabrication of linear time is a history of progress requiring a vision of history analogous to the view offered the spectator at a diorama. Le Play employed the design principles and spirit of the diorama in his formulations for the social sciences, and L’Exposition Universelle of 1867 used the technology wherever it could. Both the gaze of the spectators and the objects viewed are part and products of the same particular and unique historical formation. Ideas of perception cannot be separated out from the conditions that make them possible. Vision and its effects are inseparable from the observing subject who is both a product of a particular historical moment and the site of certain practices. (shrink)

In a spellbinding narrative that skillfully weaves together cutting-edge research among today's foremost scientists, theoretical physicist Michio Kaku--author of the bestselling book Hyperspace --presents a bold, exhilarating adventure into the science of tomorrow. In Visions, Dr. Kaku examines in vivid detail how the three scientific revolutions that profoundly reshaped the twentieth century--the quantum, biogenetic, and computer revolutions--will transform the way we live in the twenty-first century. The fundamental elements of matter and life--the particles of the atom and the nucleus of (...) the cell--have now been decoded, closing one of the great chapters of scientific history. But this is just the preface to an even more far-reaching scientific revolution, as we make the transition from being passive observers of the mysteries of nature to becoming masters of nature, able to manipulate matter, life, and intelligence to remold the world around us. In the first part of Visions, Dr. Kaku discusses the cyber future, when millions of microprocessors are scattered throughout our environment; when the iron principle that has ruled the computer industry, Moore's Law, finally collapses, forcing scientists to adopt startling new designs like DNA computers and quantum computers; and when artificial intelligence systems finally arrive. In the next section, Dr. Kaku shows how the decoding of DNA will allow us to conquer devastating genetic diseases, defeat many cancers at the molecular level, synthesize new medicines using virtual reality, grow new organs, conquer aging and reshape our genetic inheritance. Finally, he explores how quantum physicists will perfect new ways to harness the cosmic energy of the universe--from molecular machines to supermagnets that may energize a second industrial revolution, to powerful fusion engines that one day may take us to the stars. What makes Michio Kaku's vision of the future of science so compelling and authoritative is that it is based on the groundbreaking research already underway at leading laboratories around the world. Weaving interviews with over 150 scientists--several of them Nobel laureates--into a rich, inspiring narrative, Dr. Kaku reveals the growing consensus among key scientists about how science will likely evolve through the early, middle, and late years of the twenty-first century. An intimate, thrilling tour through the next century of science, Visions is a riveting, essential map to how scientists will reshape our future. (shrink)

This article attempts to demystify computer vision for novice programmers through a survey of new applications in the arts, system design considerations, and contemporary tools. It introduces the concept and gives a brief history of computer vision within interactive art from Myron Kruger to the present. Basic techniques of computer vision such as detecting motion and object tracking are discussed in addition to various software applications created for exploring the topic. As an example, the results of a (...) one-week machine vision workshop are presented to show how designers are able to apply their skills toward creating novel uses of these technologies. The article concludes with a listing of code for basic computer vision techniques. (shrink)

It is only in the last three centuries that the formidable knowledge-making machine we call modern science has transformed our way of life and our vision of the universe - two thousand years after the invention of law, philosophy, drama and mathematics. Why did we take so long to invent science? And how has it proved to be so powerful?The Knowledge Machine gives a radical answer, exploring how science calls on its practitioners to do something apparently irrational- (...) strip away all previous knowledge - such as theological, metaphysical or political beliefs - and channel unprecedented energy into observation and experiment. In times of climate extremes, novel diseases and rapidly advancing technology, Strevens contends that we need more than ever to grasp the inner workings of our knowledge machine. (shrink)

서비스 로봇이나 자율주행자동차처럼 현실의 공간에서 작동하는 기계가 임무를 성공적으로 수행하기 위하여 갖추어야 할 조건은 그것이 처한 환경의 상태를 파악하는 능력, 곧 지각의 능력이다. 이 논문은 이런 기계 지각, 특히 인간을 대행하도록 의도된 기계의 지각이 충족해야 할 조건들을 검토한다. 이러한 시도는 오늘의 사회가 집단적으로 추진하고 있는 공학 프로젝트에서 기술의 지향점을 환기시키면서 그것을 향한 실천을 구체화하는 논의라는 의미를 지닌다. 공학윤리의 원칙에 명시된 최우선의 가치를 고려할 때, 인간을 대행할 인공물은 우리가 아는 범위에서 가장 안전한 방식으로 구성되어야 하고, 이를 위하여 기계 시각을 비롯한 인공물의 (...) 지각은 일차적으로 그것이 대행할 인간의 지각을 닮은 결과를 산출하도록 설계, 제작되어야 한다. 인간의 지각은 자연의 역사가 부여한 여러 흥미로운 속성들을 가지고 있다. 특히 이 논문은 지각의 대상을 개념적 범주들을 적용해 판별하는 방식, 지각에 나타나는 다양한 항등성의 측면들, 인간의 지각에 나타나는 행지주의적 특성에 주목한다. 이 세 요소는 자율주행자동차를 비롯하여 이 논문이 고려한 적용의 영역들에서 모두 뚜렷한 유관성을 드러낸다. 이로부터, 이런 똑똑한 인공물을 설계, 제작하는 과정에서 인간 지각의 이러한 속성들이 실현되거나 아니면 적어도 실질적인 손실 없이 대체되는지를 살펴야 한다는 당위가 도출된다. (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)

Machines will attain human levels of intelligence by the year 2040, predicts robotics expert Hans Moravec. And by 2050, they will have far surpassed us. In this mind-bending new book, Hans Moravec takes the reader on a roller coaster ride packed with such startling predictions. He tells us, for instance, that in the not-too-distant future, an army of robots will displace workers, causing massive, unprecedented unemployment. But then, says Moravec, a period of very comfortable existence will follow, as humans benefit (...) from a fully automated economy. And eventually, as machines evolve far beyond humanity, robots will supplant us. But if Moravec predicts the end of the domination by human beings, his is not a bleak vision. Far from railing against a future in which machines rule the world, Moravec embraces it, taking the startling view that intelligent robots will actually be our evolutionary heirs. "Intelligent machines, which will grow from us, learn our skills, and share our goals and values, can be viewed as children of our minds." And since they are our children, we will want them to outdistance us. In fact, in a bid for immortality, many of our descendants will choose to transform into "ex humans," as they upload themselves into advanced computers. We will become our children and live forever. In his provocative new book, the highly anticipated follow-up to his bestselling volume Mind Children, Moravec charts the trajectory of robotics in breathtaking detail. A must read for artificial intelligence, technology, and computer enthusiasts, Moravec's freewheeling but informed speculations present a future far different than we ever dared imagine. (shrink)

In recent developments in Artificial Intelligence and especially in robotics we can observe a tendency towards building intelligent artefacts that are meant to be social, to have ‘human social’ characteristics like emotions, the ability to conduct dialogue, to learn, to develop personality, character traits, and social competencies. Care, entertainment, pet and educational robots are conceptualised as friendly, understanding partners and credible assistants which communicate ‘naturally’ with users, show emotions and support them in everyday life. Social robots are often designed to (...) interact physically, affectively and socially with humans in order to learn from them. To achieve this goal, roboticists often model the human‐robot interaction on early caregiver‐infant interactions. In this paper I want to analyse prominent visions of these ‘socio‐emotional’ machines as well as early prototypes and commercial products with regard to the human‐machine interface. By means of this I will ask how feminist critiques of technology could be applied to the field of social robotics in which concepts like sociality or emotion are crucial elements while, at the same time, these concepts play an important role in feminist critiques of technology. (shrink)

Conventional imagers and almost all vision processes use and rely on theories that are based on the principle of static image-frames. A frame is a 2D matrix that represents the spatial locations of intensities of a scene projected on the imager. The notion of a frame itself is so embedded in machine vision, that it is usually taken for granted that this is how biological systems store light information. This paper presents a biosinpired event-based image formation principle, (...) which output data rely on an asynchronous acquisition process. The generated information is stored in temporal volumes, which size and information depend only on the dynamic content of observed scenes. Practical analysis of such information will shows that the processing of visual information can only be based on a semiotic process. The paper also provides a general definition of the notion of visual features as the interpretation of signs according to different possible readings of the codified visual signal. (shrink)

The loss or absence of vision is probably one of the most incapacitating events that can befall a human being. The importance of vision for humans is also reflected in brain anatomy as approximately one third of the human brain is devoted to vision. It is therefore unsurprising that throughout history many attempts have been undertaken to develop devices aiming at substituting for a missing visual capacity. In this review, we present two concepts that have been prevalent (...) over the last two decades. The first concept is sensory substitution, which refers to the use of another sensory modality to perform a task that is normally primarily sub-served by the lost sense. The second concept is cross-modal plasticity, which occurs when loss of input in one sensory modality leads to reorganization in brain representation of other sensory modalities. Both phenomena are training-dependent. We also briefly describe the history of blindness from ancient times to modernity, and then proceed to address themeansthat have been used to help blind individuals, with an emphasis on modern technologies, invasive (various type of surgical implants) and non-invasive devices. With the advent of brain imaging, it has become possible to peer into the neural substrates of sensory substitution and highlight the magnitude of the plastic processes that lead to a rewired brain. Finally, we will address the important question of the value and practicality of the available technologies and future directions. (shrink)

Examines key narratives animating the techno-progressive rhetoric of the human enhancement movement, arguing that enhancement and transhumanist discourse performs distinctly mythic functions. They cast a vision of a technological future involving enhanced posthumans, immortality, human merger with machines and space colonization.

Paul Churchland's book is an entertaining and instructive advertisement for a "neurocomputational" vision of how the brain works. While we agree with its general thrust, and commend its lucid pedagogy on a host of difficult topics, we note that such pedagogy often exploits artificially heightened contrast, and sometimes the result is a misleading caricature instead of a helpful simplification. In particular, Churchland is eager to contrast the explanation of consciousness that can be accomplished by his "aspiring new structural and (...) dynamic cognitive prototype: recurrent PDP networks" with what strikes him as the retrograde introduction by Dennett of a virtual von Neumannesque machine--a "failed prototype"--as the key element in an explanation of human consciousness. We will try to show that by oversimplifying Dennett's alternative, he has taken a potential supplement to his own view--a much needed supplement--and transformed it in his imagination into a subversive threat. In part 1, we will expose and correct the mistaken contrasts. In part 2, we will compare the performance of the two views on Churchland's list of seven features of consciousness any theory must account for, showing that Dennett's account provides more than Churchland has recognized, and indeed offers answers to key questions that Churchland's account is powerless to address. At that point, Churchland's project and Dennett's could be seen to collaborate in a useful division of labor instead of being in mortal combat, were it not for what appears to be a fairly major disagreement about consciousness in non-human animals. Part 3 briefly examines this issue. It may be due to a misunderstanding, which when cleared up might restore the happy prospect of unification. (shrink)

What is the most important reason for using Computer Vision methods in humanities research? In this article, I argue that the use of numerical representation and data analysis methods offers a new language for describing cultural artifacts, experiences and dynamics. The human languages such as English or Russian that developed rather recently in human evolution are not good at capturing analog properties of human sensorial and cultural experiences. These limitations become particularly worrying if we want to compare thousands, millions (...) or billions of artifacts—i.e. to study contemporary media and cultures at their new twenty-first century scale. When we instead use numerical measurements of image properties standard in Computer Vision, we can better capture details of a single artifact as well as visual differences between a number of artifacts–even if they are very small. The examples of visual dimensions that numbers can capture better then languages include color, shape, texture, contours, composition, and visual characteristics of represented faces, bodies and objects. The methods of finding structures and relationships in large numerical datasets developed in statistics and machine learning allow us to extend this analysis to very big datasets of cultural objects. Equally importantly, numerical image features used in Computer Vision also give us a new language to represent gradual and continuous temporal changes—something which natural languages are also bad at. This applies to both single artworks such as a film or a dance piece and also to changes in visual characteristics in millions of artifacts over decades or centuries. (shrink)

What is colour vision for? In the popular imagination colour vision is for “seeing the colours” — adding hue to the achromatic world of shape, depth and motion. On this view colour vision plays little more than an ornamental role, lending glamour to an otherwise monochrome world. This idea has guided much theorising about colour within vision science and philosophy. However, we argue that a broader approach is needed. Recent research in the psychology of colour demonstrates (...) that colour vision is integral to a variety of visual processes, helping us to perform many types of visual tasks. We discuss some of this research and consider its implications for philosophical theories of colour. (shrink)

This paper extends three decades of work arguing that researchers who discuss consciousness should not restrict themselves only to (adult) human minds, but should study (and attempt to model) many kinds of minds, natural and artificial, thereby contributing to our understanding of the space containing all of them. We need to study what they do or can do, how they can do it, and how the natural ones can be emulated in synthetic minds. That requires: (a) understanding sets of requirements (...) that are met by different sorts of minds, i.e. the niches that they occupy, (b) understanding the space of possible designs, and (c) understanding complex and varied relationships between requirements and designs. Attempts to model or explain any particular phenomenon, such as vision, emotion, learning, language use, or consciousness lead to muddle and confusion unless they are placed in that broader context. A methodology for making progress is summarised and a novel requirement proposed for a theory of how human minds work: the theory should support a single generic design for a learning, developing system that, in addition to meeting familiar requirements, should be capable of developing different and opposed philosophical viewpoints about consciousness, and the so-called hard problem. In other words, we need a common explanation for the mental machinations of mysterians, materialists, functionalists, identity theorists, and those who regard all such theories as attempting to answer incoherent questions. No designs proposed so far come close. (shrink)

In response to growing concerns of bias, discrimination, and unfairness perpetuated by algorithmic systems, the datasets used to train and evaluate machine learning models have come under increased scrutiny. Many of these examinations have focused on the contents of machine learning datasets, finding glaring underrepresentation of minoritized groups. In contrast, relatively little work has been done to examine the norms, values, and assumptions embedded in these datasets. In this work, we conceptualize machine learning datasets as a type (...) of informational infrastructure, and motivate a genealogy as method in examining the histories and modes of constitution at play in their creation. We present a critical history of ImageNet as an exemplar, utilizing critical discourse analysis of major texts around ImageNet’s creation and impact. We find that assumptions around ImageNet and other large computer vision datasets more generally rely on three themes: the aggregation and accumulation of more data, the computational construction of meaning, and making certain types of data labor invisible. By tracing the discourses that surround this influential benchmark, we contribute to the ongoing development of the standards and norms around data development in machine learning and artificial intelligence research. (shrink)

Paul Churchland's book (hereafter ER)is an entertaining and instructive advertisement for a "neurocomputational" vision of how the brain (and mind) works. While we agree with its general thrust, and commend its lucid pedagogy on a host of difficult topics, we note that such pedagogy often exploits artificially heightened contrast, and sometimes the result is a misleading caricature instead of a helpful simplification. In particular, Churchland is eager to contrast the explanation of consciousness that can be accomplished by his "aspiring (...) new structural and dynamic cognitive prototype: recurrent PDP networks" (p.266) with what strikes him as the retrograde introduction by Dennett of a virtual von Neumannesque machine--a "failed prototype"--as the key element in an explanation of human consciousness (in Consciousness Explained, 1991, hereafter, CE). We will try to show that by oversimplifying Dennett's alternative, he has taken a potential supplement to his own view--a much needed supplement--and transformed it in his imagination into a subversive threat. In part 1, we will expose and correct the mistaken contrasts. In part 2, we will compare the performance of the two views on Churchland's list of seven features of consciousness any theory must account for, showing that Dennett's account provides more than Churchland has recognized, and indeed offers answers to key questions that Churchland's account is powerless to address. At that point, Churchland's project and Dennett's could be seen to collaborate in a useful division of labor instead of being in mortal combat, were it not for what appears to be a fairly major disagreement about consciousness in non-human animals. Part 3 briefly examines this issue. It may be due to a misunderstanding, which when cleared up might restore the happy prospect of unification. (shrink)

What has philosophy become after computation? Critical positions about what counts as intelligence, reason, and thinking have addressed this question by reenvisioning and pushing debates about the modern question of technology towards new radical visions. Artificial intelligence, it is argued, is replacing transcendental metaphysics with aggregates of data resulting in predictive modes of decision-making, replacing conceptual reflection with probabilities. This article discusses two main positions. While on the one hand, it is feared that philosophy has been replaced by cybernetic metaphysics, (...) on the other hand it is claimed that only the coconstitution of philosophy and automation challenges modern transcendental reason and colonial capital. As Donna Haraway pointed out, cybernetic circuits of communication have constructed counterfactual ontologies against the master narrative of the human. This article addresses recent attempts at redeveloping a critique of natural philosophy that explains cybernetic metaphysics beyond the universal master narratives of mechanicism and vitalism. This article suggests that the recursive system of nature and technology also needs to account for the problem of philosophical decision, which will be explored in terms of mediatic thinking, instrumentality, and automation. This article follows insights from the movie Get Out (2017) to argue that the model of philosophical decision relies on a servomechanic understanding of the medium of thought, based on the colonial abstraction of value in the prosthetic extension of the slave-machine. It explores the nonphilosophical envisioning of automation in terms of a counterfactual theorisation of the negative negation of the medium and argues for a nonoptical darkness entering the space of thinking. Philosophy and automation are neither coupled nor set in opposition as if in a ceaseless mirroring. Instead, both philosophy and automation must transform their self-determining axiomatics in order to host the heretic activities of machine propositions. (shrink)

The essay below is excerpted from my forthcoming book, At Any Cost—A Guide to The Transhumanist Wager and the Ideas of Zoltan Istvan. It is an examination of, Jethro Knights, the iconoclastic and highly controversial protagonist of Zoltan’s philosophical novel, who views himself as already having partially transcended his human origins and conducts himself as though he is a highly evolved machine intelligence, possessed of a moral system an A.I. would likely adopt, according to Jethro’s vision of the (...) post-human future he is fighting to bring about. (shrink)

The Internet provides access to a global space of information assets and computational services. It also, however, serves as a platform for social interaction (e.g., Facebook) and participatory involvement in all manner of online tasks and activities (e.g., Wikipedia). There is a sense, therefore, that the Internet yields an unprecedented form of access to the human social environment: it provides insight into the dynamics of human behavior (both individual and collective), and it additionally provides access to the digital products of (...) human cognitive labor (again, both individual and collective). Such access is interesting from the standpoint of research into machine intelligence, for the human social environment looks to be of crucial importance when it comes to the evolutionary and developmental origins of the human mind. In the present paper, we develop a theoretical account that sees the Internet as providing opportunities for online systems to function as socially-situated agents. The result is a vision of machine intelligence in which advanced forms of cognitive competence are seen to arise from the creation of a new kind of digital socio-ecological niche. The present paper attempts to detail this vision with respect to the notion of socially-scaffolded cognition. It also describes some of the forms of machine learning that may be required to enable online systems to press maximal cognitive benefit from their new-found informational contact with the human social world. (shrink)