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)

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)

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)

Cinema and Machine Vision unfolds the aesthetic, epistemic, and ideological dimensions of machine-seeing films and television using computers. With its critical-technical approach, this book presents to the reader key new problems that arise as AI becomes integral to visual culture. The book theorises machine vision through a selection of aesthetics, film theory, and applied machine learning research, dispelling widely held assumptions about computer systems designed to watch and make images on our behalf. -/- At (...) its heart, Cinema and Machine Vision is an invitation for film and media scholars to critically engage with AI at a technical level, a prompt for scientists and engineers working with images and cultural data to critically reflect on where their assumptions about vision come from, and a joint recognition of the fruitful problems of working together to understand the algorithmic governance of the visual. (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)

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)

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 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)

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

Computer vision is one of AI’s most successful fields. In the last twenty years, machines have become increasingly good at extracting information from images and at identifying objects. But does this mean that machines really can see, or is computer vision just a fancy metaphor for object detection? This paper aims to provide a reasoned answer to the question. First, three criteria for vision attribution are reviewed and it is argued that a functionalist criterion, in terms of (...) exploitable internal representations based on visual stimuli, fares better than behaviourist or phenomenological ones. The functionalist criterion is then applied to vision algorithms based on neural networks and it is argued that such machines can indeed see, insofar as neural networks are precisely trained to generate representations of the visual data they are fed with. Those representations present the specific traits associated with successful training: They are hierarchical, robust, and versatile. We argue that these properties may be used as further constraints on representational devices in general, helping to solve some of the classical issues faced by teleosemantic theories of representation such as that expounded by Dretske. (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)

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)

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)

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)

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)

Accurate measurement of livestock weight is a primary indicator in the meat industry to increase the economic gain. In lambs, the weight of a live animal is still usually estimated manually using traditional scales, resulting in a tedious process for the experienced assessor and stressful for the animal. In this paper, we propose a solution to this problem using computer vision techniques; thus, the proposed procedure estimates the weight of a lamb by analysing its zenithal image without interacting with (...) the animal, which speeds up the process and reduces weighing costs. It is based on a data-driven decision support system that uses RGB-D machine vision techniques and regression models. Unlike existing methods, it does not require walk-over-weighing platforms or special and expensive infrastructures. The proposed method includes a decision support system that automatically rejects those images that are not appropriate to estimate the lamb weight. After determining the body contour of the lamb, we compute several features that feed different regression models. Best results were achieved with Extra Tree Regression ($R^{2}$=91.94%), outperforming the existing techniques. Using only an image, the proposed approach can identify with a minimum error the optimal weight of a lamb to be slaughtered, so as to maximise the economic profit. (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)

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)

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)

Predictions concerning postindustrial society include that of workers serving as machine monitors. That concept is explored in this article in respect to faculty in higher education serving as monitors of computers that are executing instructional programs. Questions concerning changes in faculty roles and the control of educational quality are addressed. Alfred Bork’s vision of asynchronous learning systems is elaborated, and that alternative is compared to the concept of machine monitoring. It is concluded that monitoring in higher education (...) is not likely unless student demand for distance learning is great, but in that case, monitoring would be superior to proposals for automated asynchronous learning systems. (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)

This commentary tests a methodology proposed by Munk et al. (2022) for using failed predictions in machine learning as a method to identify ambiguous and rich cases for qualitative analysis. Using a dataset describing actions performed by fictional characters interacting with machine vision technologies in 500 artworks, movies, novels and videogames, I trained a simple machine learning algorithm (using the kNN algorithm in R) to predict whether or not an action was active or passive using only (...) information about the fictional characters. Predictable actions were generally unemotional and unambiguous activities where machine vision technologies were treated as simple tools. Unpredictable actions, that is, actions that the algorithm could not correctly predict, were more ambivalent and emotionally loaded, with more complex power relationships between characters and technologies. The results thus support Munk et al.'s theory that failed predictions can be productively used to identify rich cases for qualitative analysis. This test goes beyond simply replicating Munk et al.'s results by demonstrating that the method can be applied to a broader humanities domain, and that it does not require complex neural networks but can also work with a simpler machine learning algorithm. Further research is needed to develop an understanding of what kinds of data the method is useful for and which kinds of machine learning are most generative. To support this, the R code required to produce the results is included so the test can be replicated. The code can also be reused or adapted to test the method on other datasets. (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)

Based on detailed descriptions of human–machine ensembles, this article explores how humans and machines work together to see specific things and unsee others, and how they come to co-configure one another. For seeing is not an automated function; whether one is a human or a machine, vision is gradually enskilled and mutually co-constituted. The analysis intersects three different ways of human–machine seeing to shed further light on the workings of each one: an airport, where facial recognition (...) algorithms collaborate with border guards to grant passage to particular travellers and not to others; a luggage-scanning system, where potential security threats are assessed by a complex of X-rays and human intro-spection; and a hospital operating room, where human–machinic surgical robots find their way and operate on the insides of human bodies, touching only by seeing. In these examples, human and machine ways of seeing merge together, seeing in particular apparatuses of material, political, organisational, economic and fleshy components. The article analyses the practical work of human–machinic collaboration and explores how the different material and social constituents, not necessarily always working from the same agenda, come to configure what can be seen and sensed and what cannot. (shrink)

This article addresses shared themes in the writing of Saint Paul and the work of the science fiction writer Philip K. Dick. Much recent philosophical interest in Saint Paul focuses on his contemporary significance as a radical political thinker, following Jacob Taubes' influential late work, The Political Theology of Paul. Assessments of Paul's writing in this context (e.g. by Agamben, Badiou, Milbank) highlight the various ways in which he uses fictionalizing, for example in setting up the tension between the present (...) world and a messianic future, in the role he assigns to faith, and in the importance he assigns to the counter-factuality of resurrection. Yet the common thread of fictionalizing running through these themes has not been explicitly discussed. Meanwhile, the supposed `religious turn' in Dick's late writing has often been taken to have less political significance than his earlier science fiction. Considering Paul alongside Philip K. Dick, this article will attempt to bring out this central role of fictionalizing in the religious experiences of both. Like Paul, Dick experienced a visionary encounter with a God-like entity that shaped his interests and writing for the remainder of his life, and developed his own soteriology in response to what he perceived as the continued existence of (the Roman) Empire in modernity. Bringing out the mutual complementarity of Dick and Paul is facilitated by a framework derived from Henri Bergson's Two Sources of Religion, which theorizes the relation between mechanization as a human tendency characterizing both imperialism and industrialization, and fabulation as a human faculty for using fiction for the jointly immanent-transcendent purposes of survival/salvation. In this context, the diverse modes of fictionalizing employed by both Dick and Paul, including their unconsciously produced visions, may be understood as part of an ongoing, continually renewed strategy of revolutionary transformation of both self and world. (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 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)

Imagine a world where machines can see and understand the world the way humans do. Rapid progress in artificial intelligence has led to smartphones that recognize faces, cars that detect pedestrians, and algorithms that suggest diagnoses from clinical images, among many other applications. The success of computer vision is founded on a deep understanding of the neural circuits in the brain responsible for visual processing. This book introduces the neuroscientific study of neuronal computations in visual cortex alongside of the (...) psychological understanding of visual cognition and the burgeoning field of biologically-inspired artificial intelligence. Topics include the neurophysiological investigation of visual cortex, visual illusions, visual disorders, deep convolutional neural networks, machine learning, and generative adversarial networks among others. It is an ideal resource for students and researchers looking to build bridges across different approaches to studying and developing visual systems. (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)

The photographic apparatus whose emergence is located in the mid-nineteenth century has not been perfectly located within the history of technology, sometimes considered as a simple tool or instrument whose utility was mainly in the field of scientific research, other times giving it the status of machine, accentuating this time the automatism of its operation. Both visions seem insufficient to us since both one and the other present a certain partiality in the understanding of the apparatus, which should not (...) be reduced to its mere optical character or to its automatism, since this is also a form of recording, of memory. Our interest will focus on demonstrating how photography should be thought of as “apparatus”, that is, as a complex element within the history of technology; that not only was able to perfect our vision considered as deficient, but at the same time was able to grant a new temporality and a specific type of perception to an entire era. (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)