Quilty-Dunn et al. argue that deep convolutional neural networks (DCNNs) optimized for image classification exemplify structural disanalogies to human vision. A different kind of artificial vision – found in reinforcement-learning agents navigating artificial three-dimensional environments – can be expected to be more human-like. Recent work suggests that language-like representations substantially improves these agents’ performance, lending some indirect support to the language-of-thought hypothesis (LoTH).

The article considers the method of factor cluster analysis which allows automatically retrain the onboard recognition system of an unmanned aerial system. The task of informational synthesis of an on-board system for identifying frames is solved within the information-extreme intellectual technology of data analysis, based on maxi- mizing the informational ability of the system during machine learning. Based on the functional approach to modeling cognitive processes inherent to humans during forming and making classification decisions, it was proposed a categorical model (...) in the form of a direct graph. According to this model, the algorithmic support of the information extreme factor cluster analysis is developed. It allows automatically retrain the system when expanding the alphabet of recognition classes. According to this algorithm, the on-board recognition system preliminarily carries out the information-extremal machine learning of recognition classes of relatively low power. When new classes appear, their unclassified structured recognition attribute vectors form additional learning matrixes. After reaching a representational volume, additional learning matrix joins the input learning matrix and the on-board recognition system is retrained. Forming additional learning matrixes of new recognition classes is carried out by the agglomerative algorithm of cluster analysis of unclassified vectors by k-means clustering. As a criterion of optimizing machine-learning parameters, we used the modified Kullback criterion which is a functional of the exact characteristics of classification solutions. To increase the functional efficiency of factor cluster analysis, it is proposed to increase the depth of machine learning by optimizing the parameters of image processing frames. (shrink)

Amblyopia, or lazy eye, is a neurological vision disorder that studies have shown to affect two to five percent of the population. Current methods of treatment produce the best visual outcome, if the condition is identified early in the patient's life. Several early screening procedures are aimed at finding the condition while the patient is a child, including an automated vision screening system. This paper aims to use artificial intelligence techniques to automatically identify children who are at (...) risk for developing the amblyopic condition and should therefore be referred to a specialist, i.e., pediatric ophthalmologist. Three techniques, namely, decision tree learning, random forest, and artificial neural network, are studied in this paper in terms of their effectiveness, using metrics of sensitivity, specificity, and accuracy. The features used by the techniques are extracted from images of patient eyes and are based on the color information. The efficacy of pixel color data is investigated with respect to the measurement of the rate of change of the color in the iris and pupil, i.e., color slope features. A 10-fold stratified cross validation procedure is used to compare the effectiveness of the three AI techniques in this medical application domain. (shrink)

During 2018, as part of a research project funded by the Deviant Practice Grant, artist Bruno Moreschi and digital media researcher Gabriel Pereira worked with the Van Abbemuseum collection (Eindhoven, NL), reading their artworks through commercial image-recognition (computer vision) artificial intelligences from leading tech companies. The main takeaways were: somewhat as expected, AI is constructed through a capitalist and product-focused reading of the world (values that are embedded in this sociotechnical system); and that this process of using AI (...) is an innovative way for doing institutional critique, as AI offers an untrained eye that reveals the inner workings of the art system through its glitches. This paper aims to regard these glitches as potentially revealing of the art system, and even poetic at times. We also look at them as a way of revealing the inherent fallibility of the commercial use of AI and machine learning to catalogue the world: it cannot comprehend other ways of knowing about the world, outside the logic of the algorithm. But, at the same time, due to their “glitchy” capacity to level and reimagine, these faulty readings can also serve as a new way of reading art; a new way for thinking critically about the art image in a moment when visual culture has changed form to hybrids of human–machine cognition and “machine-to-machine seeing”. (shrink)

Block (Trends Cogn Sci 7:285–286, 2003) and Prinz (PSYCHE 12:1–19, 2006) have defended the idea that SSD perception remains in the substituting modality (auditory or tactile). Hurley and Noë (Biol Philos 18:131–168, 2003) instead argued that after substantial training with the device, the perceptual experience that the SSD user enjoys undergoes a change, switching from tactile/auditory to visual. This debate has unfolded in something like a stalemate where, I will argue, it has become difficult to determine whether the perception acquired (...) through the coupling with an SSD remains in the substituting or the substituted modality. Within this puzzling deadlock two new approaches have been recently suggested. Ward and Meijer (Conscious Cogn 19:492–500, 2010) describe SSD perception as visual-like but characterize it as a kind of artificially induced synaesthesia. Auvray et al. (Perception 36:416–430, 2007) and Auvray and Myin (Cogn Sci 33:1036–1058, 2009) suggest that SSDs let their users experience a new kind of perception. Deroy and Auvray (forthcoming) refine this position, and argue that this new kind of perception depends on pre-existing senses without entirely aligning with any of them. So, they have talked about perceptual experience in SSDs as going "beyond vision". In a similar vein, MacPherson (Oxford University Press, New York, 2011a) claims that “if the subjects (SSD users) have experiences with both vision-like and touch-like representational characteristics then perhaps they have a sense that ordinary humans do not” (MacPherson in Oxford University Press, New York, 2011a, p. 139). (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)

Bringing together literary scholars, computer scientists, ethicists, philosophers of mind, and scholars from affiliated disciplines, this collection of essays offers important and timely insights into the pasts, presents, and, above all, possible futures of Artificial Intelligence. This book covers topics such as ethics and morality, identity and selfhood, and broader issues about AI, addressing questions about the individual, social, and existential impacts of such technologies. Through the works of science fiction authors such as Isaac Asimov, Stanislaw Lem, Ann Leckie, (...) Iain M. Banks, and Martha Wells, alongside key visual productions such as Ex Machina, Westworld, and Her, contributions illustrate how science fiction might inform potential futures as well as acting as a springboard to bring disciplinary knowledge to bear on significant developments of Artificial Intelligence. Addressing a broad, interdisciplinary audience, both expert and non-expert readers gain an in-depth understanding of the wide range of pressing issues to which Artificial Intelligence gives rise, and the ways in which science fiction narratives have been used to represent them. Using science fiction in this manner enables readers to see how even fictional worlds and imagined futures have very real impacts on how we understand these technologies. As such, readers are introduced to theoretical positions on Artificial Intelligence through fictional works as well as encouraged to reflect on the diverse aspects of Artificial Intelligence through its many philosophical, social, legal, scientific, and cultural ramifications. (shrink)

Animate vision systems have gaze control mechanisms that can actively position the camera coordinate system in response to physical stimuli. Compared to passive systems, animate systems show that visual computation can be vastly less expensive when considered in the larger context of behavior. The most important visual behavior is the ability to control the direction of gaze. This allows the use of very low resolution imaging that has a high virtual resolution. Using such a system in a controlled way (...) provides additional constraints that dramatically simplify the computations of early vision. Another important behavior is the way the environment “behaves‘. Animate systems under real-time constraints can further reduce their computational burden by using environmental cues that are perspicuous in the local context. A third source of economy is introduced when behaviors are learned. Because errors are rarely fatal, systems using learning algorithms can amortize computational cost over extended periods. Further economies can be achieved when the learning system uses indexical reference, which is a form of dynamic variable binding. Animate vision is a natural way of implementing this dynamic binding. (shrink)

Apocalyptic AI, the hope that we might one day upload our minds into machines and live forever in cyberspace, has become commonplace. This view now affects robotics and AI funding, play in online games, and philosophical and theological conversations about morality and human dignity.

In this 60th anniversary of Business & Society essay, we seek to make three main contributions at the intersection of governance and artificial intelligence. First, we aim to illuminate some of the deeper social, legal, organizational, and democratic challenges of rising AI adoption and resulting algorithmic power by reviewing AI research through a governance lens. Second, we propose an AI governance framework that aims to better assess AI challenges as well as how different governance modalities can support AI. At (...) the heart of our framework lies the governance forces that apply to institutions, organizations, and individuals, who ultimately provide, regulate, and use AI decision-making. We discuss how businesses may harness AI’s economic power through governance solutions without creating or amplifying societal biases and inequalities. Third, as part of our section on future research, we identify a set of governance trade-offs in AI adoption, suggest future research avenues to conceptually strengthen research on the governance of AI, and lay out key policy recommendations. (shrink)

When is it ethically acceptable to use artificial agents in health care? This article articulates some criteria for good care and then discusses whether machines as artificial agents that take over care tasks meet these criteria. Particular attention is paid to intuitions about the meaning of ‘care’, ‘agency’, and ‘taking over’, but also to the care process as a labour process in a modern organizational and financial-economic context. It is argued that while there is in principle no objection (...) to using machines in medicine and health care, the idea of them functioning and appearing as ‘artificial agents’ is problematic and attends us to problems in human care which were already present before visions of machine care entered the stage. It is recommended that the discussion about care machines be connected to a broader discussion about the impact of technology on human relations in the context of modernity. (shrink)

Focused on city-scale automation, and using self-driving cars (SDCs) as a case study, this article reflects on the role of AI—and in particular, computer vision systems used for mapping and navigation—as a catalyst for urban transformation. Urban research commonly presents AI and cities as having a one-way cause-and-effect relationship, giving undue weight to AI’s impact on cities and overlooking the role of cities in shaping AI. Working at the intersection of data science and social research, this paper aims to (...) counter this trend by exploring the reverse perspective: how do cities affect the development, and expose the present limits, of SDCs? The contribution of this paper is threefold. First, by comparing urban and nonurban environments and thoroughly examining the relationship between computer vision and city-specific sociality and form, it defines machine autonomy/automation as a function of the sociotechnical milieu in which an AI system operates. Second, and related, the paper problematizes the notion of SDCs as autonomous technologies and the role it plays in envisioning contending policy arrangements and technical solutions for achieving full driving automation. Finally, the article offers insight into a materialist and spatialized understanding of AI—namely, not as an abstract quality susceptible to replication within discrete machines, but rather as a distributed property emerging through embodied interactions among a multiplicity of agents (human, non-human, and technological) within/with their environments. (shrink)

Colour fascinates all of us, and scientists and philosophers have sought to understand the true nature of colour vision for many years. In recent times, investigations into colour vision have been one of the main success stories of cognitive science, for each discipline within the field - neuroscience, psychology, linguistics, computer science and artificial intelligence, and philosophy - has contributed significantly to our understanding of colour. Evan Thompson's book is a major contribution to this interdisciplinary project. Colour (...) Vision provides an accessible review of the current scientific and philosophical discussions of colour vision. Thompson steers a course between the subjective and objective positions on colour, arguing for a relational account. This account develops a novel `ecological' approach to colour vision in cognitive science and the philosophy of perception. It is vital reading for all cognitive scientists and philosophers whose interests touch upon this central area. (shrink)

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a ‘good AI society’. To do so, we examine how each report addresses the following three topics: the development of a (...) ‘good AI society’; the role and responsibility of the government, the private sector, and the research community in pursuing such a development; and where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a ‘good AI society’. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach. (shrink)

Interest in computerised central economic planning (CCEP) has seen a resurgence, as there is strong demand for an alternative vision to modern free (or not so free) market liberal capitalism. Given the close links of CCEP with what we would now broadly call artificial intelligence (AI)—e.g. optimisation, game theory, function approximation, machine learning, automated reasoning—it is reasonable to draw direct analogues and perform an analysis that would help identify what commodities and institutions we should see for a CCEP (...) programme to become successful. Following this analysis, we conclude that a CCEP economy would need to have a very different outlook from current market practices, with a focus on producing basic “interlinking” commodities (e.g. tools, processed materials, instruction videos) that consumers can use as a form of collective R &D. On an institutional level, CCEP should strive for the release of basic commodities that empower consumers by having as many alternative uses as possible, but also making sure that a baseline of basic necessities is widely available. (shrink)

For millions of years, biological creatures have dealt with the world without being able to see it; however, the change in the atmospheric condition during the Cambrian period and the subsequent increase of light, triggered the sudden evolution of vision and the consequent evolutionary benefits. Nevertheless, how from simple organisms to more complex animals have been able to generate meaning from the light who fell in their eyes and successfully engage the visual world remains unknown. As shown by many (...) psychophysical experiments, biological visual systems cannot measure the physical properties of the world. The light projected onto the retina is, in fact, unable to specify the physical properties of the world in which humans and other visually ‘intelligent’ animals behave; however, visual behaviours are habitually successful. Through psychophysical evidence, examples of the functioning of Artificial Neural Networks and a reflection upon visual appreciation in the cultural and artistic context, this paper shows how vision emerged by random trial and error during evolution and lifetime learning; how the functioning of ANNs may provide evidence and insights on how machine and human vision works; and how rethinking vision theory in terms of trial and error may offer a new approach to better understand vision—biological and artificial—and reveal new insights into why we like what we like. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and (...) used by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

Is there anything peculiarly "photographic" about photography—something which sets it apart from all other ways of making pictures? If there is, how important is it to our understanding of photographs? Are photographs so unlike other sorts of pictures as to require unique methods of interpretation and standards of evaluation? These questions may sound artificial, made up especially for the purpose of theorizing. But they have in fact been asked and answered not only by critics and photographers but by laymen. (...) Furthermore, for most of this century the majority of critics and laymen alike have tended to answer these questions in the same way: that photographs and paintings differ in an important way and require different methods in interpretation precisely because photographs and paintings come into being in different ways. These answers are interesting because, even within the rather restricted classes of critics, photographers, and theorists, they are held in common by a wide variety of people who otherwise disagree strongly with each other—by people who think that photographs are inferior to paintings and people who believe they are superior; by people who think that photographs ought to be "objective" and those who believe they should be "subjective"; by those who believe that it is impossible for photographers to "create" anything and by those who believe that they should at least try. Joel Snyder teaches criticism and history of photography at the University of Chicago and is presently compiling a book of his own photographs. His contributions to Critical Inquiry include "Picturing Vision" and "Reflexions on Las Meninas: Paradox Lost", written with Ted Cohen in the Winter 1980 issue. Neil Walsh Allen produces educational audio-visual materials and has designed eight permanent exhibits on the history and applications of photography for the Smithsonian Institution. (shrink)

As Artificial Intelligence researchers attempt to emulate human intelligence and transhumanists work toward superintelligence, philosophers and theologians confront a dilemma: we must either, on the one horn, (1) abandon the view that the defining feature of humanity is rationality and propose an account of spirituality that dissociates it from reason; or, on the other horn, (2) find a way to invalidate the growing faith in a posthuman future shaped by the enhancements of Intelligence Amplification (IA) or the progress of (...) Artificial Intelligence (AI). I grasp both horns of the dilemma and offer three recommendations. First, it is love understood as agape, not rational intelligence, which tells us how to live a godly life. Love tells us how to be truly human. Second, the transhumanist vision of a posthuman superintelligence is not only unrealistic, it portends the kind of tragedy we expect from a false messiah. Third, if as a byproduct of AI and IA research combined with H+ zeal the wellbeing of the human species and our planet is enhanced, we should be grateful. (shrink)

The age of artificial intelligence (AI) is upon us, and its effect upon society in the coming years will be noteworthy. Artificial intelligence is a field that encompasses such applications as robotics, expert systems, natural language understanding, speech recognition, and computer vision. The effect of these AI systems upon existing and future job occupations will be important. This paper takes a look at artificial intelligence in terms of the creation of new job categories. Also, the introduction (...) of AI into the organization to better familiarize the employees about AI will be discussed. (shrink)

National Artificial Intelligence (AI) strategies articulate imaginaries of the integration of AI into society and envision the governing of AI research, development and applications accordingly. To integrate these central aspects of national AI strategies under one coherent perspective, this paper presented an analysis of Germany’s strategy ‘AI made in Germany’ through the conceptual lens of ordoliberal political rationality. The first part of the paper analyses how the guiding vision of a human-centric AI not only adheres to ethical and (...) legal principles consistent with Germany’s liberal democratic constitutional system but also addresses the risks and promises inherent to the ordoliberal problematization of freedom. Second, it is scrutinized how the strategy cultivates the fear of not achieving technological sovereignty in the AI sector. Thereby, it frames the global AI race as a race of competing (national) approaches to governing AI and articulates an ordoliberal approach to governing AI (the ‘third way’), according to which government has to operate between the twin dangers of governing too much and not governing enough. Third, the paper analyses how this ordoliberal proportionality of governing structures Germany’s Science Technology & Innovation Policy. It is shown that the corresponding risk-based approach of regulating AI constitutes a security apparatus as it produces an assessment of fears: weighting the fear of the failure to innovate with the fear of the ramifications of innovation. Finally, two lines of critical engagement based on this analysis are conducted. (shrink)

As China and the United States strive to be the primary global leader in AI, their visions are coming into conflict. This is frequently painted as a fundamental clash of civilisations, with evidence based primarily around each country’s current political system and present geopolitical tensions. However, such a narrow view claims to extrapolate into the future from an analysis of a momentary situation, ignoring a wealth of historical factors that influence each country’s prevailing philosophy of technology and thus their overarching (...) AI strategies. In this article, we build a philosophy-of-technology-grounded framework to analyse what differences in Chinese and American AI policies exist and, on a fundamental level, why they exist. We support this with Natural Language Processing methods to provide an evidentiary basis for our analysis of policy differences. By looking at documents from three different American presidential administrations––Barack Obama, Donald Trump, and Joe Biden––as well as both national and local policy documents (many available only in Chinese) from China, we provide a thorough comparative analysis of policy differences. This article fills a gap in US–China AI policy comparison and constructs a framework for understanding the origin and trajectory of policy differences. By investigating what factors are informing each country’s philosophy of technology and thus their overall approach to AI policy, we argue that while significant obstacles to cooperation remain, there is room for dialogue and mutual growth. (shrink)

The European Union Commission’s whitepaper on Artificial Intelligence proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: the lack of a coherent EU vision to (...) drive future decision-making processes at state and local levels and the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society. (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)

Vision is inseparably connected to perceptual awareness which can be seen as the culmination of sensory processing. Studies on conscious vision reveal that object recognition is just one of the means through which our representation of the world is built. We propose an operationalization of subjective experience in the context of deep neural networks (DNNs) that could encourage a more thorough comparison of human and artificial vision.

Increasing computational power and improving deep learning methods have made computer vision technologies pervasively common in urban environments. Their applications in policing, traffic management, and documenting public spaces are increasingly common (Ridgeway 2018, Coifman et al. 1998, Sun et al. 2020). Despite the often-discussed biases in the algorithms' training and unequally borne benefits (Khosla et al. 2012), almost all applications similarly reduce urban experiences to simplistic, reductive, and mechanistic measures. There is a lack of context, depth, and specificity in (...) these practices that enables semantic knowledge or analysis within urban contexts, especially within the context of using and occupying urban space. This paper will critique existing uses of artificial intelligence and computer vision in urban practices to propose a new framework for understanding people, action, and public space. This paper revisits Geertz's (1973) use of thick descriptions in generating interpretive theories of culture and activity and uses this lens to establish a framework to approach evaluating the varied uses of computer vision technologies that weigh meaning. By discussing cases of implemented examples of urban computer vision—from LinkNYC and Numina's urban measurements to the Detroit Police's use of DataWorks Plus's facial recognition technology—it proposes a framework for evaluating the thickness of the algorithm's conclusions against the computational method's complexity required to produce that outcome. Further, we discuss how the framework's positioning may differ (and conflict) between different users of the technology, from engineer to urban planner and policymaker, to citizen. This paper also discusses how the current use and training of deep learning algorithms and how this process limits semantic learning and proposes three potential methodologies toward gaining a more contextually specific, urban-semantic, description of urban space relevant to urbanists. This paper contributes to the critical conversations regarding the proliferation of artificial intelligence by challenging the current applications of these technologies in the urban environment by highlighting their failures within this context while also proposing an evolution of these algorithms that may ultimately make them sensitive and useful within this spatial and cultural milieu. (shrink)

As the notion of artificial moral agency gains popularity among ethicists, it threatens the unique status of the human person as a responsible moral agent. The philosophy of ontocentrism, popularized by Luciano Floridi, argues that biocentrism is too restrictive and must yield to a new philosophical vision that endows all beings with some intrinsic value. Floridi’s macroethics also regards more sophisticated digital entities such as robots as accountable moral agents. To refute these principles, this paper turns to the (...) thought of Karol Wojtyla, who argued cogently for an intimate correlation between personal action (actus personae) and moral agency. By examining the distinguishing characteristics of personal action, we can ascertain the necessary conditions of moral agency and demonstrate why artificial entities do not meet those condi­tions. National Catholic Bioethics Quarterly 11.3 (Autumn 2011): 479–501. (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 paper considers recent experiments in art and artificial intelligence that crystallize around training algorithms to generate artworks based on datasets derived from the Western art historical canon. Over the last decade, a shift towards the rejection of canonicity has begun to take shape in art historical discourse. At the same time, algorithmically enabled practices in the US and Europe have emerged that entrench the Western canon as a locus and guarantor of aesthetic value. Operating within the epistemic framework (...) of a “view from nowhere,” this tendency in generative art inherits the coloniality of both art history and artificial intelligence. Producing “art histories from nowhere,” this tendency conflates the conceptual category of visual art with the histories of Western cultural production. It reproduces a set of aesthetic values that entrench the mythology of the artist-genius and his imputed whiteness and masculinity; the extolment of innovation and novelty as self-evident virtues; disembodied Cartesian models of knowing and sensing; and the erasure of contributions that have been occluded from canonical visibility. As we encounter systems trained on particular visions of art history and of the artist, how might we remain attentive to the specific lens through which they are taught to see? This essay addresses that question by bringing the coloniality of recent experiments into view, bridging data feminisms and decolonial studies to formulate alternative visions of encounters between art and AI. (shrink)

Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in (...) the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust--in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better. (shrink)

Few modern artists so consistently embodied a fuzzy logic of their own as did the Indian painter Maqbool Fida Husain (1915 – 2011). His critics tried to define him as a reckless defamer of Hindu values, but another way to define him is as a dutiful devotee of a vision that was inclusive, rather than exclusive, and that understood all boundaries and identities as fluid or blurry, rather than as fixed and immutable. Or one might say that Husain strove (...) to project what Ashis Nandy has called “Indian-style secularism,” celebrating creation, humanity, and beauty in the multiple religious forms of the subcontinent. Having lived and painted in India all his life, he was forced into exile in his nineties by right-wing Hindu politicians. In London, he continued to work on a new interpretation of Indian civilization as universally relevant, in a sequence of paintings with themes from the Mahabharata, while, in Doha, a royal patron commissioned him to paint a series relating Islamic and Christian civilization. The two series are shown, in this essay, to best exhibit Husain's view of “all distinctions” as “political, artificial.”. (shrink)

The article provides a comprehensive analysis of scientific approaches to the formation of legal regulation of relations arising in the development and use of artificial intelligence technologies, their socio-legal status, as well as social, ethical, methodological, and practical legal issues with an emphasis on the fundamentals of natural legal doctrine. The author’s vision of the concept of human interaction and artificial intelligence from the standpoint of legal relations is given. Emphasis is placed on the need to study (...) the problems that arise in this area, within the framework of information law, as a complex branch of law and sociohumanitarian informology—at the level of an interdisciplinary approach. Ways to improve the mechanisms and methods of legal support in the field of artificial intelligence through the development and implementation of technological and legal methods as an innovative tools and effective tools for special technological impact. (shrink)

Since their introduction in Colombia in the '80s for Pablo Escobar’s extravagant zoo, hippos have become an ecological problem around the basin of the Magdalena River. This article proposes an ecosemiotic discourse analysis of different visions of nature enacted by stakeholders and public opinion around the management of hippos in Colombia. Concretely, we focus on three particular discourses and visions of nature: animalista, narco-cultural, and conservacionista. In this article, we present the relevant social and ecological context of Colombia, the visions (...) of nature theory and the impact of such visions on conservation measures regarding so-called invasive species; we describe and analyze the three visions of nature we center on, and present a computational analysis of discourse dynamics and controversies in Twitter between of such visions of nature; and we reflect on possible courses of action and recommendations about addressing the close interrelation of public discourses and ecosystem conservation by proposing an alternative view, based on the biosemiotic framework of semiocide, to the concept of invasive species. (shrink)

Las tecnologías de la inteligencia artificial (IA) hacen emerger con mayor fuerza una pregunta central para la filosofía contemporánea: ¿cómo se generan los desplazamientos éticos a través de la producción de nuevas formas de convivencia tecnológica? Saber en qué consisten estos desplazamientos y si contribuyen, o no, a determinados tipos de convivencia es más urgente que precipitarse a una producción de normativa que no se enfrenta a los cambios inherentes al nuevo entorno. Pero una de las consecuencias que apuntan (...) en este enfoque es que la programación, sometida a las lógicas de la anticipación, no puede resolver el problema simplemente. La programación tiende a la formación de nichos o esferas en los que los individuos se desenvuelven perdiendo visión de la complejidad; la delegación de los cálculos a las máquinas hace que disminuya no sólo la capacidad del cálculo aritmético sino la imaginación matemática, creando nichos epistémicos crecientemente reservados a las máquinas; la minería de datos borra las diferencias entre lo público y lo privado, afianzando modos de comportamiento que esquivan la autorreflexión y el escrutinio de nuestras acciones en relación al bien común. Pero ¿pueden los programas desenvolverse en un sentido contrario, fortaleciendo las destrezas epistémicas, haciendo visible la complejidad, la participación política y la diversificación de bienes comunes en un mundo tecnológicamente denso? O en otros términos, ¿podemos encontrar en ellos claves para una ética robusta de la convivencia tecnológica? Las contribuciones de este número desgranan las transformaciones en las nociones de autonomía, creatividad y precariedad en el contexto de la IA. (shrink)

[Müller, Vincent C. (ed.), (2013), Philosophy and theory of artificial intelligence (SAPERE, 5; Berlin: Springer). 429 pp. ] --- Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. (...) This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here. (shrink)

This study, originally published in 1977, focuses on a critical examination of the life-work of Alfred Schutz, the most important and influential ‘father’ of several recent schools of empirical social research. The author shows why Shutz and his followers fail in their attempts to ‘humanize’ empirical social science. The problems they encounter, he argues, are due to their attempt to achieve a methodological synthesis of self-determining subjectivity and empirical criteria of validation, based on Schutz’s heuristic adoption of relevant ideas from (...) Weber and Husserl. This is, in effect, an artificial union of subjectivity and objectivity – their ‘dual vision’ – that satisfies neither phenomenological nor naturalist perspectives. Dr Gorman suggests that the radical implications of phenomenology must lead to a consistent, socially-conscious method of inquiry, and, in a final chapter, he re-defines the methodological implications of phenomenology with the aid of existential and Marxist categories. (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.

The emerging neurocomputational vision of humans as embodied, ecologically embedded, social agents—who shape and are shaped by their environment—offers a golden opportunity to revisit and revise ideas about the physical and information-theoretic underpinnings of life, mind, and consciousness itself. In particular, the active inference framework makes it possible to bridge connections from computational neuroscience and robotics/AI to ecological psychology and phenomenology, revealing common underpinnings and overcoming key limitations. AIF opposes the mechanistic to the reductive, while staying fully grounded in (...) a naturalistic and information-theoretic foundation, using the principle of free energy minimization. The latter provides a theoretical basis for a unified treatment of particles, organisms, and interactive machines, spanning from the inorganic to organic, non-life to life, and natural to artificial agents. We provide a brief introduction to AIF, then explore its implications for evolutionary theory, ecological psychology, embodied phenomenology, and robotics/AI research. We conclude the paper by considering implications for machine consciousness. (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 lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Vanities of the Eye: Vision in Early Modern European CultureDallas G. Denery IIStuart Clark. Vanities of the Eye: Vision in Early Modern European Culture. Oxford-New York: Oxford University Press, 2007. Pp. xi + 415. Cloth, $75.00.A popular and pervasive historical narrative links the Renaissance development of linear perspective with Europe’s transition from a pre-modern to an early modern society. Erwin Panofsky gave this narrative its definitive (...) form early in the twentieth century and William Ivins boiled it down to a simple idea that served as the title of his most famous book. According to Ivins, single-point perspective, the artistic technique championed by Alberti and perfected in the paintings of Masaccio and Piero della Francesca, allowed for “the rationalization of sight.” In other words, it provided a mathematically and geometrically grounded method for accurately representing the external world. It is a powerful and seductive claim, one that has shaped generations of scholarly work. It is also, Stuart Clark contends in this important new book, patently wrong. Far from exhibiting a renewed or reinvigorated confidence in the accuracy and reliability of vision, sixteenth- and seventeenth-century philosophers, artists, theologians, and doctors worried that sight was susceptible, perhaps permanently so, to all sorts of debilitating derangements, displacements, and delusions.Rather than relate a history of progress, Clark offers a history of exhaustion, failure, and, ultimately, of rejection. Early modern intellectuals inherited a comprehensive theory of vision and cognition from their medieval predecessors known as perspectivist optics. This theory sought to secure the accuracy of human sense perception through regularized causal processes that linked things in the world with our various cognitive faculties. While some fourteenth-century intellectuals, most notably Nicolas of Autrecourt and Nicole Oresme, recognized structural deficiencies in this theory, their critiques were mostly ignored or treated as anomalies. Over the course of the next two and a half centuries, Clark argues, the challenges to this theory multiplied until it collapsed under their weight (20).Clark’s argument is straightforward and, as his evidence mounts, thoroughly convincing. Throughout each of the eight engrossing chapters that form the core of the book, Clark outlines a different threat, a different set of challenges that pointed out problems with the assumption that vision is trustworthy. The range and depth of those challenges are truly amazing. Doctors worried that imbalances in our humoral system, and especially in the black bile that causes melancholy, could render our visual perceptions dubious at best (ch. 2). Theologians, wary of the dangers of witchcraft and eager to prosecute its practitioners, obsessed over the cognitive threats that devils and demons posed to good Christians (ch. 4), while Protestant reformers relegated the entire tradition of Catholic miracles to the counterfeit illusions of the antichrist (ch. 5). For their part, artists believed that perspective undermined vision, depending as it does on the assumption that what we see is always relative, dependent upon our point of view (ch. 3).Clark structures much of his argument around George Hakewill’s 1608 book, The vanitie of the eye, an exposition on the natural, artificial, and demonic sources that forever render visual knowledge suspect. He could just as well have organized it around the opening pages of Descartes’s Meditations, and in many ways Clark’s book serves as a superb rumination on the sources of Descartes’s skeptical arguments. Unlike Etienne Gilson and, more recently, Richard Popkin, both of whom have done so much to open up the scholastic and early modern sources of Descartes’s skeptical thought experiments, Clark does not limit himself to philosophical lineages. Rather, he considers sources of visual skepticism that developed across an entire culture—in natural philosophy, medicine, art, religion, and literature (especially in Shakespeare’s Macbeth). Not only does the sheer volume and variety of such [End Page 103] sources help to explain Descartes’s urgent desire to overturn everything he had learned and begin again from the foundations, but it also contextualizes the specific arguments he employs. None of Descartes’s skeptical arguments were new and most were well known in the Middle Ages. What had changed over the intervening centuries, Clark contends, was how these arguments drew from... (shrink)

On its release, the Instruction on Respect for Human Life was accused of obstructing the technological enhancement of human life by using slippery slope arguments to impose the Magisterium’s opinion that accepting certain new technologies, like homologous artificial fertilization, would weaken resistance to practices the Church traditionally has opposed. To the contrary, the instruction calls attention to the fact that by using these technologies, we have in principle accepted all sorts of thigs, with or without technology, which are destructive (...) of human life. (shrink)