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The first book to draw a direct line between the datafication and prediction techniques of past eugenicists and today's often violent and extractive "big data" regimes. Predatory Data illuminates the throughline between the nineteenth century's anti-immigration and eugenics movements and our sprawling systems of techno-surveillance and algorithmic discrimination. With this book, Anita Say Chan offers a historical, globally multisited analysis of the relations of dispossession, misrecognition, and segregation expanded by dominant knowledge institutions in the Age of Big Data. While technological advancement has a tendency to feel inevitable, it always has a history, including efforts to chart...
This collection takes an interdisciplinary approach to the study of gendered technology, an emerging area of inquiry that draws on a range of fields to explore how technology is designed and used in a way that reinforces or challenges gender norms and inequalities. The volume explores different perspectives on the impact of technology on gender relations through specific cases of translation and interpreting technologies. In particular, the book considers the slow response of legal frameworks in dealing with the rise of language-based technologies, especially machine translation and large language models, and their impacts on individual and collective rights. Part I introduces the study of g...
The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applica...
Winner of the Nayef Al-Rodhan Book Prize from The Royal Institute of Philosophy An exciting, new framework for interpreting the philosophical significance of neuroscience. All science needs to simplify, but when the object of research is something as complicated as the brain, this challenge can stretch the limits of scientific possibility. In fact, in The Brain Abstracted, an avowedly “opinionated” history of neuroscience, M. Chirimuuta argues that, due to the brain’s complexity, neuroscientific theories have only captured partial truths—and “neurophilosophy” is unlikely to be achieved. Looking at the theory and practice of neuroscience, both past and present, Chirimuuta shows ho...
This book offers an accessible introduction to the ways that language is processed and produced by computers, a field that has recently exploded in interest. The book covers writing systems, tools to help people write, computer-assisted language learning, the multidisciplinary study of text as data, text classification, information retrieval, machine translation, and dialog. Throughout, we emphasize insights from linguistics along with the ethical and social consequences of emerging technology. This book welcomes students from diverse intellectual backgrounds to learn new technical tools and to appreciate rich language data, thus widening the bridge between linguistics and computer science.
This open access book provides cybersecurity practitioners with the knowledge needed to understand the risks of the increased availability of powerful large language models (LLMs) and how they can be mitigated. It attempts to outrun the malicious attackers by anticipating what they could do. It also alerts LLM developers to understand their work's risks for cybersecurity and provides them with tools to mitigate those risks. The book starts in Part I with a general introduction to LLMs and their main application areas. Part II collects a description of the most salient threats LLMs represent in cybersecurity, be they as tools for cybercriminals or as novel attack surfaces if integrated into e...
Today, Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society, many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms and tools have been used in many internet applications and electronic devices, they are also vulnerable to various attacks and threats. AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, among many other attacks and threats. Such attacks can make AI products dangerous to use. While this discussion focuses on ...
Is artificial intelligence (AI) becoming more and more expressive, or is human thought adopting more and more structures from computation? What does it mean to perform oneself through AI, or to construct one’s subjectivity through AI? How does AI continue to complicate what it means to have a body? Has the golden age of AI, especially with regards to creative applications, already ended? Choreomata: Performance and Performativity after AI is a book about performance and performativity, but more specifically, it is a book about the performance of artificiality and the performance of intelligence. Both humans and human-designed computational forces are thoroughly engaged in an entangled, mutual performance of AI. Choreomata spins up a latticework of interdisciplinary thought, pairing theoretical inquiry from philosophy, information theory, and computer science with practical case studies from visual art, dance, music, and social theory. Through cross-disciplinary proportions and a diverse roster of contributors, this book contains insights for computer scientists, social scientists, industry professionals, artists, and beyond.