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Author: Jonathan Roberge
Publisher: Springer Nature
ISBN: 3030562867
Category : Social Science
Languages : en
Pages : 298
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Book Description
This book brings together the work of historians and sociologists with perspectives from media studies, communication studies, cultural studies, and information studies to address the origins, practices, and possible futures of contemporary machine learning. From its foundations in 1950s and 1960s pattern recognition and neural network research to the modern-day social and technological dramas of DeepMind’s AlphaGo, predictive political forecasting, and the governmentality of extractive logistics, machine learning has become controversial precisely because of its increased embeddedness and agency in our everyday lives. How can we disentangle the history of machine learning from conventional histories of artificial intelligence? How can machinic agents’ capacity for novelty be theorized? Can reform initiatives for fairness and equity in AI and machine learning be realized, or are they doomed to cooptation and failure? And just what kind of “learning” does machine learning truly represent? We empirically address these questions and more to provide a baseline for future research. Chapter 2 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Author: Jonathan Roberge
Publisher: Springer Nature
ISBN: 3030562867
Category : Social Science
Languages : en
Pages : 298
Get Book Here
Book Description
This book brings together the work of historians and sociologists with perspectives from media studies, communication studies, cultural studies, and information studies to address the origins, practices, and possible futures of contemporary machine learning. From its foundations in 1950s and 1960s pattern recognition and neural network research to the modern-day social and technological dramas of DeepMind’s AlphaGo, predictive political forecasting, and the governmentality of extractive logistics, machine learning has become controversial precisely because of its increased embeddedness and agency in our everyday lives. How can we disentangle the history of machine learning from conventional histories of artificial intelligence? How can machinic agents’ capacity for novelty be theorized? Can reform initiatives for fairness and equity in AI and machine learning be realized, or are they doomed to cooptation and failure? And just what kind of “learning” does machine learning truly represent? We empirically address these questions and more to provide a baseline for future research. Chapter 2 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Author: Sofian Audry
Publisher: MIT Press
ISBN: 0262367106
Category : Art
Languages : en
Pages : 215
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Book Description
An examination of machine learning art and its practice in new media art and music. Over the past decade, an artistic movement has emerged that draws on machine learning as both inspiration and medium. In this book, transdisciplinary artist-researcher Sofian Audry examines artistic practices at the intersection of machine learning and new media art, providing conceptual tools and historical perspectives for new media artists, musicians, composers, writers, curators, and theorists. Audry looks at works from a broad range of practices, including new media installation, robotic art, visual art, electronic music and sound, and electronic literature, connecting machine learning art to such earlier artistic practices as cybernetics art, artificial life art, and evolutionary art. Machine learning underlies computational systems that are biologically inspired, statistically driven, agent-based networked entities that program themselves. Audry explains the fundamental design of machine learning algorithmic structures in terms accessible to the nonspecialist while framing these technologies within larger historical and conceptual spaces. Audry debunks myths about machine learning art, including the ideas that machine learning can create art without artists and that machine learning will soon bring about superhuman intelligence and creativity. Audry considers learning procedures, describing how artists hijack the training process by playing with evaluative functions; discusses trainable machines and models, explaining how different types of machine learning systems enable different kinds of artistic practices; and reviews the role of data in machine learning art, showing how artists use data as a raw material to steer learning systems and arguing that machine learning allows for novel forms of algorithmic remixes.
Author: Andrea L. Guzman
Publisher: SAGE
ISBN: 1529786746
Category : Computers
Languages : en
Pages : 1019
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Book Description
The SAGE Handbook of Human-Machine Communication has been designed to serve as the touchstone text for researchers and scholars engaging in new research in this fast-developing field. Chapters provide a comprehensive grounding of the history, methods, debates and theories that contribute to the study of human-machine communication. Further to this, the Handbook provides a point of departure for theorizing interactions between people and technologies that are functioning in the role of communicators, and for considering the theoretical and methodological implications of machines performing traditionally ‘human’ roles. This makes the Handbook the first of its kind, and a valuable resource for students and scholars across areas such as communication, media and information studies, and computer science, as well as for practitioners, engineers and researchers interested in the foundational elements of this emerging field. Part 1: Histories and Trajectories Part 2: Approaches and Methods Part 3: Concepts and Contexts Part 4: Technologies and Applications
Author: Wang, John
Publisher: IGI Global
ISBN: 1799892212
Category : Computers
Languages : en
Pages : 3296
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Book Description
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Author: Anthony Elliott
Publisher: John Wiley & Sons
ISBN: 150954982X
Category : Social Science
Languages : en
Pages : 150
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Book Description
Artificial intelligence not only powers our cars, hospitals and courtrooms: predictive algorithms are becoming deeply lodged inside us too. Machine intelligence is learning our private preferences and discreetly shaping our personal behaviour, telling us how to live, who to befriend and who to date. In Algorithmic Intimacy, Anthony Elliott examines the power of predictive algorithms in reshaping personal relationships today. From Facebook friends and therapy chatbots to dating apps and quantified sex lives, Elliott explores how machine intelligence is working within us, amplifying our desires and steering our personal preferences. He argues that intimate relationships today are threatened not by the digital revolution as such, but by the orientation of various life strategies unthinkingly aligned with automated machine intelligence. Our reliance on algorithmic recommendations, he suggests, reflects a growing emergency in personal agency and human bonds. We need alternatives, innovation and experimentation for the interpersonal, intimate effort of ongoing translation back and forth between the discourses of human and machine intelligence. Accessible and compelling, this book sheds fresh light on the impact of artificial intelligence on the most intimate aspects of our lives. It will appeal to students in the social sciences and humanities and to a wide range of general readers.
Author: Habib, Maki K.
Publisher: IGI Global
ISBN: 1522577947
Category : Education
Languages : en
Pages : 278
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Book Description
Artificial Intelligence (AI) serves as a catalyst for transformation in the field of digital teaching and learning by introducing novel solutions to revolutionize all dimensions of the educational process, leading to individualized learning experiences, teachers playing a greater role as mentors, and the automation of all administrative processes linked to education. AI and machine learning are already contributing to and are expected to improve the quality of the educational process by providing advantages such as personalized and interactive tutoring with the ability to adjust the content and the learning pace of each individual student while assessing their performance and providing feedback. These shifts in the educational paradigm have a profound impact on the quality and the way we live, interact with each other, and define our values. Thus, there is a need for an earnest inquiry into the cultural repercussions of this phenomenon that extends beyond superficial analyses of AI-based applications in education. Revolutionizing Education in the Age of AI and Machine Learning addresses the need for a scholarly exploration of the cultural and social impacts of the rapid expansion of artificial intelligence in the field of education including potential consequences these impacts could have on culture, social relations, and values. The content within this publication covers such topics as AI and tutoring, role of teachers, physical education and sports, interactive E-learning and virtual laboratories, adaptive curricula development, support critical thinking, and augmented intelligence and it is designed for educators, curriculum developers, instructional designers, educational software developers, education consultants, academicians, administrators, researchers, and professionals.
Author: Chris Wiggins
Publisher: W. W. Norton & Company
ISBN: 1324006749
Category : Technology & Engineering
Languages : en
Pages : 289
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Book Description
“Fascinating.” —Jill Lepore, The New Yorker A sweeping history of data and its technical, political, and ethical impact on our world. From facial recognition—capable of checking people into flights or identifying undocumented residents—to automated decision systems that inform who gets loans and who receives bail, each of us moves through a world determined by data-empowered algorithms. But these technologies didn’t just appear: they are part of a history that goes back centuries, from the census enshrined in the US Constitution to the birth of eugenics in Victorian Britain to the development of Google search. Expanding on the popular course they created at Columbia University, Chris Wiggins and Matthew L. Jones illuminate the ways in which data has long been used as a tool and a weapon in arguing for what is true, as well as a means of rearranging or defending power. They explore how data was created and curated, as well as how new mathematical and computational techniques developed to contend with that data serve to shape people, ideas, society, military operations, and economies. Although technology and mathematics are at its heart, the story of data ultimately concerns an unstable game among states, corporations, and people. How were new technical and scientific capabilities developed; who supported, advanced, or funded these capabilities or transitions; and how did they change who could do what, from what, and to whom? Wiggins and Jones focus on these questions as they trace data’s historical arc, and look to the future. By understanding the trajectory of data—where it has been and where it might yet go—Wiggins and Jones argue that we can understand how to bend it to ends that we collectively choose, with intentionality and purpose.
Author: Dariusz Brzeziński
Publisher: Taylor & Francis
ISBN: 1040257852
Category : Social Science
Languages : en
Pages : 250
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Book Description
This volume brings together eminent scholars from various parts of the world, representing different fields of knowledge in order to explore the social, cultural, political and economic effects of the development of new technologies. On the one hand, the book contextualises the discussion of algorithms and artificial intelligence (AI) within the broader framework of the digital revolution, on the other it also examines individual experiences and practices. Moreover, in light of the speed at which algorithms and AI are being incorporated into various aspects of life, contributors also question the ethical implications of their development. The widespread development of AI and algorithmic solutions is one of the most important contemporary phenomena. It has an overwhelming impact on the social and cultural life of the 21st century. In this context, one can point to both exciting examples of the application of algorithms and AI in business and popular culture, as well as the challenges of widening social inequality or the expanding scope of surveillance. The scope of the impact of algorithms and AI makes the formation of new theoretical frameworks vital. This is the aim of this book, which will be of interest to academics within the humanities and social sciences with an interest in technology and the impact of algorithms and AI on society and culture.
Author: Matteo Pasquinelli
Publisher: Verso Books
ISBN: 1788730062
Category : Social Science
Languages : en
Pages : 273
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Book Description
A social history of AI that finally reveals its roots in the spatial computation of industrial factories and the surveillance of collective behaviour. What is AI? A dominant view describes it as the quest "to solve intelligence," a solution supposedly to be found in the secret logic of the mind or in the deep physiology of the brain, such as in its complex neural networks. The Eye of the Master argues, to the contrary, that the inner code of AI is shaped not by the imitation of biological intelligence, but the intelligence of labour and social relations, as it is found in Babbage's "calculating engines" of the industrial age as well as in the recent algorithms for image recognition and surveillance. The idea that AI may one day become autonomous (or "sentient", as someone thought of Google's LaMDA) is pure fantasy. Computer algorithms have always imitated the form of social relations and the organisation of labour in their own inner structure and their purpose remains blind automation. The Eye of the Master urges a new literacy on AI for scientists, journalists and new generations of activists, who should recognise that the "mystery" of AI is just the automation of labour at the highest degree, not intelligence per se.
Author: David Beer
Publisher: Policy Press
ISBN: 1529212901
Category : Computers
Languages : en
Pages : 152
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Book Description
In this pioneering book, David Beer redefines emergent algorithmic technologies as the new systems of knowing. He examines the acute tensions they create and how they are changing what is known and what is knowable.
