What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? Drawing on more than a decade of research, award‑winning scholar Kate Crawford reveals how AI is a technology of extraction: from the minerals drawn from the earth, to the labor pulled from low-wage information workers, to the data taken from every action and expression. This book reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequity. Rather than taking a narrow focus on code and algorithms, Crawford offers us a material and political perspective on what it takes to make AI and how it centralizes power. This is an urgent account of what is at stake as technology companies use artificial intelligence to reshape the world.
In AI Superpowers, Kai-fu Lee argues powerfully that because of these unprecedented developments in AI, dramatic changes will be happening much sooner than many of us expected. Indeed, as the US-Sino AI competition begins to heat up, Lee urges the US and China to both accept and to embrace the great responsibilities that come with significant technological power. Most experts already say that AI will have a devastating impact on blue-collar jobs. But Lee predicts that Chinese and American AI will have a strong impact on white-collar jobs as well. Is universal basic income the solution? In Lee's opinion, probably not. But he provides a clear description of which jobs will be affected and how soon, which jobs can be enhanced with AI, and most importantly, how we can provide solutions to some of the most profound changes in human history that are coming soon.
Until the mid-1980s, AI researchers assumed that an intelligent system doing high-level reasoning was necessary for the coupling of perception and action. In this traditional model, cognition mediates between perception and plans of action. Realizing that this core AI, as it was known, was illusory, Rodney A. Brooks turned the field of AI on its head by introducing the behavior-based approach to robotics. The cornerstone of behavior-based robotics is the realization that the coupling of perception and action gives rise to all the power of intelligence and that cognition is only in the eye of an observer. Behavior-based robotics has been the basis of successful applications in entertainment, service industries, agriculture, mining, and the home. It has given rise to both autonomous mobile robots and more recent humanoid robots such as Brooks' Cog.
This book represents Brooks' initial formulation of and contributions to the development of the behavior-based approach to robotics. It presents all of the key philosophical and technical ideas that put this "bottom-up" approach at the forefront of current research in not only AI but all of cognitive science.
In Possible Minds, John Brockman gathers their disparate visions of where AI might be taking us. The fruit of the long history of Brockman's profound engagement with the most important scientific minds who have been thinking about AI--from Alison Gopnik and David Deutsch to Frank Wilczek and Stephen Wolfram*-Possible Minds* is an ideal introduction to the landscape of crucial issues AI presents. The collision between opposing perspectives is salutary and exhilarating; some of these figures, such as computer scientist Stuart Russell, Skype co-founder Jaan Tallinn, and physicist Max Tegmark, are deeply concerned with the threat of AI, including the existential one, while others, notably robotics entrepreneur Rodney Brooks, philosopher Daniel Dennett, and bestselling author Steven Pinker, have a very different view.
"The Artist in the Machine" by Arthur I. Miller delves into the fascinating world of AI-driven creativity, exploring the intersection of art and artificial intelligence. Miller examines how algorithms are being harnessed to compose music, create visual art, write poetry, and more. Through a series of case studies and analyses, the book challenges traditional notions of creativity, questioning the role of machines in the artistic process. Miller's exploration offers insights into the potential, challenges, and ethical considerations of AI in the arts, ultimately pondering the nature of creativity in an age of advanced technology.
In 1970 Japanese engineer Masahiro Mori introduced the concept of the “uncanny valley” as a terrain of existential uncertainty that humans experience when confronted with autonomous machines that mimic their physical and mental properties. As subjectivities are increasingly organized and shaped by algorithms that track and evaluate our data, the question of what it means to be human has shifted.
The featured artists mine the tropes and modalities of AI and machine learning for critical and aesthetic potential, proposing new ways of thinking about intelligence, nature, and artifice
"The Creativity Code: Art and Innovation in the Age of AI" by Marcus du Sautoy delves into the intersection of art, creativity, and artificial intelligence. Du Sautoy, a renowned mathematician, explores the capabilities and limitations of AI in emulating human creativity. He examines various fields, from music and visual arts to literature, questioning whether machines can truly be creative or if they merely mimic patterns learned from human-generated data. Throughout the book, du Sautoy grapples with the philosophical implications of AI's role in artistic creation, pondering what creativity means in the digital age and how it challenges our understanding of human uniqueness.
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.