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Artificial intelligence (AI) is now mediating, and in some cases seen to be controlling, key urban services and infrastructures, thus becoming a prominent feature of the contemporary city. As portrayed in recent studies, the “autonomous city” can be understood as a city where urban artificial intelligences perform tasks and take on roles which have traditionally been the domain of humans. At stake in these debates are questions related to the meaning and ongoing role of intelligence, for both humans and machines. While autonomous cars transport people, service robots run shops, drones deliver goods and city brains govern entire cities, humans are redefining the meaning of what “smart” means in the city and what role the human being may play in future urban spaces. With humans shifted to new sectors of the economy or pushed aside by algorithms and robotic agents creating new ways of seeing and governing the city, we raise the question as to whether or not cities are becoming more autonomous from human experience in the sense that their operation does not rely as much on human inputs anymore.
An authoritative, up-to-date survey of the state of the art in artificial intelligence, written for non-specialists.
Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]
This book explores in theory and practice how artificial intelligence (AI) intersects with and alters the city. Drawing upon a range of urban disciplines and case studies, the chapters reveal the multitude of repercussions that AI is having on urban society, urban infrastructure, urban governance, urban planning and urban sustainability. Contributors also examine how the city, far from being a passive recipient of new technologies, is influencing and reframing AI through subtle processes of co-constitution. The book advances three main contributions and arguments: First, it provides empirical evidence of the emergence of a post-smart trajectory for cities in which new material and decision-making capabilities are being assembled through multiple AIs. Second, it stresses the importance of understanding the mutually constitutive relations between the new experiences enabled by AI technology and the urban context. Third, it engages with the concepts required to clarify the opaque relations that exist between AI and the city, as well as how to make sense of these relations from a theoretical perspective. Artificial Intelligence and the City offers a state-of-the-art analysis and review of AI urbanism, from its roots to its global emergence. It cuts across several disciplines and will be a useful resource for undergraduates and postgraduates in the fields of urban studies, urban planning, geography, architecture, urban design, science and technology studies, sociology and politics.
The variety, pace, and power of technological innovations that have emerged in the 21st Century have been breathtaking. These technological developments, which include advances in networked information and communications, biotechnology, neurotechnology, nanotechnology, robotics, and environmental engineering technology, have raised a number of vital and complex questions. Although these technologies have the potential to generate positive transformation and help address 'grand societal challenges', the novelty associated with technological innovation has also been accompanied by anxieties about their risks and destabilizing effects. Is there a potential harm to human health or the environment? What are the ethical implications? Do this innovations erode of antagonize values such as human dignity, privacy, democracy, or other norms underpinning existing bodies of law and regulation? These technological developments have therefore spawned a nascent but growing body of 'law and technology' scholarship, broadly concerned with exploring the legal, social and ethical dimensions of technological innovation. This handbook collates the many and varied strands of this scholarship, focusing broadly across a range of new and emerging technology and a vast array of social and policy sectors, through which leading scholars in the field interrogate the interfaces between law, emerging technology, and regulation. Structured in five parts, the handbook (I) establishes the collection of essays within existing scholarship concerned with law and technology as well as regulatory governance; (II) explores the relationship between technology development by focusing on core concepts and values which technological developments implicate; (III) studies the challenges for law in responding to the emergence of new technologies, examining how legal norms, doctrine and institutions have been shaped, challenged and destabilized by technology, and even how technologies have been shaped by legal regimes; (IV) provides a critical exploration of the implications of technological innovation, examining the ways in which technological innovation has generated challenges for regulators in the governance of technological development, and the implications of employing new technologies as an instrument of regulatory governance; (V) explores various interfaces between law, regulatory governance, and new technologies across a range of key social domains.
This new collection of essays follows in the footsteps of the successful volume Thinking Ahead - Essays on Big Data, Digital Revolution, and Participatory Market Society, published at a time when our societies were on a path to technological totalitarianism, as exemplified by mass surveillance reported by Edward Snowden and others. Meanwhile the threats have diversified and tech companies have gathered enough data to create detailed profiles about almost everyone living in the modern world - profiles that can predict our behavior better than our friends, families, or even partners. This is not only used to manipulate peoples’ opinions and voting behaviors, but more generally to influence consumer behavior at all levels. It is becoming increasingly clear that we are rapidly heading towards a cybernetic society, in which algorithms and social bots aim to control both the societal dynamics and individual behaviors. span lang="EN-US" style="font-family: However there are also silver linings: most of the threats that have accumulated over the past years have been identified and regulations are on the way to being introduced. Furthermore, entirely novel approaches based on blockchain technology and other developments derived from complexity science offer the possibility of entirely redefining collective trust and building platforms to support our core societal values. span lang="EN-US" style="font-family: This book conveys an encouraging vision of the future and provides a sketch of how it may look: The road to digital enlightenment is still open, but it needs to be taken now./pbrp
The topic of urban life and the ambient in smart cities, learning cities, and future cities is a timely one, fitting as it does in the world today by responding in an interdisciplinary way across many areas of research and practice. It is essential for researchers to think about and engage with the notion of flourishing in increasingly challenging environments in smarter ways. Urban Life and the Ambient in Smart Cities, Learning Cities, and Future Cities expands upon explorations of urban life to the ambient. As such, perspectives are offered in this work on urban life in the context of smart cities, learning cities, and future cities, enriched by understandings of the ambient, infusing the interactions of people and technologies in 21st-century environments with increased awareness, at the moment. Covering topics such as ambient learning, smart homes, and extended realities, this premier reference work is an essential resource for students and educators of higher education, architects, urban planners, instructional designers, sociologists, city officials, community leaders, librarians, researchers, and academicians.
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.
Machine learning algorithms and artificial intelligence influence many aspects of life today. This report identifies some of their shortcomings and associated policy risks and examines some approaches for combating these problems.