Self-Tracking


Book Description

What happens when people turn their everyday experience into data: an introduction to the essential ideas and key challenges of self-tracking. People keep track. In the eighteenth century, Benjamin Franklin kept charts of time spent and virtues lived up to. Today, people use technology to self-track: hours slept, steps taken, calories consumed, medications administered. Ninety million wearable sensors were shipped in 2014 to help us gather data about our lives. This book examines how people record, analyze, and reflect on this data, looking at the tools they use and the communities they become part of. Gina Neff and Dawn Nafus describe what happens when people turn their everyday experience—in particular, health and wellness-related experience—into data, and offer an introduction to the essential ideas and key challenges of using these technologies. They consider self-tracking as a social and cultural phenomenon, describing not only the use of data as a kind of mirror of the self but also how this enables people to connect to, and learn from, others. Neff and Nafus consider what's at stake: who wants our data and why; the practices of serious self-tracking enthusiasts; the design of commercial self-tracking technology; and how self-tracking can fill gaps in the healthcare system. Today, no one can lead an entirely untracked life. Neff and Nafus show us how to use data in a way that empowers and educates.




Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance


Book Description

This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.




The Algebraic Mind


Book Description

In The Algebraic Mind, Gary Marcus attempts to integrate two theories about how the mind works, one that says that the mind is a computer-like manipulator of symbols, and another that says that the mind is a large network of neurons working together in parallel. Resisting the conventional wisdom that says that if the mind is a large neural network it cannot simultaneously be a manipulator of symbols, Marcus outlines a variety of ways in which neural systems could be organized so as to manipulate symbols, and he shows why such systems are more likely to provide an adequate substrate for language and cognition than neural systems that are inconsistent with the manipulation of symbols. Concluding with a discussion of how a neurally realized system of symbol-manipulation could have evolved and how such a system could unfold developmentally within the womb, Marcus helps to set the future agenda of cognitive neuroscience.




Artificial Intelligence for the Internet of Everything


Book Description

Artificial Intelligence for the Internet of Everything considers the foundations, metrics and applications of IoE systems. It covers whether devices and IoE systems should speak only to each other, to humans or to both. Further, the book explores how IoE systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems. It examines the meaning, value and effect that IoT has had and may have on ordinary life, in business, on the battlefield, and with the rise of intelligent and autonomous systems. Based on an artificial intelligence (AI) perspective, this book addresses how IoE affects sensing, perception, cognition and behavior. Each chapter addresses practical, measurement, theoretical and research questions about how these "things may affect individuals, teams, society or each other. Of particular focus is what may happen when these "things begin to reason, communicate and act autonomously on their own, whether independently or interdependently with other "things. - Considers the foundations, metrics and applications of IoE systems - Debates whether IoE systems should speak to humans and each other - Explores how IoE systems affect targeted audiences and society - Discusses theoretical IoT ecosystem models




Emotional AI


Book Description

What happens when media technologies are able to interpret our feelings, emotions, moods, and intentions? In this cutting edge new book, Andrew McStay explores that very question and argues that these abilities result in a form of technological empathy. Offering a balanced and incisive overview of the issues raised by ‘Emotional AI’, this book: Provides a clear account of the social benefits and drawbacks of new media trends and technologies such as emoji, wearables and chatbots Demonstrates through empirical research how ‘empathic media’ have been developed and introduced both by start-ups and global tech corporations such as Facebook Helps readers understand the potential implications on everyday life and social relations through examples such as video-gaming, facial coding, virtual reality and cities Calls for a more critical approach to the rollout of emotional AI in public and private spheres Combining established theory with original analysis, this book will change the way students view, use and interact with new technologies. It should be required reading for students and researchers in media, communications, the social sciences and beyond.




AI and education


Book Description

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]




Deep Medicine


Book Description

A Science Friday pick for book of the year, 2019 One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.




The Fourth Industrial Revolution


Book Description

World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolu­tion, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wear­able sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manu­facturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individu­als. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frame­works that advance progress.




Heartificial Intelligence


Book Description

Algorithms will soon know more about us than we know ourselves Where should machine automation end? Is it acceptable to have a digital assistant arrange your calendar, but not to have a robot spouse? Are companion robots acceptable for seniors in need of comfort, but not okay for toddlers exposed to emotional software that could influence their behavior? Is it desirable to live a life within the virtual reality of Facebook’s Oculus Rift, but not if your thoughts are sold to advertisers who manipulate your purchases? We’ve entered an era where a myriad of personalization algorithms influence our every decision, and the lines between human assistance, automation, and extinction have blurred. We need to create ethical standards for the Artificial Intelligence usurping our lives, and allow individuals to control their identity based on their values. Otherwise, we sacrifice our humanity for productivity versus purpose and for profits versus people. Featuring pragmatic solutions drawing on economics, emerging technologies, and positive psychology, Heartificial Intelligence provides the first values-driven approach to algorithmic living—a definitive roadmap to help humanity embrace the present and positively define their future. Each chapter opens with a fictional vignette, helping readers imagine how they would respond to various Artificial Intelligence scenarios while demonstrating the need to codify their values, as the algorithms dominating society today are already doing. Funny, poignant, and accessible, this book paints a vivid portrait of how our lives might look in either a dystopia of robotic and corporate dominance, or a utopia where humans use technology to enhance our natural abilities to evolve into a long-lived, super-intelligent, and altruistic species.




Artificial Intelligence in Medicine


Book Description

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.