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AI for Disease Surveillance and Pandemic Intelligence: Intelligent Disease Detection in Action (Studies in Computational Intelligence #1013)
by Simone Bianco Arash Shaban-Nejad Martin MichalowskiThis book aims to highlight the latest achievements in the use of artificial intelligence for digital disease surveillance, pandemic intelligence, as well as public and clinical health surveillance. The edited book contains selected papers presented at the 2021 Health Intelligence workshop, co-located with the Association for the Advancement of Artificial Intelligence (AAAI) annual conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. While disease surveillance has always been a crucial process, the recent global health crisis caused by COVID-19 has once again highlighted our dependence on intelligent surveillance infrastructures that provide support for making sound and timely decisions. This book provides information for researchers, students, industry professionals, and public health agencies interested in the applications of AI in population health and personalized medicine.
AI for Diversity (AI for Everything)
by Roger A. SøraaArtificial intelligence (AI) is increasingly impacting many aspects of people’s lives across the globe, from relatively mundane technology to more advanced digital systems that can make their own decisions. While AI has great potential, it also holds great peril depending on how it is designed and used. AI for Diversity questions how AI technology can lead to inclusion or exclusion for diverse groups in society. The way data is selected, trained, used, and embedded into societies can have unfortunate consequences unless we critically investigate the dangers of systems left unchecked, and can lead to misogynistic, homophobic, racist, ageist, transphobic, or ableist outcomes. This book encourages the reader to take a step back to see how AI is impacting diverse groups of people and how diversity-awareness strategies can impact AI.
AI for Finance (AI for Everything)
by Edward P. TsangFinance students and practitioners may ask: can machines learn everything? Could AI help me? Computing students or practitioners may ask: which of my skills could contribute to finance? Where in finance should I pay attention? This book aims to answer these questions. No prior knowledge is expected in AI or finance. To finance students and practitioners, this book will explain the promise of AI, as well as its limitations. It will cover knowledge representation, modelling, simulation and machine learning, explaining the principles of how they work. To computing students and practitioners, this book will introduce the financial applications in which AI has made an impact. This includes algorithmic trading, forecasting, risk analysis portfolio optimization and other less well-known areas in finance. This book trades depth for readability. It aims to help readers to decide whether to invest more time into the subject. This book contains original research. For example, it explains the impact of ignoring computation in classical economics. It explains the relationship between computing and finance and points out potential misunderstandings between economists and computer scientists. The book also introduces Directional Change and explains how this can be used.
AI for Health Equity and Fairness: Leveraging AI to Address Social Determinants of Health (Studies in Computational Intelligence #1164)
by Simone Bianco Arash Shaban-Nejad Martin MichalowskiThis book aims to highlight the latest achievements in the use of AI for improving Health Equity and Fairness. The edited volume contains selected papers presented at the 2024 Health Intelligence workshop, co-located with the Thirty-Eight Association for the Advancement of Artificial Intelligence (AAAI) conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. This book provides information for researchers, students, industry professionals, clinicians, and public health agencies interested in the applications of AI in medicine and public health.
AI for Immunology (AI for Everything)
by Louis J. CataniaThe bioscience of immunology has given us a better understanding of human health and disease. Artificial intelligence (AI) has elevated that understanding and its applications in immunology to new levels. Together, AI for immunology is an advancing horizon in health care, disease diagnosis, and prevention. From the simple cold to the most advanced autoimmune disorders and now pandemics, AI for immunology is unlocking the causes and cures. Key features: A highly accessible and wide-ranging short introduction to AI for immunology Includes a chapter on COVID-19 and pandemics Includes scientific and clinical considerations, as well as immune and autoimmune diseases
AI for Learning (AI for Everything)
by Carmel Kent Benedict du BoulayWhat is artificial intelligence (AI)? How can AI help a learner, a teacher or a system designer? What are the positive impacts of AI on human learning? AI for Learning examines how artificial intelligence can, and should, positively impact human learning, whether it be in formal or informal educational and training contexts. The notion of ‘can’ is bound up with ongoing technological developments. The notion of ‘should’ is bound up with an ethical stance that recognises the complementary capabilities of human and artificial intelligence, as well as the objectives of doing good, not doing harm, increasing justice and maintaining fairness. The book considers the different supporting roles that can help a learner – from AI as a tutor and learning aid to AI as a classroom moderator, among others – and examines both the opportunities and risks associated with each.
AI for Physics (AI for Everything)
by Volker KnechtWritten in accessible language without mathematical formulas, this short book provides an overview of the wide and varied applications of artificial intelligence (AI) across the spectrum of physical sciences. Focusing in particular on AI's ability to extract patterns from data, known as machine learning (ML), the book includes a chapter on important machine learning algorithms and their respective applications in physics. It then explores the use of ML across a number of important sub-fields in more detail, ranging from particle, molecular and condensed matter physics, to astrophysics, cosmology and the theory of everything. The book covers such applications as the search for new particles and the detection of gravitational waves from the merging of black holes, and concludes by discussing what the future may hold.
AI for Radiology (AI for Everything)
by Oge MarquesArtificial intelligence (AI) has revolutionized many areas of medicine and is increasingly being embraced. This book focuses on the integral role of AI in radiology, shedding light on how this technology can enhance patient care and streamline professional workflows. This book reviews, explains, and contextualizes some of the most current, practical, and relevant developments in artificial intelligence and deep learning in radiology and medical image analysis. AI for Radiology presents a balanced viewpoint of the impact of AI in these fields, underscoring that AI technologies are not intended to replace radiologists but rather to augment their capabilities, freeing professionals to focus on more complex cases. This book guides readers from the basic principles of AI to their practical applications in radiology, moving from the role of data in AI to the ethical and regulatory considerations of using AI in radiology and concluding with a selection of resources for further exploration. This book has been crafted with a diverse readership in mind. It is a valuable asset for medical professionals eager to stay up to date with AI developments, computer scientists curious about AI’s clinical applications, and anyone interested in the intersection of healthcare and technology.
AI for Robotics: Toward Embodied and General Intelligence in the Physical World
by Alishba Imran Keerthana GopalakrishnanThis book approaches robotics from a deep learning perspective. Artificial intelligence (AI) has transformed many fields, including robotics. This book shows you how to reimagine decades-old robotics problems as AI problems and is a handbook for solving problems using modern techniques in an era of large foundation models. The book begins with an introduction to general-purpose robotics, how robots are modeled, and how physical intelligence relates to the movement of building artificial general intelligence, while giving you an overview of the current state of the field, its challenges, and where we are headed. The first half of this book delves into defining what the problems in robotics are, how to frame them as AI problems, and the details of how to solve them using modern AI techniques. First, we look at robot perception and sensing to understand how robots perceive their environment, and discuss convolutional networks and vision transformers to solve robotics problems such as segmentation, classification, and detection in two and three dimensions. The book then details how to apply large language and multimodal models for robotics, and how to adapt them to solve reasoning and robot control. Simulation, localization, and mapping and navigation are framed as deep learning problems and discussed with recent research. Lastly, the first part of this book discusses reinforcement learning and control and how robots learn via trial and error and self-play. The second part of this book is concerned with applications of robotics in specialized contexts. You will develop full stack knowledge by applying the techniques discussed in the first part to real-world use cases. Individual chapters discuss the details of building robots for self-driving, industrial manipulation, and humanoid robots. For each application, you will learn how to design these systems, the prevalent algorithms in research and industry, and how to assess trade-offs for performance and reliability. The book concludes with thoughts on operations, infrastructure, and safety for data-driven robotics, and outlooks for the future of robotics and machine learning. In summary, this book offers insights into cutting-edge machine learning techniques applied in robotics, along with the challenges encountered during their implementation and practical strategies for overcoming them. What You Will Learn Explore ML applications in robotics, covering perception, control, localization, planning, and end-to-end learning Delve into system design, and algorithmic and hardware considerations for building efficient ML-integrated robotics systems Discover robotics applications in self-driving, manufacturing, and humanoids and their practical implementations Understand how machine learning and robotics benefit current research and organizations Who This Book Is For Software and AI engineers eager to learn about robotics, seasoned robotics and mechanical engineers looking to stay at the cutting edge by integrating modern AI, and investors, executives or decision makers seeking insights into this dynamic field
AI for School Teachers (AI for Everything)
by Rose Luckin Mutlu Cukurova Karine GeorgeWhat is artificial intelligence? Can I realistically use it in my school? What’s best done by human intelligence vs. artificial intelligence, and how do I bring these strengths together? What would it look like for me, and my school, to be AI Ready? AI for School Teachers will help teachers and headteachers understand enough about AI to build a strategy for how it can be used in their school. Examining the needs of schools to ensure they are ready to leverage the power of AI and drawing examples from early years to high school students, this book outlines the educational implications and benefits that AI brings to school education in practical ways. It develops an understanding of what AI is and isn't and how we define and measure what we value and provides a framework which supports a step-by-step approach to developing an AI mindset, focusing on ways to improve educational opportunities for students with evidence-informed interventions.
AI for Social Good: Using Artificial Intelligence to Save the World
by Rahul DodhiaUnderstand the real power of AI and and its ability to shape the future for the better. AI For Social Good: Using Artificial Intelligence to Save the World bridges the gap between the current state of reality and the incredible potential of AI to change the world. From humanitarian and environmental concerns to advances in art and science, every area of life stands poised to make a quantum leap into the future. The problem? Too few of us really understand how AI works and how to integrate it into our policies and projects. In this book, Rahul Dodhia, Deputy Director of Microsoft’s AI for Good Research Lab, offers a nontechnical exploration of artificial intelligence tools—how they’re built, what they can and can’t do, and the raw material that teaches them what they “know.” Readers will also find an inventory of common challenges they might face when integrating AI into their work. You'll also read more on: The potential for AI to solve longstanding issues and improve lives Learn how you can tap into the power of AI, regardless of the size of your organization Gain an understanding of how AI works and how to communicate with AI scientists to create new solutions Understand the real risks of implementing AI and how to avoid potential pitfalls Real-life examples and stories that demonstrate how teams of AI specialists, project managers, and subject matter experts can achieve remarkable products. Written for anyone who is curious about AI, and especially useful for policymakers, project managers, and leaders who work alongside AI, AI For Social Good provides discussions of how AI scientists create artificially intelligent systems, and how AI can be used ethically (or unethically) to transform society. You’ll also find a discussion of how governments can become more flexible, helping regulations keep up with the fast pace of change in technology.
AI for Sports (AI for Everything)
by Chris Brady Karl Tuyls Shayegan OmidshafieiIt seems that artificial intelligence (AI) is always just five years away, but it never arrives. Recently, however, developments have made the practical utility of game theory a genuine reality. Will sport provide the petri dish in which AI will prove itself? What do domain specialists like managers and coaches want to know that they can’t currently find out, and can AI provide the answer? What competitive advantages might AI provide for recruitment, performance and tactics, health and fitness, pedagogy, broadcasting, eSports, gambling and stadium design in the future? Written by leading experts in both sports management and AI, AI for Sports begins to answer these and many other questions on the future of AI for sports.
AI in Business: Volume 1 (Studies in Systems, Decision and Control #515)
by Reem Khamis Amina BuallayThis book is a comprehensive guide to understanding the potential of artificial intelligence (AI) in improving business functions, as well as the limitations and challenges that come with its implementation. In this book, readers will learn about the various opportunities that AI presents in business, including how it can automate routine tasks, reduce errors, and increase efficiency. The book covers a range of topics, including how AI can be used in financial reporting, auditing, fraud detection, and tax preparation. However, the book also explores the limitations of AI in business, such as the need for skilled professionals, data quality, and the potential for bias. It examines the challenges that companies face when implementing AI in business functions, including the need for ethical considerations, transparency, and accountability. The book is written for business professionals, business leaders, and anyone interested in the potential of AI in business functions. It offers practical advice on how to implement AI effectively and provides insights into the latest developments in AI technology. Through case studies and real-world examples, readers will gain a deeper understanding of how AI can be used to enhance business functions, as well as the potential pitfalls and limitations to be aware of. Overall, "AI in Business: Opportunities and Limitations" is an essential guide for anyone looking to harness the power of AI to improve their business functions, and to stay ahead in an increasingly competitive business environment.
AI in Business: Volume 2 (Studies in Systems, Decision and Control #516)
by Reem Khamis Amina BuallayThis book is a comprehensive guide to understanding the potential of artificial intelligence (AI) in improving business functions, as well as the limitations and challenges that come with its implementation. In this book, readers will learn about the various opportunities that AI presents in business, including how it can automate routine tasks, reduce errors, and increase efficiency. The book covers a range of topics, including how AI can be used in financial reporting, auditing, fraud detection, and tax preparation. However, the book also explores the limitations of AI in business, such as the need for skilled professionals, data quality, and the potential for bias. It examines the challenges that companies face when implementing AI in business functions, including the need for ethical considerations, transparency, and accountability. The book is written for business professionals, business leaders, and anyone interested in the potential of AI in business functions. It offers practical advice on how to implement AI effectively and provides insights into the latest developments in AI technology. Through case studies and real-world examples, readers will gain a deeper understanding of how AI can be used to enhance business functions, as well as the potential pitfalls and limitations to be aware of. Overall, this book is an essential guide for anyone looking to harness the power of AI to improve their business functions and to stay ahead in an increasingly competitive business environment.
AI in Chemical Engineering: Unlocking the Power Within Data
by José A. Romagnoli Luis Briceño-Mena Vidhyadhar ManeeIndustry 4.0 is revolutionizing chemical manufacturing. Today's chemical companies are swiftly embracing the digital era, recognizing the significant benefits of interconnected products, production equipment, and personnel. As technology advances and production volumes grow, there is an increasing need for new computational tools and innovative solutions to address everyday challenges. AI in Chemical Engineering: Unlocking the Power Within Data introduces readers to the essential concepts of machine learning and their application in the chemical and process industries, aiming to enhance efficiency, adaptability, and profitability. This work delves into the transformation of traditional plant operations into integrated and intelligent systems, providing readers with a foundation for developing and understanding the tools necessary for data collection and analysis, thereby gaining valuable insights and practical applications. Introduces the principles and applications of unsupervised learning and discusses the role of machine learning in extracting information from plant data and transforming it into knowledge Conveys the concepts, principles, and applications of supervised learning, setting the stage for developing advanced monitoring systems, complex predictive models, and advanced computer vision applications Explores implementation of reinforced learning ideas for chemical process control and optimization, investigating various model structures and discussing their practical implementation in both simulation and experimental units Incorporates sample code examples in Python to illustrate key concepts Includes real-life case studies in the context of chemical engineering and covers a wide variety of chemical engineering applications from oil and gas to bioengineering and electrochemistry Clearly defines types of problems in chemical engineering subject to AI solutions and relates them to subfields of AI This practical text, designed for advanced chemical engineering students and industry practitioners, introduces concepts and theories in a logical and sequential manner. It serves as an essential resource, helping readers understand both current and emerging developments in this important and evolving field.
AI in Healthcare: How Artificial Intelligence Is Changing IT Operations and Infrastructure Services
by Robert ShimonskiThe best source for cutting-edge insights into AI in healthcare operations AI in Healthcare: How Artificial Intelligence Is Changing IT Operations and Infrastructure Services collects, organizes and provides the latest, most up-to-date research on the emerging technology of artificial intelligence as it is applied to healthcare operations. Written by a world-leading technology executive specializing in healthcare IT, this book provides concrete examples and practical advice on how to deploy artificial intelligence solutions in your healthcare environment. AI in Healthcare reveals to readers how they can take advantage of connecting real-time event correlation and response automation to minimize IT disruptions in critical healthcare IT functions. This book provides in-depth coverage of all the most important and central topics in the healthcare applications of artificial intelligence, including: Healthcare IT AI Clinical Operations AI Operational Infrastructure Project Planning Metrics, Reporting, and Service Performance AIOps in Automation AIOps Cloud Operations Future of AI Written in an accessible and straightforward style, this book will be invaluable to IT managers, administrators, and engineers in healthcare settings, as well as anyone with an interest or stake in healthcare technology.
AI in Manufacturing and Green Technology: Methods and Applications (Green Engineering and Technology)
by Sambit Kumar Mishra, Zdzislaw Polkowski, Samarjeet Borah, Ritesh DashThis book focuses on environmental sustainability by employing elements of engineering and green computing through modern educational concepts and solutions. It visualizes the potential of artificial intelligence, enhanced by business activities and strategies for rapid implementation, in manufacturing and green technology. This book covers utilization of renewable resources and implementation of the latest energy-generation technologies. It discusses how to save natural resources from depletion and illustrates facilitation of green technology in industry through usage of advanced materials. The book also covers environmental sustainability and current trends in manufacturing. The book provides the basic concepts of green technology, along with the technology aspects, for researchers, faculty, and students.
AI in Material Science: Revolutionizing Construction in the Age of Industry 4.0
by Syed Saad Syed Ammad Kumeel RasheedThis book explores the transformative impact of artificial intelligence on material science and construction practices in the Industry 4.0 landscape. It enquires into AI history and applications, examining material optimization, smart materials, and AI in construction. Covering automation, robotics, and AI-assisted design, the book provides insights into ethical considerations and future trends. A modern reference for scholars and professionals, it bridges academia and practical applications in the dynamic intersection of AI and materials science.
AI in Wireless for Beyond 5G Networks
by Yulei Wu Sukhdeep Singh Madhan Raj Kanagarathinam Payam Barnaghi Kaustubh Joshi Mohan Rao GnsArtificial intelligence (AI) is a game changer in many domains, and wireless communication networks are no exception. With the advent of 5G networks, we have witnessed rapid growth in wireless connectivity, which has led to unprecedented opportunities for innovation and new use cases. However, as we move beyond 5G (B5G), the challenges and opportunities are set to become even more significant, offering new, previously unimaginable services. AI in Wireless for Beyond 5G Networks provides a comprehensive overview of the use of AI in wireless communication for B5G networks. The authors draw on their expertise in the field to explore the latest developments in AI technologies and their applications in B5G wireless communication systems. The book discusses a wide range of topics, including enabling AI technologies, architecture, and applications of AI from smartphones, radio access networks (RANs), edge and core networks, and application service providers. It also discusses the trends in on-device AI for B5G networks. This book is written in an accessible style, making it an ideal resource for academics, researchers, and industry professionals in wireless communication. It provides valuable insights into the latest field trends and developments and practical possibilities for implementing AI technologies in wireless communication systems. Above all, this book is a testament to the power of collaboration and innovation in wireless communication. The authors’ dedication and expertise have produced a valuable resource for anyone interested in the latest AI and wireless communication developments. This book will inspire and inform readers, and we highly recommend it to scholars interested in the future of AI in wireless communication.
AI in and for Africa: A Humanistic Perspective (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)
by Susan Brokensha Eduan Kotzé Burgert A. SenekalAI in and for Africa: A Humanistic Perspective explores the convoluted intersection of artificial intelligence (AI) with Africa’s unique socio-economic realities. This book is the first of its kind to provide a comprehensive overview of how AI is currently being deployed on the African continent. Given the existence of significant disparities in Africa related to gender, race, labour, and power, the book argues that the continent requires different AI solutions to its problems, ones that are not founded on technological determinism or exclusively on the adoption of Eurocentric or Western-centric worldviews. It embraces a decolonial approach to exploring and addressing issues such as AI’s diversity crisis, the absence of ethical policies around AI that are tailor-made for Africa, the ever-widening digital divide, and the ongoing practice of dismissing African knowledge systems in the contexts of AI research and education. Although the book suggests a number of humanistic strategies with the goal of ensuring that Africa does not appropriate AI in a manner that is skewed in favour of a privileged few, it does not support the notion that the continent should simply opt for a "one-size-fits-all" solution either. Rather, in light of Africa’s rich diversity, the book embraces the need for plurality within different regions’ AI ecosystems. The book advocates that Africa-inclusive AI policies incorporate a relational ethics of care which explicitly addresses how Africa’s unique landscape is entwined in an AI ecosystem. The book also works to provide actionable AI tenets that can be incorporated into policy documents that suit Africa’s needs. This book will be of great interest to researchers, students, and readers who wish to critically appraise the different facets of AI in the context of Africa, across many areas that run the gamut from education, gender studies, and linguistics to agriculture, data science, and economics. This book is of special appeal to scholars in disciplines including anthropology, computer science, philosophy, and sociology, to name a few.
AI in the Wild: Sustainability in the Age of Artificial Intelligence (One Planet)
by Peter DauvergneExamining the potential benefits and risks of using artificial intelligence to advance global sustainability.Drones with night vision are tracking elephant and rhino poachers in African wildlife parks and sanctuaries; smart submersibles are saving coral from carnivorous starfish on Australia's Great Barrier Reef; recycled cell phones alert Brazilian forest rangers to the sound of illegal logging. The tools of artificial intelligence are being increasingly deployed in the battle for global sustainability. And yet, warns Peter Dauvergne, we should be cautious in declaring AI the planet's savior. In AI in the Wild, Dauvergne avoids the AI industry-powered hype and offers a critical view, exploring both the potential benefits and risks of using artificial intelligence to advance global sustainability.
AI on the Edge with Security: Foundations and Practices
by Naresh Kumar Sehgal Manoj Saxena Dhaval N. ShahThis book provides readers with an overview of the next generation of Cloud computing with AI, evolving to minimize latency and address privacy/security concerns of many customers. This book will highlight the associated problems and propose new solutions for performing AI and ML at the edge of computing networks.
AI to Improve e-Governance and Eminence of Life: Kalyanathon 2020 (Studies in Big Data #130)
by Jyotsna Kumar Mandal Somnath Mukhopadhyay Sudipta Roy Sunita SarkarThe volume presents research works on developing Artificial Intelligence based algorithms and methodologies for making social good that too to a notable one. The book discusses latest findings on efficient technological solutions of e-governance and other areas of life from the leading researchers in the field. The prime focus is on solving socio-economic technical problems using state-of-the-art research findings like fuzzy computing, evolutionary and hybrid frameworks, neuro computing, etc., along with other AI based computation platforms. The topics covered include solution frameworks using Artificial Intelligence based models in application areas like agriculture and rural development, road accident, travel and tourism, solid waste management, rural medical care, crowd sourced election monitoring system, ragging, rape and other abuses, cyber criminals and cyber bullying, disaster management, social good, etc. The book offers a valuable resource for all undergraduate, postgraduate students and researchers interested in exploring solution frameworks for social good problems using artificial intelligence.
AI überleben: Das Versprechen und die Gefahr Artifizielle Intelligenz
by Janardhan MarappaDies ist das Jahrhundert zweier Singularitäten – der wirtschaftlichen Singularität (technologische Arbeitslosigkeit) und der technologischen Singularität (Intelligenzexplosion). Beides birgt enorme Chancen und enorme Herausforderungen. Wenn wir sie erfolgreich verwalten, ist unsere Zukunft als Spezies mehr als wunderbar. Wenn wir versagen, könnte es miserabel sein - und vielleicht kurz. Der Treiber ist Artifizelle Intelligenz (AI) - die leistungsstärkste Technologie der Menschheit. Software, die Probleme löst und Daten in Erkenntnisse umwandelt, hat unser Leben bereits revolutioniert, und die Revolution beschleunigt sich. Das Argument dieses Buches ist, dass wir die stattfindenden Veränderungen überwachen und Richtlinien verabschieden sollten, die die bestmöglichen Ergebnisse fördern. Die Bandbreite der möglichen Ergebnisse ist groß, vom Schrecklichen bis zum Wunderbaren, und sie sind nicht vorherbestimmt. Sie werden zum Teil durch Glück, zum Teil durch ihre eigene interne Logik, zum Teil aber auch durch die Politik auf allen Ebenen der Gesellschaft ausgewählt. Automatisierung und Superintelligenz sind die beiden Entwicklungen, von denen wir bereits sehen, dass sie wahrscheinlich enorme Auswirkungen haben werden. Automatisierung könnte zu einer wirtschaftlichen Singularität und der Entwicklung einer völlig anderen Art von Wirtschaft führen. Wenn wir das falsch verstehen, könnte eine Elite die Produktionsmittel besitzen und den Rest von uns in einem dystopischen technologischen autoritären Regime unterdrücken. Wenn wir es richtig machen, könnten wir eine Wirtschaft des radikalen Überflusses genießen, in der niemand arbeiten muss, um seinen Lebensunterhalt zu verdienen, und wir alle frei sind, Spaß zu haben, unseren Geist zu dehnen und unsere Fähigkeiten voll zu entfalten. Die Ankunft der Superintelligenz wird, falls und wenn sie eintritt, eine technologische Singularität darstellen, die das bedeutendste Ere
AI, Consciousness and The New Humanism: Fundamental Reflections on Minds and Machines
by Sangeetha Menon Tilak Agerwala Saurabh TodariyaThis edited volume presents perspectives from computer science, information theory, neuroscience and brain imaging, aesthetics, social sciences, psychiatry, and philosophy to answer frontier questions related to artificial intelligence and human experience. Can a machine think, believe, aspire and be purposeful as a human? What is the place in the machine world for hope, meaning and transformative enlightenment that inspires human existence? How, or are, the minds of machines different from that of humans and other species? These questions are responded to along with questions in the intersection of health, intelligence and the brain. It highlights the place of consciousness by attempting to respond to questions with the help of fundamental reflections on human existence, its life-purposes and machine intelligence. The volume is a must-read for interdisciplinary and multidisciplinary researchers in humanities and social sciences and philosophy of science who wish to understand the future of AI and society.