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The Mental Health of Gifted Intelligent Machines explores the increasingly sophisticated behaviours of developing AI and how we can ensure it will have emotional resilience, ethical strength and an ability to think in a new and enhanced way. Its primary aim is to change how we understand the world by investigating humanity as an intelligent being, examining and contrasting human and artificial intelligence. The book considers what we can learn from the likely mental health issues that will occur with increasingly sophisticated aspects of machine intelligence and how they will reflect the human condition. It asks questions about our identity in a deeply uncertain and disruptive ever-changing world; how we will improve and enhance our psychological intelligence to meet the increasing complications and demands of the future; and what we need to do, now, to be psychologically intelligent enough to live a full meaningful life in a new world evolving around us. The book argues that changes in our understanding of mental health, psychology and our view of intelligence will challenge huge aspects of our fundamental beliefs and assumptions and that it is essential we explore new arenas to further understand both our own human psychological issues and mental health as we develop gifted intelligent machines. It is a must read for all students, researchers and professionals involved with AI, gifted education, consciousness and mental health.
Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management.
Research shows that by improving the wellbeing of learners, we also improve their learning. Effective Learning and Mental Wellbeing is a crucial resource, filled with ready-to-use and thought-provoking activities that support wellbeing within your school, college, organisation, community group or on your own. Woven throughout are ideas and activities that support learning and wellbeing for many different kinds of learner. Supported by well-researched content, this essential book will enrich and improve both the wellbeing and the learning of all who use it. Areas covered include but are not limited to: How we learn and blocks to learning Mental health and self-efficacy Positive steps to mental wellbeing Wellbeing in the connected learning community The future of wellbeing and learning This book is an essential resource for teachers, therapists, health professionals, parents or carers and those in the community who work to improve learning through improving wellbeing.
Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings
The Mental Health of Gifted Intelligent Machines explores the increasingly sophisticated behaviours of developing AI and how we can ensure it will have emotional resilience, ethical strength and an ability to think in a new and enhanced way. Its primary aim is to change how we understand the world by investigating humanity as an intelligent being, examining and contrasting human and artificial intelligence. The book considers what we can learn from the likely mental health issues that will occur with increasingly sophisticated aspects of machine intelligence and how they will reflect the human condition. It asks questions about our identity in a deeply uncertain and disruptive ever-changing world; how we will improve and enhance our psychological intelligence to meet the increasing complications and demands of the future; and what we need to do, now, to be psychologically intelligent enough to live a full meaningful life in a new world evolving around us. The book argues that changes in our understanding of mental health, psychology and our view of intelligence will challenge huge aspects of our fundamental beliefs and assumptions and that it is essential we explore new arenas to further understand both our own human psychological issues and mental health as we develop gifted intelligent machines. It is a must read for all students, researchers and professionals involved with AI, gifted education, consciousness and mental health.
Our brightest, most creative children and adults are often being misdiagnosed with behavioral and emotional disorders such as ADHD, Oppositional-Defiant Disorder, Bipolar, OCD, or Asperger?s. Many receive unneeded medication and inappropriate counseling as a result. Physicians, psychologists, and counselors are unaware of characteristics of gifted children and adults that mimic pathological diagnoses. Six nationally prominent health care professionals describe ways parents and professionals can distinguish between gifted behaviors and pathological behaviors. ?These authors have brought to light a widespread and serious problem?the wasting of lives from the misdiagnosis of gifted children and adults and the inappropriate treatment that often follows.? Jack G. Wiggins, Ph. D., Former President, American Psychological Association
As the relationship between AI machines and humans develops, we ask what it will mean to be an intelligent learner in an emerging, socio-dynamic learningscape. The need for a new global view of intelligence and education is the core discussion of this future-focussed collection of ideas, questions, and activities for learners to explore. This fascinating guide offers activities to understand what needs to be changed in our educations systems and our view of intelligence. As well as exploring AI, HI, the future of learning and caring for all learners, this book addresses fundamental questions such as: How do we educate ourselves for an increasingly uncertain future? What is the purpose of intelligence? How can a curriculum focussing on human curiosity and creativity be created? Who are we and what are we becoming? What will we invent now that AI exists? AI and Developing Human Intelligence will interest you, inform you, and empower your understanding of "intelligence" and where we are going on the next part of our journey in understanding what it is to be human now and tomorrow.
As a movement, transhumanism aims to upgrade the human body through science, constantly pushing back the limits of a person by using cutting-edge technologies to fix the human body and upgrade it beyond its natural abilities. Transhumanism can not only change human habits, but it can also change learning practices. By improving human learning, it improves the human organism beyond natural and biological limits. The Handbook of Research on Learning in the Age of Transhumanism is an essential research publication that discusses global values, norms, and ethics that relate to the diverse needs of learners in the digital world and addresses future priorities and needs for transhumanism. The book will identify and scrutinize the needs of learners in the age of transhumanism and examine best practices for transhumanist leaders in learning. Featuring topics such as cybernetics, pedagogy, and sociology, this book is ideal for educators, trainers, instructional designers, curriculum developers, professionals, researchers, academicians, policymakers, and librarians.
6736 references to literature about human intelligence. Citations arranged alphabetically by author. Topical outline and index provide subject approach.
This book explores the advancements and future challenges in biomedical application developments using breakthrough technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Signal Processing. It will also contribute to biosensors and secure systems,and related research. Applied Artificial Intelligence: A Biomedical Perspective begins by detailing recent trends and challenges of applied artificial intelligence in biomedical systems. Part I of the book presents the technological background of the book in terms of applied artificial intelligence in the biomedical domain. Part II demonstrates the recent advancements in automated medical image analysis that have opened ample research opportunities in the applications of deep learning to different diseases. Part III focuses on the use of cyberphysical systems that facilitates computing anywhere by using medical IoT and biosensors and the numerous applications of this technology in the healthcare domain. Part IV describes the different signal processing applications in the healthcare domain. It also includes the prediction of some human diseases based on the inputs in signal format. Part V highlights the scope and applications of biosensors and security aspects of biomedical images. The book will be beneficial to the researchers, industry persons, faculty, and students working in biomedical applications of computer science and electronics engineering. It will also be a useful resource for teaching courses like AI/ML, medical IoT, signal processing, biomedical engineering, and medical image analysis.