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Author: Mark V. Albert
Publisher: Springer Nature
ISBN: 3030847292
Category : Education
Languages : en
Pages : 364
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Book Description
This edited volume is based on contributions from the TCET-AECT “Human-Technology Frontier: Understanding the Learning of Now to Prepare for the Work of the Future Symposium” held in Denton, Texas on May 16-18, sponsored by AECT. The authors embrace an integrative approach to designing and implementing advances technologies in learning and instruction, and focus on the emerging themes of artificial intelligence, human-computer interactions, and the resulting instructional design. The volume will be divided into four parts: (1) Trends and future in learning and learning technologies expected in the next 10 years; (2) Technologies likely to have a significant impact on learning in the next 10 years; (3) Challenges that will need to be addressed and resolved in order to achieve significant and sustained improvement in learning; and (4) Reflections and insights from the Symposium that should be pursued and that can form the basis for productive research collaborations. The primary audience for this volume is academics and researchers in disciplines such as artificial intelligence, cognitive science, computer science, educational psychology, instructional design, human-computer interactions, information science, library science, and technology integration.
Author: Mark V. Albert
Publisher: Springer Nature
ISBN: 3030847292
Category : Education
Languages : en
Pages : 364
Get Book
Book Description
This edited volume is based on contributions from the TCET-AECT “Human-Technology Frontier: Understanding the Learning of Now to Prepare for the Work of the Future Symposium” held in Denton, Texas on May 16-18, sponsored by AECT. The authors embrace an integrative approach to designing and implementing advances technologies in learning and instruction, and focus on the emerging themes of artificial intelligence, human-computer interactions, and the resulting instructional design. The volume will be divided into four parts: (1) Trends and future in learning and learning technologies expected in the next 10 years; (2) Technologies likely to have a significant impact on learning in the next 10 years; (3) Challenges that will need to be addressed and resolved in order to achieve significant and sustained improvement in learning; and (4) Reflections and insights from the Symposium that should be pursued and that can form the basis for productive research collaborations. The primary audience for this volume is academics and researchers in disciplines such as artificial intelligence, cognitive science, computer science, educational psychology, instructional design, human-computer interactions, information science, library science, and technology integration.
Author: Rume Dominic
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Throughout human history, our pursuit of innovation and discovery has never ceased. With each passing generation, we build upon the works of those before us, striving to understand more about ourselves and the universe. In recent times, we have created machines that extraordinarily mirror human intelligence. As you read "From Code to Consciousness," you'll enter a realm where science meets philosophy, technology embraces humanity, and the lines between biological life and artificial intelligence begin to blur. This exploration delves into one of the most profound questions of our age: What does it mean for a machine to be conscious? It all begins with code, a set of programming instructions that enable computers to perform tasks, solve problems, and execute commands. Code has evolved from simple calculations to sophisticated algorithms that can mimic human thought patterns. But where does consciousness fit in? Consciousness is something deeply human, an internal experience that defies easy definition. It's our awareness of ourselves and the world around us. Can a machine possess this spark? Can code evolve into consciousness? To delve into these questions, we must explore various fields, from artificial intelligence and machine learning to neuroscience and ethics. As we create machines that can potentially feel, we are holding a mirror to our nature and asking what it means to be human in an age of intelligent machines. This book bridges two worlds, a nexus where science and philosophy intermingle, where the technical meets the existential. It invites you to ponder the profound, question the status quo, and imagine a future where the boundary between humans and machines is a gateway to new possibilities. "From Code to Consciousness" is your guide and companion in an incredible journey from the tangible to the mysterious. It challenges your thoughts, ignites your curiosity, and inspires you to see technology, humanity, and consciousness in a new light.
Author: Ben Shneiderman
Publisher: Oxford University Press
ISBN: 0192845292
Category : Computers
Languages : en
Pages : 390
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Book Description
The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity.
Author: Ann E Williams
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This is a book that examines the relationship between humans and artificial intelligence (AI) and explores ways to make AI more human-friendly. It discusses the current state of AI, its potential to transform our lives, and the ethical implications of its applications. The book proposes strategies to humanize AI, such as designing AI systems that are sensitive to human emotions and values, promoting transparency and accountability in the development and deployment of AI, and emphasizing collaboration between humans and machines. Overall, the book offers a balanced and insightful perspective on the future of AI and its relationship with humanity.
Author: Rajest, S. Suman
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 433
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Book Description
In the realm of psychological and brain sciences, there is a growing urgency to refine individual performance using personalized interventions that account for unique cognitive and biological attributes. Yet, the quest for such tailored approaches has proven challenging, as conventional methods often fall short. The limited integration of domain expertise and human judgment curtails the potential of artificial intelligence (AI) in effectively optimizing human performance, particularly in areas like customized training, health monitoring, and cognitive enhancement. Bridging the gap between AI capabilities and the specific requirements of individuals becomes crucial in meeting this rising demand. Advances in Artificial and Human Intelligence in the Modern Era present a transformative solution to tackle the prevailing challenges at the intersection of AI and human performance enhancement. This book delves deeply into the latest empirical research, literature reviews, and methodological advancements to introduce precision AI techniques for personalized interventions. By examining how the amalgamation of domain expertise and human insights can enhance AI performance, the book establishes a comprehensive framework for modeling individual distinctions and devising effective, tailored AI approaches. Tailored for academic scholars and researchers in psychological and brain sciences, computer science, and related fields, this book provides a comprehensive exploration of pioneering advancements in the convergence of artificial and human intelligence. Its diverse chapters encompass a wide array of topics, including the identification of mental health concerns, integration of human intelligence into AI tools, enhancement of reliability, and exploration of data standards. As it fuses expertise from these two disciplines, the book paves the way for a new era of personalized interventions with the potential to revolutionize human cognitive enhancement, training, and overall well-being.
Author: Shengquan Yu
Publisher: Springer Nature
ISBN: 9811627703
Category : Education
Languages : en
Pages : 205
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Book Description
This book systematically reviews a broad range of cases in education that utilize cutting-edge AI technologies. Furthermore, it introduces readers to the latest findings on the scope of AI in education, so as to inspire researchers from non-technological fields (e.g. education, psychology and neuroscience) to solve education problems using the latest AI techniques. It also showcases a number of established AI systems and products that have been employed for education. Lastly, the book discusses how AI can offer an enabling technology for critical aspects of education, typically including the learner, content, strategy, tools and environment, and what breakthroughs and advances the future holds. The book provides an essential resource for researchers, students and industrial practitioners interested and engaged in the fields of AI and education. It also offers a convenient handbook for non-professional readers who need a primer on AI in education, and who want to gain a deeper understanding of emerging trends in this domain.
Author: Ogata, Takashi
Publisher: IGI Global
ISBN: 1799848655
Category : Science
Languages : en
Pages : 409
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Book Description
The use of cognitive science in creating stories, languages, visuals, and characters is known as narrative generation, and it has become a trending area of study. Applying artificial intelligence (AI) techniques to story development has caught the attention of professionals and researchers; however, few studies have inherited techniques used in previous literary methods and related research in social sciences. Implementing previous narratology theories to current narrative generation systems is a research area that remains unexplored. Bridging the Gap Between AI, Cognitive Science, and Narratology With Narrative Generation is a collection of innovative research on the analysis of current practices in narrative generation systems by combining previous theories in narratology and literature with current methods of AI. The book bridges the gap between AI, cognitive science, and narratology with narrative generation in a broad sense, including other content generation, such as a novels, poems, movies, computer games, and advertisements. The book emphasizes that an important method for bridging the gap is based on designing and implementing computer programs using knowledge and methods of narratology and literary theories. In order to present an organic, systematic, and integrated combination of both the fields to develop a new research area, namely post-narratology, this book has an important place in the creation of a new research area and has an impact on both narrative generation studies, including AI and cognitive science, and narrative studies, including narratology and literary theories. It is ideally designed for academicians, researchers, and students, as well as enterprise practitioners, engineers, and creators of diverse content generation fields such as advertising production, computer game creation, comic and manga writing, and movie production.
Author: Toby Walsh
Publisher: Black Inc.
ISBN: 1743820259
Category : Technology & Engineering
Languages : en
Pages : 336
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Book Description
‘A compelling invitation to imagine the future we want’ —BRIAN CHRISTIAN, author of The Most Human Human By 2062 we will have built machines as intelligent as us – so the leading artificial intelligence and robotics experts predict. But what will this future look like? In 2062, world-leading researcher Toby Walsh considers the impact AI will have on work, war, economics, politics, everyday life and even death. Will automation take away most jobs? Will robots become conscious and take over? Will we become immortal machines ourselves, uploading our brains to the cloud? How will politics adjust to the post-truth, post-privacy digitised world? When we have succeeded in building intelligent machines, how will life on this planet unfold? Based on a deep understanding of technology, 2062 describes the choices we need to make today to ensure that the future remains bright. ‘Clarity and sanity in a world full of fog and uncertainty – a timely book about the race to remain human.’ —RICHARD WATSON, author of Digital Vs. Human and futurist-in-residence at Imperial College, London ‘One of the deepest questions facing humanity, pondered by a mind well and truly up to the task.’ —ADAM SPENCER, broadcaster
Author: Erik J. Larson
Publisher: Harvard University Press
ISBN: 0674259920
Category : Computers
Languages : en
Pages : 321
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Book Description
“Exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it.” —John Horgan “If you want to know about AI, read this book...It shows how a supposedly futuristic reverence for Artificial Intelligence retards progress when it denigrates our most irreplaceable resource for any future progress: our own human intelligence.” —Peter Thiel Ever since Alan Turing, AI enthusiasts have equated artificial intelligence with human intelligence. A computer scientist working at the forefront of natural language processing, Erik Larson takes us on a tour of the landscape of AI to reveal why this is a profound mistake. AI works on inductive reasoning, crunching data sets to predict outcomes. But humans don’t correlate data sets. We make conjectures, informed by context and experience. And we haven’t a clue how to program that kind of intuitive reasoning, which lies at the heart of common sense. Futurists insist AI will soon eclipse the capacities of the most gifted mind, but Larson shows how far we are from superintelligence—and what it would take to get there. “Larson worries that we’re making two mistakes at once, defining human intelligence down while overestimating what AI is likely to achieve...Another concern is learned passivity: our tendency to assume that AI will solve problems and our failure, as a result, to cultivate human ingenuity.” —David A. Shaywitz, Wall Street Journal “A convincing case that artificial general intelligence—machine-based intelligence that matches our own—is beyond the capacity of algorithmic machine learning because there is a mismatch between how humans and machines know what they know.” —Sue Halpern, New York Review of Books
Author: P. Buitelaar
Publisher: IOS Press
ISBN: 1607502968
Category : Computers
Languages : en
Pages : 292
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Book Description
The promise of the Semantic Web is that future web pages will be annotated not only with bright colors and fancy fonts as they are now, but with annotation extracted from large domain ontologies that specify, to a computer in a way that it can exploit, what information is contained on the given web page. The presence of this information will allow software agents to examine pages and to make decisions about content as humans are able to do now. The classic method of building an ontology is to gather a committee of experts in the domain to be modeled by the ontology, and to have this committee agree on which concepts cover the domain, on which terms describe which concepts, on what relations exist between each concept and what the possible attributes of each concept are. All ontology learning systems begin with an ontology structure, which may just be an empty logical structure, and a collection of texts in the domain to be modeled. An ontology learning system can be seen as an interplay between three things: an existing ontology, a collection of texts, and lexical syntactic patterns. The Semantic Web will only be a reality if we can create structured, unambiguous ontologies that model domain knowledge that computers can handle. The creation of vast arrays of such ontologies, to be used to mark-up web pages for the Semantic Web, can only be accomplished by computer tools that can extract and build large parts of these ontologies automatically. This book provides the state-of-art of many automatic extraction and modeling techniques for ontology building. The maturation of these techniques will lead to the creation of the Semantic Web.
