Bridging Human Intelligence and Artificial Intelligence

2022-02-24

PDF Bridging Human Intelligence and Artificial Intelligence Download

Author: Mark V. Albert
Publisher: Springer Nature
ISBN: 3030847292
Category : Education
Languages : en
Pages : 364

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.

From Code to Consciousness

2024-01-24

PDF From Code to Consciousness Download

Author: Rume Dominic
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 0

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.

Human-Centered AI

2022

PDF Human-Centered AI Download

Author: Ben Shneiderman
Publisher: Oxford University Press
ISBN: 0192845292
Category : Computers
Languages : en
Pages : 390

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.

An Introduction to Artificial Intelligence in Education

2021-11-29

PDF An Introduction to Artificial Intelligence in Education Download

Author: Shengquan Yu
Publisher: Springer Nature
ISBN: 9811627703
Category : Education
Languages : en
Pages : 205

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.

Advances in Artificial and Human Intelligence in the Modern Era

2023-09-11

PDF Advances in Artificial and Human Intelligence in the Modern Era Download

Author: Rajest, S. Suman
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 433

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.

Humanizing AI

2023-03-28

PDF Humanizing AI Download

Author: Ann E Williams
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 0

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.

Human and Machine Learning

2018-06-07

PDF Human and Machine Learning Download

Author: Jianlong Zhou
Publisher: Springer
ISBN: 3319904035
Category : Computers
Languages : en
Pages : 482

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of “black-box” in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications. This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making. This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially benefit researchers in areas like artificial intelligence, decision support systems and human-computer interaction.

The Self-Assembling Brain

2022-12-13

PDF The Self-Assembling Brain Download

Author: Peter Robin Hiesinger
Publisher: Princeton University Press
ISBN: 0691241694
Category : Computers
Languages : en
Pages : 384

"In this book, Peter Robin Hiesinger explores historical and contemporary attempts to understand the information needed to make biological and artificial neural networks. Developmental neurobiologists and computer scientists with an interest in artificial intelligence - driven by the promise and resources of biomedical research on the one hand, and by the promise and advances of computer technology on the other - are trying to understand the fundamental principles that guide the generation of an intelligent system. Yet, though researchers in these disciplines share a common interest, their perspectives and approaches are often quite different. The book makes the case that "the information problem" underlies both fields, driving the questions that are driving forward the frontiers, and aims to encourage cross-disciplinary communication and understanding, to help both fields make progress. The questions that challenge researchers in these fields include the following. How does genetic information unfold during the years-long process of human brain development, and can this be a short-cut to create human-level artificial intelligence? Is the biological brain just messy hardware that can be improved upon by running learning algorithms in computers? Can artificial intelligence bypass evolutionary programming of "grown" networks? These questions are tightly linked, and answering them requires an understanding of how information unfolds algorithmically to generate functional neural networks. Via a series of closely linked "discussions" (fictional dialogues between researchers in different disciplines) and pedagogical "seminars," the author explores the different challenges facing researchers working on neural networks, their different perspectives and approaches, as well as the common ground and understanding to be found amongst those sharing an interest in the development of biological brains and artificial intelligent systems"--

2062

2018-07-30

PDF 2062 Download

Author: Toby Walsh
Publisher: Black Inc.
ISBN: 1743820259
Category : Technology & Engineering
Languages : en
Pages : 336

‘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

The Myth of Artificial Intelligence

2021-04-06

PDF The Myth of Artificial Intelligence Download

Author: Erik J. Larson
Publisher: Harvard University Press
ISBN: 0674259920
Category : Computers
Languages : en
Pages : 321

“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