Artificial Intelligence (AI) Resources

Designed as a self-teaching introduction to the fundamental concepts of artificial intelligence, the book begins with its history, the Turing test, and early applications. Later chapters cover the basics of searching, game playing, and knowledge representation. Expert systems and machine learning are covered in detail, followed by separate programming chapters on Prolog and Python. The concluding chapter on artificial intelligence machines and robotics is comprehensive with numerous modern applications.

You will learn how AI is being utilised today and how it is likely to be used in the future to balance the talents of humans and machines. You will explore robotics and machine learning within the context of AI, and discover how the challenges AI presents are being addressed.

he book highlights the broad field of artificial intelligence applications in education, regarding any type of artificial intelligence that is correlated with education. It discusses learning methodologies, intelligent tutoring systems, intelligent student guidance and assessments, intelligent education chatbots, and artificial tutors and presents the practicality and applicability implications of AI in education. The book offers new and current research along with case studies showing the latest techniques and educational activities.

Bringing together expert perspectives from around the world, this exciting, informative collection of research and analysis helps educators, policymakers and analysts navigate the future of work and learning amid rapid and accelerating technological change.

Structured in three parts, the book starts developing the creative engagement perspective for learning and teaching to then present practical applications of AI in K-12 and higher education, covering different fields (teacher education, professional education, business education) as well as different types of AI supported tools (games, chatbots, and AI assisted assessment). It also delves into the ethical considerations, policy implications, and the central role educators play in harnessing the power of an AI informed educational experience.

This book is authored by a range of international experts with a diversity of backgrounds and perspectives hopefully bringing us closer to the responses for the questions what we should teach (what the ‘right'set of future skills is), how we should teach (the way in which schools should teach and assess them) and where we should teach (what implications does AI have for today's education infrastructure).

The themes are around artificial intelligence technology and applications; intelligent and knowledge-based systems; information-based education; intelligent learning; advanced information theory and neural network technology ; software computing and algorithms; intelligent algorithms and computing and many other topics.

rom interactive learning techniques to advanced assignment and assessment strategies, this comprehensive guide offers practical suggestions for integrating AI effectively into teaching and learning environments. Bowen and Watson tackle crucial questions related to academic integrity, cheating, and other emerging issues.In the age of AI, critical thinking skills, information literacy, and a liberal arts education are more important than ever. As AI continues to reshape the nature of work and human thinking, educators can equip students with the skills they need to thrive in a rapidly evolving world. This book serves as a compass, guiding educators through the uncharted territory of AI-powered education and the future of teaching and learning.

The authors share relevant best practices and use cases for teaching, develop answers to ongoing organizational challenges, and reflect on the practical implications of different theoretical approaches to AI ethics. The book is of great interest to faculty members, researchers, and students in the fields of artificial intelligence, computer science, mathematics, computer engineering, and related areas, as well as higher education administration.

This book explores the complex topic of AI ethics in a cross-functional way, alternating between theory and practice. Practical and recent events, and their associated challenges, are presented, such as the collateral effects of the COVID-19 pandemic on the application of AI technologies. The book also gives an up-to-date overview of the potential positive and negative outcomes of AI implementations together with an analysis of AI from an ethical perspective.

Case studies are one of the best ways to learn about ethical dilemmas and to achieve insights into various complexities and stakeholder perspectives. Given the omnipresence of AI ethics in academic, policy and media debates, the book will be suitable for a wide range of audiences, from scholars of different disciplines (e.g. AI science, ethics, politics, philosophy, economics) to policy-makers, lobbying NGOs, teachers and the educated public.

As algorithmic data processing increasingly pervades everyday life, it is also making its way into the worlds of art, literature and music. In doing so, it shifts notions of creativity and evokes non-anthropocentric perspectives on artistic practice. This volume brings together contributions from the fields of cultural studies, literary studies, musicology and sound studies as well as media studies, sociology of technology, and beyond, presenting a truly interdisciplinary, state-of-the-art picture of the transformation of creative practice brought about by various forms of AI.

In Co-Intelligence, Mollick urges us to engage with AI as co-worker, co-teacher, and coach. He assesses its profound impact on business and education, using dozens of real-time examples of AI in action. Co-Intelligence shows what it means to think and work together with smart machines, and why it's imperative that we master that skill. Mollick challenges us to utilize AI's enormous power without losing our identity, to learn from it without being misled, and to harness its gifts to create a better human future. Wide ranging, hugely thought-provoking, optimistic, and lucid, Co-Intelligence reveals the promise and power of this new era.

Human-AI Teaming: State-of-the-Art and Research Needs examines the factors that are relevant to the design and implementation of AI systems with respect to human operations. This report provides an overview of the state of research on human-AI teaming to determine gaps and future research priorities and explores critical human-systems integration issues for achieving optimal performance.

Who is designing AI? A select, narrow group. How is their world view shaping our future? Artificial intelligence can be all too human: quick to judge, capable of error, vulnerable to bias. It's made by humans, after all. Humans make decisions about the laws and standards, the tools, the ethics in this new world. Who benefits. Who gets hurt. Made by Humans explores our role and responsibilities in automation. Roaming from Australia to the UK and the US, elite data expert Ellen Broad talks to world leaders in AI about what we need to do next. It is a personal, thought-provoking examination of humans as data and humans as the designers of systems that are meant to help us.

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.

he Adoption and Effect of Artificial Intelligence on Human Resources Management Series sets out a blended approach towards different functions of HRM and AI, reflecting upon: HR data privacy; data security; diversity and inclusion using AI; and sustainable AI-HR practices. This book is ideal for HR managers, senior managers, researchers, and students planning a career in this field.

Increased use of artificial intelligence (AI) is being deployed in many hospitals and healthcare settings to help improve health care service delivery. Machine learning (ML) and deep learning (DL) tools can help guide physicians with tasks such as diagnosis and detection of diseases and assisting with medical decision making.

Today, many Americans are concerned about the impact that artificial intelligence and machine learning will have on jobs. This book examines the impact of these factors on the workforce, including issues related to worker displacement, retraining of the current workforce, and developing a skilled technical workforce of the future that can thrive in an economy in which AI increasingly plays a role.

By the end of this book, you'll have learned how machine learning works and have a solid understanding of the recent business applications of AI.

From a manufacturing applications perspective, the book illustrates the deployment of these AI paradigms in a variety of use cases spanning production planning, quality control, anomaly detection, metrology, workers' training, supply chain management, as well as various production optimization scenarios.

The authors describe industrial AI's challenges, the approaches adopted, and the main industrial systems and applications to give the reader extensive insight into the technical nature of this field. The chapters provide insightful material on industrial AI technologies and applications.This book is a valuable resource for researchers, post-graduate students, practitioners, and technoloyg developers interested in gaining insight into industrial edge AI, the IIoT, embedded machine and deep learning, new technologies, and solutions to advance intelligent processing at the edge.