The emerging widespread use of artificial intelligence in education.

A public policy leader addresses how artificial intelligence is transforming the future of labor—and what we can do to protect the role of workers. As computer technology advances with dizzying speed, human workers face an ever-increasing threat of obsolescence. In Human Work In the Age of Smart Machines, Jamie Merisotis argues that we can—and must—rise to this challenge by preparing to work alongside smart machines doing that which only humans can: thinking critically, reasoning ethically, interacting interpersonally, and serving others with empathy. The president and CEO of Lumina Foundation, Merisotis offers a roadmap for the large-scale, radical changes we must make in order to find abundant and meaningful work for ourselves in the 21st century. His vision centers on developing our unique capabilities as humans through learning opportunities that deliver fair results and offer a broad range of credentials. By challenging long-held assumptions and expanding our concept of work, Merisotis argues that we can harness the population’s potential, encourage a deeper sense of community, and erase a centuries-long system of inequality.

A fresh look at a “robot-proof” education in the new age of generative AI. In 2017, Robot-Proof, the first edition, foresaw the advent of the AI economy and called for a new model of higher education designed to help human beings flourish alongside smart machines. That economy has arrived. Creative tasks that, seven years ago, seemed resistant to automation can now be performed with a simple prompt. As a result, we must now learn not only to be conversant with these technologies, but also to comprehend and deploy their outputs. In this revised and updated edition, Joseph Aoun rethinks the university’s mission for a world transformed by AI, advocating for the lifelong endeavor of a “robot-proof” education. Aoun puts forth a framework for a new curriculum, humanics, which integrates technological, data, and human literacies in an experiential setting, and he renews the call for universities to embrace lifelong learning through a social compact with government, employers, and learners themselves. Drawing on the latest developments and debates around generative AI, Robot-Proof is a blueprint for the university as a force for human reinvention in an era of technological change—an era in which we must constantly renegotiate the shifting boundaries between artificial intelligence and the capacities that remain uniquely human.

A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+

This book examines, from a comparative perspective, the impact of the movement from the so-called knowledge-based economy towards the Intelligent Economy, which is premised upon the application of knowledge. This volume links the advent of this new technological revolution to the world of governance and policy formulation in education.

Title: Intelligent Machines in the Classroom: Unlocking the Potential of AI in K12 Education Author: Adam Smith In "Intelligent Machines in the Classroom: Unlocking the Potential of AI in K12 Education," renowned author and education technology expert Adam Smith explores the transformative potential of artificial intelligence in the realm of K12 education. This insightful book serves as a comprehensive guide for educators, administrators, policymakers, and parents interested in understanding and leveraging the power of AI to enhance learning outcomes. Smith delves into the intricacies of AI, demystifying complex concepts with his lucid writing style. He provides a balanced perspective on the benefits and challenges of integrating AI into the classroom, drawing on real-world examples and case studies from schools that have successfully adopted AI technologies. The book covers a wide range of topics, including personalized learning, data-driven instruction, intelligent tutoring systems, and the ethical considerations of AI in education. Smith also discusses the role of teachers in an AI-driven educational landscape and provides practical strategies for effectively blending human instruction with machine learning. "Intelligent Machines in the Classroom" is not just a theoretical exploration of AI in education. It is a practical roadmap for the future, offering actionable insights and recommendations for harnessing the power of AI to create more engaging, personalized, and effective learning experiences. This book is a must-read for anyone interested in the future of education and the role that technology will play in shaping it

The A.I. Revolution is here and many schools are scrambling with how to respond. The truth is nobody knows exactly how machine learning will change teaching and learning. Moving forward, educators will need to be adaptable in the face of these changes. But more importantly, our students will need to navigate a world where to corporate ladder is now a maze. They'll need to develop deeply human skills in a world of smart machines.This book does not offer a blueprint with specific directions for how to use generative AI. It doesn't offer a step-by-step instruction manual for how educators will need to re-imagine learning. But what it does offer is a roadmap for how we can navigate the changing terrain. We explore how AI works and how we can avoid the two dead-ends of the Lock It and Block It and the Techno-Futurism routes. In this roadmap, we offer a third way that is human-centered and tech-infused. We examine how AI is transforming creative thinking, information literacy, project-based learning, assessment, and personalized learning and how we might keep a human-centered focus as we navigate these changes. Finally, we analyze how AI is changing each subject area and how we can respond in a way that helps us leverage AI while maintaining our humanity.