What is the role of educators with the rise of the artificial intelligence era? We are entering an unprecedented era of innovation, where humanity and technology will work together in harmony. This collaboration allows for technology to handle mundane tasks while educators are empowered to use their unique skill set toward more creative endeavors. Educators have an opportunity to leverage artificial intelligence in order to provide students with a future-focused education that's tailored specifically to their needs. By embracing this change, educators will be able to focus more of their time on building meaningful relationships and doing what they truly love - teaching!The AI Classroom will help you:Create content and do tasks using artificial intelligenceInfuse emotional intelligence with artificial intelligenceEnhance existing pedagogies Put students in control of their learning

This open Access book constitutes the refereed proceedings of the First International Workshop on AI in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. The 12 papers presented here were carefully reviewed and selected for these open access proceedings. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.

A critique of what lies behind the use of data in contemporary education policy    While the science fiction tales of artificial intelligence eclipsing humanity are still very much fantasies, in Algorithms of Education the authors tell real stories of how algorithms and machines are transforming education governance, providing a fascinating discussion and critique of data and its role in education policy. Algorithms of Education explores how, for policy makers, today's ever-growing amount of data creates the illusion of greater control over the educational futures of students and the work of school leaders and teachers. In fact, the increased datafication of education, the authors argue, offers less and less control, as algorithms and artificial intelligence further abstract the educational experience and distance policy makers from teaching and learning. Focusing on the changing conditions for education policy and governance, Algorithms of Education proposes that schools and governments are increasingly turning to "synthetic governance"--a governance where what is human and machine becomes less clear--as a strategy for optimizing education. Exploring case studies of data infrastructures, facial recognition, and the growing use of data science in education, Algorithms of Education draws on a wide variety of fields--from critical theory and media studies to science and technology studies and education policy studies--mapping the political and methodological directions for engaging with datafication and artificial intelligence in education governance. According to the authors, we must go beyond the debates that separate humans and machines in order to develop new strategies for, and a new politics of, education.

The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased. Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers' engagement in testing. In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices.

Artificial Intelligence-Based System Models in Healthcare provides a comprehensive and insightful guide to the transformative applications of AI in the healthcare system. This book is a groundbreaking exploration of the synergies between artificial intelligence and healthcare innovation. In an era where technological advancements are reshaping the landscape of medical practices, this book provides a comprehensive and insightful guide to the transformative applications of AI in healthcare systems. From conceptual foundations to practical implementations, the book serves as a roadmap for understanding the intricate relationships between AI-based system models and the evolution of healthcare delivery. The first section delves into the fundamental role of technology in reshaping the healthcare landscape. With a focus on daily life activities, decision support systems, vision-based management, and semantic frameworks, this section lays the groundwork for understanding the pivotal role of AI in revolutionizing traditional healthcare approaches. Each chapter offers a unique perspective, emphasizing the intricate integration of technology into healthcare ecosystems. The second section takes a deep dive into specific applications of AI, ranging from predictive analysis and machine learning to deep learning, image analysis, and biomedical text processing. With a focus on decision-making support systems, this section aims to demystify the complex world of AI algorithms in healthcare, offering valuable insights into their practical implications and potential impact on patient outcomes. The final section addresses the modernization of healthcare practices and envisions the future landscape of AI applications. From medical imaging and diagnostics to predicting ventilation needs in intensive care units, modernizing health record maintenance, natural language processing, chatbots for medical inquiries, secured health insurance management, and glimpses into the future, the book concludes by exploring the frontiers of AI-driven healthcare innovations. Audience This book is intended for researchers and postgraduate students in artificial intelligence and the biomedical and healthcare sectors. Medical administrators, policymakers and regulatory specialists will also have an interest.

Artificial Intelligence and Evaluation: Emerging Technologies and Their Implications for Evaluation is a groundbreaking exploration of how the landscape of program evaluation will be redefined by artificial intelligence and other emerging digital technologies. In an era where digital technologies and artificial intelligence (AI) are rapidly evolving, this book presents a pivotal resource for evaluators navigating the transformative intersection of their practice and cutting-edge technology. Addressing the dual dimensions of how evaluations are conducted and what is evaluated, a roster of distinguished contributors illuminate the impact of AI on program evaluation methodologies. Offering a discerning overview of various digital technologies, their promises and perils, they carefully dissect the implications for evaluative processes and debate how evaluators must be equipped with the requisite skills to harness the full potential of AI tools. Further, the book includes a number of compelling use cases, demonstrating the tangible applications of AI in diverse evaluation scenarios. The use cases range from the application of GIS data to advanced text analytics. As such, this book provides evaluators with inspirational cases on how to apply AI in their practice as well as what pitfalls one must look out for. Artificial Intelligence and Evaluation is an indispensable guide for evaluators seeking to not only adapt to but thrive in the dynamic landscape of evaluation practices reshaped by the advent of artificial intelligence. The Open Access version of this book, available at http: //www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

No detailed description available for "Artificial Intelligence and Knowledge Processing: Methods and Applications".

Artificial Intelligence of Things (AIoT): Current and Future Trends brings together researchers and developers from a wide range of domains to share ideas on how to implement technical advances, create application areas for intelligent systems, and how to develop new services and smart devices connected to the Internet. Section One covers AIoT in Everything, providing a wide range of applications for AIoT methods and technologies. Section Two gives readers comprehensive guidance on AIoT in Societal Research and Development, with practical case studies of how AIoT is impacting cultures around the world. Section Three covers the impact of AIoT in educational settings. The book also covers new capabilities such as pervasive sensing, multimedia sensing, machine learning, deep learning, and computing power. These new areas come with various requirements in terms of reliability, quality of service, and energy efficiency.

This open access book constitutes revised selected papers from the First International Conference on Bridging the Gap between AI and Reality, AISoLA 2023, which took place in Crete, Greece, in October 2023.  The papers included in this book focus on the following topics: The nature of AI-based systems; ethical, economic and legal implications of AI-systems in practice; ways to make controlled use of AI via the various kinds of formal methods-based validation techniques; dedicated applications scenarios which may allow certain levels of assistance; and education in times of deep learning.   

This informative Handbook provides a comprehensive overview of the legal, ethical, and policy implications of AI and algorithmic systems. As these technologies continue to impact various aspects of our lives, it is crucial to understand and assess the challenges and opportunities they present. Drawing on contributions from experts in various disciplines, the book covers theoretical insights and practical examples of how AI systems are used in society today. It also explores the legal and policy instruments governing AI, with a focus on Europe. The interdisciplinary approach of this book makes it an invaluable resource for anyone seeking to gain a deeper understanding of AI's impact on society and how it should be regulated. This title is also available as Open Access on Cambridge Core.

Ever since the large language model-based AI chatbot ChatGPT launched in 2022, there has been a significant amount of buzz and concern around the possibility of this technology impacting writing as both a creative and professional pursuit. Proponents of the use of ChatGPT and similar AI argue that it can be useful in helping people improve their writing and be more productive, while opponents fear that it could make writing less creative, discourage people from learning to effectively communicate themselves, and even result in the loss of jobs that involve writing. This volume considers viewpoints on both sides of this debate to explore the role of ChatGPT and other AI today and in the years to come.

'Industry 5.0' was first described in 2020 by the European Commission to describe the next wave of technologies, including Virtual Simulation and Automated Robots, to impact businesses and individuals. It recognizes how these technologies can no more be counted as purely 'future tech', but as realities that will begin to impact society as a whole. This open access book describes this new world as 'Society 5.0' and explores the real impact of AI-enabled business on society. Beginning with a brief history of AI, the current terms, and its conceptual components, visualisation, data, and algorithms, this book then presents a collection of studies from leading scholars in the field of AI and Digital Business. The first section focuses on the immediate challenges and strategic changes that will be required for businesses to successfully adapt to this new reality. The second focuses on the opportunities of AI to businesses and society. And the final section includes chapters on the future and the possibilities and challenges that lie beyond Industry 5.0. It will be of great interest to scholars and students of innovation strategy and digital business, as well as all those engaged in research around cutting-edge technologies and their impact on society.

The educational landscape is changing rapidly due to the digital transformation. The contributors to this volume - teachers, researchers, and graduate students - help to navigate the dynamic domain of digital feedback, adopting a multifaceted approach to innovative and interactive feedback practices in higher education. Emphasizing learner engagement, they discuss changes in teachers' roles as well as curriculum design, and place a special focus on the utilization of social media and artificial intelligence for feedback purposes. Altogether, this comprehensive, critical, creative, and collaborative exploration underscores the necessity of a continuous development and dialogue about digital feedback literacy.

A straightforward and accessible explainer of new and upcoming technologies for business leaders In Digitally Curious: Your guide to navigating the future of AI and all things tech, futurist, speaker, and technology trends expert Andrew Grill delivers an easy-to-follow and incisive discussion of current and future technologies, as well as how leading companies are deploying them. The author examines critical business concepts, like the future of work, from a technical and human-centric point of view and how Artificial Intelligence will impact us at work and in society. He includes a broad range of relevant technologies and platforms, offering examples that will be immediately relevant to any industry and business. Digitally Curious offers recent and relevant examples via accessible and revealing interviews with global business leaders from various fields. The book also provides: Actionable insights and end-of-chapter takeaways, with links to further information and additional resources Complimentary access to a companion website created and updated by the author, a 30-year veteran of technology and business Immediately applicable steps you can implement right away to create positive change in your business Digitally Curious is perfect for managers, executives, board members, and other business leaders. It is the ideal resource for anyone looking for a simple and straightforward explanation of how new and upcoming tech and digital trends will impact you at work and in broader society.

In this book, expert lawyers from across the full spectrum of EU law explore the impact of the digital age on the Union's legal framework. The fifth industrial revolution is impacting on all aspects of society. This open access collection looks at how the European Union and its legal framework is reacting, responding, and evolving to best accommodate the reality of this new environment. Drawn from the insightful and thought-provoking views of acknowledged experts in the field, it examines the questions from all aspects of EU law. This is a thoughtful and timely collection on a question that will continue to dominate EU law in the coming years. The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com. Open access was funded by the Swedish Studies Network.

No detailed description available for "Future Farming: Advancing Agriculture with Artificial Intelligence".

HUMAN-MACHINE INTERFACE The book contains the latest advances in healthcare and presents them in the frame of the Human-Machine Interface (HMI). The Human-Machine Interface (HMI) industry has witnessed the evolution from a simple push button to a modern touch-screen display. HMI is a user interface that allows humans to operate controllers for machines, systems, or instruments. Most medical procedures are improved by HMI systems, from calling an ambulance to ensuring that a patient receives adequate treatment on time. This book describes the scenario of biomedical technologies in the context of the advanced HMI, with a focus on direct brain-computer connection. The book describes several HMI tools and related techniques for analyzing, creating, controlling, and upgrading healthcare delivery systems, and provides details regarding how advancements in technology, particularly HMI, ensure ethical and fair use in patient care. Audience The target audience for this book is medical personnel and policymakers in healthcare and pharmaceutical professionals, as well as engineers and researchers in computer science and artificial intelligence.

Discover how to navigate the intersection of tech, cybersecurity, and commerce In an era where technological innovation evolves at an exponential rate, Inside Cyber: How AI, 5G, and Quantum Computing Will Transform Privacy and Our Security by Chuck Brooks emerges as a critical roadmap for understanding and leveraging the next wave of tech advancements. Brooks, a renowned executive and consultant, breaks down complex technological trends into digestible insights, offering a deep dive into how emerging technologies will shape the future of industry and society. In the book, you'll: Gain clear, accessible explanations of cutting-edge technologies such as AI, blockchain, and quantum computing, and their impact on the business world Learn how to navigate the cybersecurity landscape, safeguarding your business against the vulnerabilities introduced by rapid technological progress Uncover the opportunities that technological advancements present for disrupting traditional industries and creating new value Perfect for entrepreneurs, executives, technology professionals, and anyone interested in the intersection of tech and business, Inside Cyber equips you with the knowledge to lead in the digital age. Embrace the future confidently with this indispensable guide.

Since new types of artificial intelligence like ChatGPT and other large language models have been introduced, many people have expressed excitement and concern about their generative potential. Could AI be used to write a book, make a movie, or create a picture that's just as good as--or maybe even better than--those created by humans? But with these questions come other legal and ethical questions. Data is used to "train" ChatGPT and other forms of AI, but where is this data coming from, and does using it violate the rights of human creators? Furthermore, when the work AI produces strongly resembles or even directly mimics the work of human creators, what intellectual property rights do the creators have? This volume examines these questions and others related to the murky intersection of AI and intellectual property, including whether the use of AI on school assignments is considered plagiarism.

This book presents insights into how Intelligent Computing and Optimization techniques can be used to attain the goals of Sustainable Development. It provides a comprehensive overview of the latest breakthroughs and recent developments in sustainable, intelligent computing technologies, applications, and optimization techniques across various industries, including business process management, manufacturing, financial sector, agriculture, financial sector, supply chain management, and healthcare. It focuses on computational intelligent techniques and optimization techniques to provide sustainable solutions to many problems. Features: - Provides insights into the theory, implementation, and application of computational intelligence techniques in many industries. - Includes industry practitioner perspectives and case studies for a better understanding of sustainable solutions. - Highlights the role of intelligent computing and optimization as key technologies in decision-making processes and in providing cutting-edge solutions to real-world problems. - Addresses the challenges and limitations of computational approaches in sustainability, such as data availability, model uncertainty, and computational complexity, while also discusses emerging opportunities and future directions in the field. This book will be useful for professionals and scholars looking for up-to-date research on cutting-edge perspectives in the field of computational intelligent and optimization techniques in the areas of agriculture, industry, financial sector, business automation, renewable energy, optimization, and smart cities.

Forward-thinking reference on spectrum sharing and resource management for 5G, B5G, and 6G wireless networks Intelligent Spectrum Management: Towards 6G explores various aspects of spectrum sharing and resource management in 5G, beyond 5G, and the envisaged 6G networks. The book offers an in-depth exploration of intelligent and secure sharing of spectrum and resource management in existing and future mobile networks. The book sets the stage by providing an insight to the evolution of mobile networks and highlights the importance of spectrum sharing and resource management in next-generation wireless networks. At the core, the book explores various promising technologies such as cognitive radio, reinforcement learning, deep learning, reconfigurable intelligent surfaces, and blockchain technology towards efficient, intelligent, and secure sharing of spectrum and resource management. Moreover, the book presents dynamic and decentralized resource management techniques, including network slicing, game theory, and blockchain-enabled approaches. Topics covered include: Spectrum, and why it must be utilized optimally and transparently Future applications envisioned with 6G, such as digital twins, Industry 5.0, holographic telepresence, and Extended Reality (XR) Challenges when Dynamic Spectrum Management (DSM) is enabled through Machine Learning (ML) techniques, including the complexity of received signals and the difficulty in obtaining accurate network data such as channel state information Reinforcement learning and deep learning-assisted spectrum management Synergy between Artificial Intelligence (AI) and blockchain technology for spectrum management Private networks, including their prospects, architecture, enabling concepts, and techniques for efficient operation In essence, various innovative technologies and approaches that can be leveraged to enhance spectrum utilization and efficiently manage network resources are discussed. The book is a potential reference for researchers, academics, and professionals in the wireless service provider industry, as well as regulators and officials.

This book provides in-depth explanations and discussions of the latest applications of Artificial Intelligence (AI), machine learning, and the Internet of Medicine, offering readers the cutting edge on this rapidly growing technology that has the potential to transform healthcare and improve patient outcomes. Over the past five years, there have been significant advances in healthcare through the use of artificial intelligence (AI) and machine learning (ML) technologies. AI and machine learning in medical imaging has significantly improved the accuracy and speed of medical imaging analysis, accelerated the drug discovery process by identifying potential drug targets and predicting the efficacy and safety of new drugs, and enabled personalized medicine by analyzing large amounts of patient data to identify individualized treatment plans based on a patient's genetic makeup and medical history. Internet of Medicine (IoM) refers to the integration of the Internet of Things (IoT) and connected medical devices with healthcare systems and processes to enable remote monitoring, diagnosis, and treatment of patients. IoM is a subset of the larger Internet of Things concept, which involves the connection of everyday devices and appliances to the internet for various purposes. IoM has the potential to revolutionize healthcare by improving patient outcomes, reducing costs, and increasing efficiency. Some of the specific applications of IoM include remote patient monitoring, real-time data analysis, predictive analytics, smart hospitals, and personalized medicine.

Learn to leverage Microsoft's new AI tool, Copilot, for enhanced productivity at work In Microsoft 365 Copilot At Work: Using AI to Get the Most from Your Business Data and Favorite Apps, a team of software and AI experts delivers a comprehensive guide to unlocking the full potential of Microsoft's groundbreaking AI tool, Copilot. Written for people new to AI, as well as experienced users, this book provides a hands-on roadmap for integrating Copilot into your daily workflow. You'll find the knowledge and strategies you need to maximize your team's productivity and drive success. The authors offer you a unique opportunity to gain a deep understanding of AI fundamentals, including machine learning, large language models, and generative AI versus summative AI. You'll also discover: How Copilot utilizes AI technologies to provide real-time intelligent assistance and revolutionize the way you work with Microsoft 365 apps Practical Implementation Strategies for project and change management, as well as practical guidance on rolling out Copilot within your organization Specific use cases, including Outlook, Teams, Excel, PowerPoint, and OneNote, and how Copilot can streamline tasks and boost efficiency across various Microsoft applications Take your Copilot proficiency to the next level with advanced AI concepts, usage monitoring, and custom development techniques. Delve into Microsoft Framework Accelerator, Copilot plugins, semantic kernels, and custom plugin development, empowering you to tailor Copilot to your organization's unique needs and workflows. Get ready to revolutionize your productivity with Microsoft 365 Copilot!

The Routledge Handbook of Artificial Intelligence and Philanthropy acts as a catalyst for the dialogue between two ecosystems with much to gain from collaboration: artificial intelligence (AI) and philanthropy. Bringing together leading academics, AI specialists, and philanthropy professionals, it offers a robust academic foundation for studying both how AI can be used and implemented within philanthropy and how philanthropy can guide the future development of AI in a responsible way. The contributors to this Handbook explore various facets of the AI-philanthropy dynamic, critically assess hurdles to increased AI adoption and integration in philanthropy, map the application of AI within the philanthropic sector, evaluate how philanthropy can and should promote an AI that is ethical, inclusive, and responsible, and identify the landscape of risk strategies for their limitations and/or potential mitigation. These theoretical perspectives are complemented by several case studies that offer a pragmatic perspective on diverse, successful, and effective AI-philanthropy synergies. As a result, this Handbook stands as a valuable academic reference capable of enriching the interactions of AI and philanthropy, uniting the perspectives of scholars and practitioners, thus building bridges between research and implementation, and setting the foundations for future research endeavors on this topic. The Open Access version of this book, available at http: //www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.

How AI is revolutionizing the future of learning and how educators can adapt to this new era of human thinking. Artificial Intelligence (AI) is revolutionizing the way we learn, work, and think. Its integration into classrooms and workplaces is already underway, impacting and challenging ideas about creativity, authorship, and education. In this groundbreaking and practical guide, teachers will discover how to harness and manage AI as a powerful teaching tool. José Antonio Bowen and C. Edward Watson present emerging and powerful research on the seismic changes AI is already creating in schools and the workplace, providing invaluable insights into what AI can accomplish in the classroom and beyond. By learning how to use new AI tools and resources, educators will gain the confidence to navigate the challenges and seize the opportunities presented by AI. From 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.

Understanding Artificial Intelligence Provides students across majors with a clear and accessible overview of new artificial intelligence technologies and applications Artificial intelligence (AI) is broadly defined as computers programmed to simulate the cognitive functions of the human mind. In combination with the Neural Network (NN), Big Data (BD), and the Internet of Things (IoT), artificial intelligence has transformed everyday life: self-driving cars, delivery drones, digital assistants, facial recognition devices, autonomous vacuum cleaners, and mobile navigation apps all rely on AI to perform tasks. With the rise of artificial intelligence, the job market of the near future will be radically different???many jobs will disappear, yet new jobs and opportunities will emerge. Understanding Artificial Intelligence: Fundamentals and Applications covers the fundamental concepts and key technologies of AI while exploring its impact on the future of work. Requiring no previous background in artificial intelligence, this easy-to-understand textbook addresses AI challenges in healthcare, finance, retail, manufacturing, agriculture, government, and smart city development. Each chapter includes simple computer laboratories to teach students how to develop artificial intelligence applications and integrate software and hardware for robotic development. In addition, this text: Focuses on artificial intelligence applications in different industries and sectors Traces the history of neural networks and explains popular neural network architectures Covers AI technologies, such as Machine Vision (MV), Natural Language Processing (NLP), and Unmanned Aerial Vehicles (UAV) Describes various artificial intelligence computational platforms, including Google Tensor Processing Unit (TPU) and Kneron Neural Processing Unit (NPU) Highlights the development of new artificial intelligence hardware and architectures Understanding Artificial Intelligence: Fundamentals and Applications is an excellent textbook for undergraduates in business, humanities, the arts, science, healthcare, engineering, and many other disciplines. It is also an invaluable guide for working professionals wanting to learn about the ways AI is changing their particular field.

This open access book takes an innovative and critical look at the ways in which digital data and algorithms are changing the face of higher education in multiple ways. It examines their impact at both the macro scale of universities and systems worldwide, but also at the more subtle level of effects on academics and students. In doing so, it focuses on the day-to-day life of the university, examining how the digital is changing the way that we communicate, learn, and create new knowledge. As well as exploring the role of 'big data' and learning analytics, the book also focuses on areas of academic life not normally considered to be part of datafication, such as the physical structures of surveillance on campus and the ways in which systems of 'quality' in research can morph into regimes of surveillance and algorithmic discipline. Taking an interdisciplinary perspective, the volume interweaves insights from Surveillance Studies, Science and Technology Studies and Postphenomenology. . Its wide-ranging analysis generates fresh, critical new insights into the nature of communication, semiosis, textual practices, subjectivities and knowledge practices at this dynamic and fast-moving juncture in the history and development of higher education worldwide. The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com. Open access was funded by University College London, UK.

This open access book addresses the thriving trend of embedding artificial intelligence (AI) and machine learning (ML) capabilities in products and services reaching the lay public, focusing on the user experience (UX) they prompt from a designerly perspective. It offers a UX evaluation method designed explicitly for AI-infused systems to answer one of the core problems affecting the relationship and interactions people have with such artefacts. The work investigates how people perceive and make sense of systems integrating AI capabilities, trying to understand how their meaning and significance can affect the experience of such products and what design challenges may arise. Given the fundamental premise that current UX methods cannot address AI-infused artefacts, it introduces the results of Meet-AI, a research project exploring specific ways to tackle these problems. The book then presents a comprehensive analysis of current UX methods, and a literature review focused on detecting possible gaps and the most suitable qualities to describe AI-infused systems, and summarizes the findings from all previous investigations into a UX evaluation scale: AIXE (AI user eXperience Evaluation). The book also portrays how the tool has been validated and expanded to become a more comprehensive method. It further describes how the scale has been applied to a comparative study of domestic smart speakers, and introduces a reversed interpretation of the outcomes, framing them as heuristics to inform the early phases of the design process and paving the way for future experimentations in the meta-design dimension.