ChatGPT & Artificial Intelligence

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 modernapplications. Features: Covers an introduction to concepts related to AI, including searching processes, knowledge representation, machine learning, expert systems, programming, and robotics Includes separate chapters on Prolog and Python to introduce basic programming techniques in AI

The importance of Artificial Intelligence cannot be over-emphasised in current times, where automation is already an integral part of industrial and business processes. A First Course in Artificial Intelligence is a comprehensive textbook for beginners which covers all the fundamentals of Artificial Intelligence. Seven chapters (divided into thirty-three units) introduce the student to key concepts of the discipline in simple language, including expert system, natural language processing, machine learning, machine learning applications, sensory perceptions (computer vision, tactile perception) and robotics. Each chapter provides information in separate units about relevant history, applications, algorithm and programming with relevant case studies and examples. The simplified approach to the subject enables beginners in computer science who have a basic knowledge of Java programming to easily understand the contents. The text also introduces Python programming language basics, with demonstrations of natural language processing. It also introduces readers to the Waikato Environment for Knowledge Analysis (WEKA), as a tool for machine learning. The book is suitable for students and teachers involved in introductory courses in undergraduate and diploma level courses which have appropriate modules on artificial intelligence.

Artificial intelligence has become an indispensible part of our lives in recent years, affecting all aspects from business and leisure to transport and health care.This book presents the proceedings of the 23rd edition of the International Conference of the Catalan Association for Artificial Intelligence (CCIA), an annual event that serves as a meeting point for researchers in Artificial Intelligence in the area of the Catalan speaking territories and from around the world. The 2021 edition was held online as a virtual conference from 20 - 22 October 2021 due to the COVID-19 pandemic. The book contains 42 long papers and 9 short papers, carefully reviewed and selected. The papers cover all aspects of artificial intelligence and are divided under six section headings: combinatorial problem solving and logics for artificial intelligence; sentiment analysis and tekst analysis; data science and decision support systems; machine learning; computer vision; and explainability and argumentation. Abstracts of the 2 invited talks delivered at the conference by Prof. Patty Kostkova and Prof. João Marques-Silva are also included. Offering a state of the art overview of the subject from a regional perspective, the book will be of interest to all those working in the field of artificial intelligence.

The rise of ChatGPT has alarmed -- and excited -- academics about the future of artificial intelligence. How should professors evaluate student writing and protect against cheating? What jobs will be lost? What efficiencies will be gained? And ChatGPT is only the beginning. This collection contains many of The Chronicle's best and latest reads on how AI is changing higher education. Read on and hang on — it’s going to be a fascinating ride.

Sir Anthony Seldon, the prominent political biographer and leading educationalist, addresses one of the high-stakes issues that will influence our future: the role of artificial intelligence and its impact on education. The use of AI promises an altogether new way of educating, offering learners from all backgrounds widespread access to personalised tuition and digital educational materials from across the world. Educational institutions across the world have been impacted by the COVID-19 pandemic and many have migrated, at least temporarily, to online platforms. The debate about how to deliver knowledge has never been more relevant. Many countries have an excellent education system with their schools and universities - excellent, but tailored to the twentieth century. The mass teaching methods of the third revolution era have failed to conquer enduring problems of inequity and lack of individualised learning. AI is disrupting the way we live, work and interact with the environment, and we cannot stop it changing our schools and universities. But we have time - albeit not for long - to shape this revolution. It will not be a panacea, and if we are not quick, it will start to replace what makes us human - being creative, having beliefs, and loving others. This book, presented in considerably updated and extended second edition, is a call to educators everywhere to open their eyes to what is coming. If we do so, then the future will be shaped by us for the common interests of humanity - but if we don't, then it will be imposed, and we will all lose. 'This book has the potential to impel change in our education system which is so badly in need of reform. The new "reconsidered" version in the wake of the COVID pandemic serves to emphasize even more strongly the role AI can play in education and how its use is being accelerated.'Lord Clement-Jones CBE

The Institutional Research profession is currently experimenting with many strategies to assess institutional effectiveness in a manner that reflects the letter and spirit of their unique mission, vision, and values. While a "best-practices" approach to the measurement and assessment of institutional functions is prevalent in the literature, a machine learning approach that synthesizes these parts into a coherent and synergistic approach has not emerged.  A Machine Learning, Artificial Intelligence Approach to Institutional Effectiveness in Higher Education presents a practical, effective, and systematic approach to the measurement, assessment, and sensemaking of institutional performance. Included are instruments and strategies to measure and assess the performance of Curriculum, Learning, Instruction, Support Services, and Program Feasibility as well as a meaningful Environmental Scanning method. The data collected in this system are organized into assessments of institutional effectiveness through the application of machine learning data processes that create an artificial intelligence model of actual institutional performance from the raw performance data. This artificial intelligence is visualized through five organizational sensemaking approaches to monitor, demonstrate, and improve institutional performance. Thus, this book provides a set of tools that can be adopted or adapted to the specific intentions of any institution, making it an invaluable resource for Higher Education administrators, leaders and practitioners.