Choice-ACRL webinar. (2023, September 28). How artificial intelligence drives scientific research. Springer Nature. https://youtu.be/gitxCfoHHXI?si=aJY3wPG5j7ixvYZf
Flierl, M. (2023, August 15). AI, higher education, and medical librarianship: Opportunities and risks. NNLM Region 6 Spotlight Speaker webinar. https://utoledo.libapps.com/libguides/admin_c.php?g=1346958&p=9936351
JoVE Webinar. (2023, September 20). ChatGPT & libraries: Applications and implications for teaching and learning.
Lo, L.S. (2023). The CLEAR path: A framework for enhancing information literacy through prompt engineering. The Journal of Academic Librarianship, 49(4), 102720. https://doi.org/10.1016/j.acalib.2023.102720
McGraw-Hill Masterclass Webinar. (2023, September 19). Artificial Intelligence in Medicine.
Oxford University Press. (n.d.). Artificial intelligence. In Oxford Reference. Retrieved 17 Nov. 2023, from https://www.oxfordreference.com/view/10.1093/oi/authority.20110803095426960
Webinar sponsored by State University of New York at Albany. (2023, November 29). The role of Generative AI in LIS publishing: Opportunities and challenges.
Wheatley, A. & Hervieux, S. (2023, October 11). ChatGPT and Generative AI: Benefits, concerns, and opportunities for health science libraries. Medical Library Association, Midwest Chapter Workshop.
Search the UTMOST library catalog for more information on artificial intelligence.
General Aspects of Applying Generative AI in Higher Education
This book explores the transformative impact of generative artificial intelligence (GenAI) on teaching and learning, examining how recent advancements in GenAI are revolutionizing educational practices across disciplines. The book is organized into three parts: an overview of GenAI in education, its application in diverse educational contexts, and future perspectives on how educators and GenAI can interface. The first part addresses the pressing concerns within the educational landscape, both the bridges GenAI allows us to build and the remaining as well as the emerging gaps. The middle part explores specific academic disciplines, such as history, sports medicine, mathematics, engineering, and the humanities, dissecting the influence of GenAI on each. The final part looks ahead, discussing the ethical implications, the evolving role of prompting, and innovative frameworks for personalized learning. By presenting a balanced view of the opportunities that are now within reach through GenAI and the challenges such leaps pose to the way we learn and teach, this book allows interested educators to learn from the early-adopting contributors to fruitfully and responsibly integrate such technologies into their pedagogical practices. It serves as a resource for anyone interested in the future of educational practices and research of education, offering insights that can spark further exploration and discussion within the academic community and educational policy makers.
Machine Learning for Decision Makers
This new and updated edition takes you through the details of machine learning to give you an understanding of cognitive computing, IoT, big data, AI, quantum computing, and more. The book explains how machine learning techniques are used to solve fundamental and complex societal and industry problems. This second edition builds upon the foundation of the first book, revises all of the chapters, and updates the research, case studies, and practical examples to bring the book up to date with changes that have occurred in machine learning. A new chapter on quantum computers and machine learning is included to prepare you for future challenges. Insights for decision makers will help you understand machine learning and associated technologies and make efficient, reliable, smart, and efficient business decisions. All aspects of machine learning are covered, ranging from algorithms to industry applications. Wherever possible, required practical guidelines and best practices related to machine learning and associated technologies are discussed. Also covered in this edition are hot-button topics such as ChatGPT, superposition, quantum machine learning, and reinforcement learning from human feedback (RLHF) technology. Upon completing this book, you will understand machine learning, IoT, and cognitive computing and be prepared to cope with future challenges related to machine learning. What You Will Learn Master the essentials of machine learning, AI, cloud, and the cognitive computing technology stack Understand business and enterprise decision-making using machine learning Become familiar with machine learning best practices Gain knowledge of quantum computing and quantum machine learning Who This Book Is For Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them
Artificial Intelligence in Higher Education and Scientific Research
This book explains the interaction between artificial intelligence and higher education. It explores artificial intelligence's tangible and intangible impact on higher education and scientific research and discusses how higher education and scientific research enhance the progress of artificial intelligence technologies. Based on systematic analysis with a multidisciplinary approach and a combination of theory and practice, the book brings original perspectives from the massive use of artificial intelligence in higher education and scientific research since the appearance of COVID-19. This book also discusses ethics in artificial intelligence, taking into consideration the recommendation on ethics of artificial intelligence adopted by UNESCO. This book explains the importance of technological sovereignty and new strategies to face current and future challenges related to e-learning, deep learning, and machine learning.
Artificial Intelligence, Social Harms and Human Rights
This book critically explores how and to what extent artificial intelligence (AI) can infringe human rights and/or lead to socially harmful consequences and how to avoid these. The European Union has outlined how it will use big data, machine learning, and AI to tackle a number of inherently social problems, including poverty, climate change, social inequality and criminality. The contributors of this book argue that the developments in AI must take place in an appropriate legal and ethical framework and they make recommendations to ensure that harm and human rights violations are avoided. The book is split into two parts: the first addresses human rights violations and harms that may occur in relation to AI in different domains (e.g. border control, surveillance, facial recognition) and the second part offers recommendations to address these issues. It draws on interdisciplinary research and speaks to policy-makers and criminologists, sociologists, scholars in STS studies, security studies scholars and legal scholars.
A Beginner's Guide to Introduce Artificial Intelligence in Teaching and Learning
This book reimagines education in today's Artificial Intelligence (AI) world and the Fourth Industrial Revolution. Artificial intelligence will drastically affect every industry and sector, and education is no exception. This book aims at how AI may impact the teaching and learning process in education. This book is designed to demystify AI for teachers and learners. This book will help improve education and support institutions in the phenomena of the emergence of AI in teaching and learning. This book presents a comprehensive study of how AI improves teaching and learning, from AI-based learning platforms to AI-assisted proctored examinations. This book provides educators, learners, and administrators on how AI makes sense in their everyday practice. Describing the application of AI in ten key aspects, this comprehensive volume prepares educational leaders, designers, researchers, and policymakers to effectively rethink the teaching and learning process and environments that students need to thrive. The readers of this book never fall behind the fast pace and promising innovations of today's most advanced learning technology.
Artificial Intelligence and Academic Integrity
Buy a new version of this textbook and receive access to the Connected eBook on Casebook Connect, including lifetime access to the online ebook with highlight, annotation, and search capabilities. Access also includes an outline tool and other helpful resources. Connected eBooks provide what you need most to be successful in your law school classes. Artificial Intelligence and Academic Integrity, by April G. Dawson, is Aspen's concise primer intended to increase student awareness of the protocols, possibilities, and ethical implications of using AI systems in their legal education studies, while also giving professors assurance that their students are informed of the same. AI is having a sudden and profound impact on the legal profession, as it has in virtually professions worldwide. Understanding how to leverage AI tools effectively and appropriately will give law school graduates a competitive edge among legal employers interested to hire tech-savvy young lawyers. But AI is also having a profound impact on the legal education experience. As more and more students seek assistance from ChatGPT and similar tools for their academic work, questions arise as to what they are gaining or sacrificing in the process; and whether, or at what point, using AI in academic work falls within the bounds of academic integrity. Such dramatic developments call for better knowledge and understanding of the ethical implications associated with using AI systems in law school. April G. Dawson explores the pros and cons of using powerful AI tools in law school while maintaining institutional standards for academic rigor and intellectual honesty in legal education--alongside students' own values and developing sense of legal ethics. Professors and students will benefit from: Assurance that AIAI raises student awareness of the importance of 1) using generative AI tools like ChatGPT responsibly; and 2) understanding how academic integrity facilitates learning and prepares students to become ethically responsible in the practice of law; 3) researching and reading their school's code of conduct, and 4) understanding the policies of individual professors with respect to the use of generative AI tools. Reflection: Professional Identity Formation (PIF), questions that prompt students to reflect on their own experiences with generative AI--both its useful applications for learning and practice, as well as the potential for using AI in ways that violate academic integrity and undermine principles of professional responsibility. Examples of individuals making choices and realizing the consequences of their decisions for a range of situations and ethical quandaries Case Studies feature summaries of recent landmark cases and discussion of law and policy. A concise overview of law-specific AI products, the tasks they perform, and the reasons for the legal profession's measured approach to adopting them Incisive discussion of the potential for generative AI's to significantly mitigate, though not fully address, the nation's access to justice crisis
Artificial Intelligence and Its Discontents
On what basis can we challenge Artificial Intelligence (AI) - its infusion, investment, and implementation across the globe? This book answers this question by drawing on a range of critical approaches from the social sciences and humanities, including posthumanism, ethics and human values, surveillance studies, Black feminism, and other strategies for social and political resistance. The authors analyse timely topics, including bias and language processing, responsibility and machine learning, COVID-19 and AI in health technologies, bio-AI and nanotechnology, digital ethics, AI and the gig economy, representations of AI in literature and culture, and many more. This book is for those who are currently working in the field of AI critique and disruption as well as in AI development and programming. It is also for those who want to learn more about how to doubt, question, challenge, reject, reform and otherwise reprise AI as it been practiced and promoted.
Toward a Conceptual Network for the Private Law of Artificial Intelligence
This book provides a set of proposals for the new conceptual network required in order to establish civil law rules for a world permeated by Artificial Intelligence. These proposals are intended by their authors to push the debate on the new civil law forward. In spite of the natural conservatism of jurists, some innovative or even futuristic ideas are called for, also because the future, even this not-so-distant one, is difficult to foresee. Paradoxically, and unlike in the past, this lack of knowledge must not stop us from planning. If it does, humankind may, as some pessimists already claim, lose its chance to win the battle for control of the world. The rise and expansion of Artificial Intelligence and robotics in recent years has highlighted a pressing need to create a suitable legal framework for this new phenomenon. The debate on the subject, although wide-ranging and involving many new legal documents, is still quite general and preliminary in nature, although these preparatory works illustrate the very real need to develop appropriate new civil law arrangements. It is exactly the branch of private law where the necessity of these new rules appears to be the most imperative. Autonomous vehicles, medical robots, and expertise software raise fundamental questions on aspects of civil liability such as culpability; whereas the growth in popularity of automated, intelligent software systems for concluding contracts requires a new approach to many fundamental and deeply rooted elements of contract law, e.g. consciousness, intent, error, deception, interpretation of contracts and good faith. Ruling on these specific matters demands the identification and clarification of certain key points, which shall become the foundation for constructing AI/robot civil law.
Artificial Intelligence in Music, Sound, Art and Design
This book constitutes the refereed proceedings of the 12th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2023, held as part of Evo* 2023, in April 2023, co-located with the Evo* 2023 events, EvoCOP, EvoApplications, and EuroGP. The 20 full papers and 7 short papers presented in this book were carefully reviewed and selected from 55 submissions. They cover a wide range of topics and application areas of artificial intelligence, including generative approaches to music and visual art, deep learning, and architecture.
Convergence: Artificial Intelligence and Quantum Computing
Prepare for the coming convergence of AI and quantum computing A collection of essays from 20 renowned, international authors working in industry, academia, and government, Convergence: Artificial Intelligence and Quantum Computing explains the impending convergence of artificial intelligence and quantum computing. A diversity of viewpoints is presented, each offering their view of this coming watershed event. In the book, you'll discover that we're on the cusp of seeing the stuff of science fiction become reality, with huge implications for ripping up the existing social fabric, global economy, and current geopolitical order. Along with an incisive foreword by Hugo- and Nebula-award winning author David Brin, you'll also find: Explorations of the increasing pace of technological development Explanations of why seemingly unusual and surprising breakthroughs might be just around the corner Maps to navigate the potential minefields that await us as AI and quantum computing come together A fascinating and thought-provoking compilation of insights from some of the leading technological voices in the world, Convergence convincingly argues that we should prepare for a world in which very little will remain the same and shows us how to get ready.
Artificial Intelligence for Healthy Longevity
This book reviews the state-of-the-art efforts to apply machine learning and AI methods for healthy aging and longevity research, diagnosis, and therapy development. The book examines the methods of machine learning and their application in the analysis of big medical data, medical images, the creation of algorithms for assessing biological age, and effectiveness of geroprotective medications. The promises and challenges of using AI to help achieve healthy longevity for the population are manifold. This volume, written by world-leading experts working at the intersection of AI and aging, provides a unique synergy of these two highly prominent fields and aims to create a balanced and comprehensive overview of the application methodology that can help achieve healthy longevity for the population. The book is accessible and valuable for specialists in AI and longevity research, as well as a wide readership, including gerontologists, geriatricians, medical specialists, and students from diverse fields, basic scientists, public and private research entities, and policy makers interested in potential intervention in degenerative aging processes using advanced computational tools.
How AI impacts urban living and public health
17th International Conference, ICOST 2019, New York City, NY, USA, October 14-16, 2019
Ethics of Artificial Intelligence
This open access collection of AI ethics case studies is the first book to present real-life case studies combined with commentaries and strategies for overcoming ethical challenges. 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.
Artificial Intelligence for Industries of the Future
This book provides a brief synthesis of the known implementations, opportunities and challenges at the intersection of artificial intelligence (AI) and modern industry beyond the big-four companies that traditionally consume and produce such advanced technology: Facebook, Amazon, Microsoft and Google. With this information, the author also makes some reasonable claims about the role of AI in future industries. The book draws on a broad range of material, including reports from consulting firms, published surveys, academic papers and books, and expert knowledge available to the author due to numerous collaborations in academia and industry on AI. It is rigorous rather than speculative, drawing on known findings and expert summaries, where available. This provides industry leaders and other interested stakeholders with an accessible review of contemporary perspectives on AI's forward-looking role in industry as well as a clarifying guide on the major issues that companies are likely to face as they commence on this exciting path. Examines the likely role of AI in industries of the future, both known and unknown Presents use-cases of AI currently being explored across Big Tech, multi-national corporations and start-ups Explores the regulation of AI and its potential impacts on the workforce