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AI and Analytics for Smart Cities and Service Systems: Proceedings of the 2021 INFORMS International Conference on Service Science (Lecture Notes in Operations Research)

by Robin Qiu Kelly Lyons Weiwei Chen

This book showcases state-of-the-art advances in service science and related fields of research, education, and practice. It presents emerging technologies and applications in contexts ranging from healthcare, energy, finance, and information technology to transportation, sports, logistics, and public services. Regardless of its size and service, every service organization is a service system. Due to the socio-technical nature of service systems, a systems approach must be adopted in order to design, develop and deliver services aimed at meeting end users’ utilitarian and socio-psychological needs alike. Understanding services and service systems often requires combining multiple methods to consider how interactions between people, technologies, organizations and information create value under various conditions. The papers in this volume highlight a host of ways to approach these challenges in service science and are based on submissions to the 2021 INFORMS Conference on Service Science.

AI and Metaverse: Volume 2 (Studies in Computational Intelligence #1160)

by Roger Lee Jongbae Kim Gwangyoung Gim

The book reports the state-of-the-art results in Artificial Intelligence and Metaverse in both printed and electronic form. Studies in Computation Intelligence (SCI) has grown into the most comprehensive computational intelligence research forum available in the world. This book publishes original papers on both theory and practice that address foundations, state-of-the-art problems and solutions, and crucial challenges.

AI and the Law: A Practical Guide to Using Artificial Intelligence Safely

by Harry Borovick

Learn how to maximize your use of, and benefit from AI, personally and professionally while staying safe. To satisfy professionals and businesses trying to modernize their approaches to work and personal tasks, this book will explain some of the basics of what AI is, what AI is likely to look like in the near future, and how not to get stung using it. You’ll quickly realize that AI isn’t coming, it’s here, along with its opportunities and challenges. While some of the advantages of using AI tools may seem too good to be true, you’ll discover that the key to navigating the early stages of the AI era is to understand its guiding principles and then to prioritize the guidelines. The book features general situations and use cases to help you experience AI for fun and for work while retaining the benefits, profits, creations, outputs, and efficiencies of it. If you’re going to use AI in your daily career, whether as a student, creative, executive, marketer or in sales this book will help you understand how to bypass obstacles and get value from AI with the guidance of an AI and tech lawyer. What You Will Learn Identify, debunk, and protect against business and legal risk in the AI eraDiscuss these issues on a high level with CTOs and COOsSee how professionals can mutually use AI to their benefit Who This Book is For Anyone who wants to know whether AI is really going to change the world through the lens of their industry, or to simply understand how AI can be safely harnessed to maximize daily value while minimizing practical risks.

AI Approaches to the Complexity of Legal Systems: International Workshops Aicol-i/ivr-xxiv, Beijing, China, September 19, 2009 And Aicol-ii/jurix 2009, Rotterdam, The Netherlands, December 16, 2009 Revised Selected Papers (Lecture Notes in Computer Science #6237)

by Ugo Pagallo Monica Palmirani Pompeu Casanovas Giovanni Sartor Serena Villata

This book includes revised selected papers from five International Workshops on Artificial Intelligence Approaches to the Complexity of Legal Systems, AICOL VI to AICOL X, held during 2015-2017: AICOL VI in Braga, Portugal, in December 2015 as part of JURIX 2015; AICOL VII at EKAW 2016 in Bologna, Italy, in November 2016; AICOL VIII in Sophia Antipolis, France, in December 2016; AICOL IX at ICAIL 2017 in London, UK, in June 2017; and AICOL X as part of JURIX 2017 in Luxembourg, in December 2017.The 37 revised full papers included in this volume were carefully reviewed and selected form 69 submissions. They represent a comprehensive picture of the state of the art in legal informatics. The papers are organized in six main sections: legal philosophy, conceptual analysis, and epistemic approaches; rules and norms analysis and representation;legal vocabularies and natural language processing; legal ontologies and semantic annotation; legal argumentation; and courts, adjudication and dispute resolution.

AI Approaches to the Complexity of Legal Systems XI-XII: AICOL International Workshops 2018 and 2020: AICOL-XI@JURIX 2018, AICOL-XII@JURIX 2020, XAILA@JURIX 2020, Revised Selected Papers (Lecture Notes in Computer Science #13048)

by Víctor Rodríguez-Doncel Monica Palmirani Michał Araszkiewicz Pompeu Casanovas Ugo Pagallo Giovanni Sartor

This book includes revised selected papers from the International Workshops on AI Approaches to the Complexity of Legal Systems, AICOL-XI@JURIX2018, held in Groningen, The Netherlands, on December 12, 2018; AICOL-XII@JURIX 2020, held in Brno, Czechia, on December 9, 2020; XAILA@JURIX 2020, held in in Brno, Czechia, on December 9, 2020.*The 17 full and 4 short papers included in this volume were carefully reviewed and selected form 39 submissions. They represent a comprehensive picture of the state of the art in legal informatics. The papers are logically organized in 5 blocks: ​Knowledge Representation; Logic, rules, and reasoning; Explainable AI in Law and Ethics; Law as Web of linked Data and the Rule of Law; Data protection and Privacy Modelling and Reasoning.*Due to the Covid-19 pandemic AICOL-XII@JURIX 2020 and XAILA@JURIX 2020 were held virtually.

AI Assisted Business Analytics: Techniques for Reshaping Competitiveness

by Joseph Boffa

The primary path to success, is to use software designed to sample and analyze cashflow and then link that analysis, with forecasting and market research. The case study will start with a small business income statement indicating a cashflow problem. The analysis that follows will be a comprehensive statistical approach of fiscal management. The case study will provide an overview of the total process of controlling and analyzing cashflow. Business prosperity depends on: 1- Staying in touch with cashflow by means of regular statistical audits2- Transition to statistical methods for forecasting future cashflow3- Link cashflow with customer perception and satisfaction The book is intended for courses with prerequisites that the student has a knowledge of accounting and is comfortable in using Excel. It uses professional Excel with its Analytics Toolkit. Complete knowledge of the Toolkit is not a prerequisite since the book will adequately cover the relevant analytic tools. There is no need for separate statistical software such as SPSS or SAS. The book is intended for intermediate/advanced college level courses in business financial methods and control.

AI-Driven Cybersecurity and Threat Intelligence: Cyber Automation, Intelligent Decision-Making and Explainability

by Iqbal H. Sarker

This book explores the dynamics of how AI (Artificial Intelligence) technology intersects with cybersecurity challenges and threat intelligence as they evolve. Integrating AI into cybersecurity not only offers enhanced defense mechanisms, but this book introduces a paradigm shift illustrating how one conceptualize, detect and mitigate cyber threats. An in-depth exploration of AI-driven solutions is presented, including machine learning algorithms, data science modeling, generative AI modeling, threat intelligence frameworks and Explainable AI (XAI) models. As a roadmap or comprehensive guide to leveraging AI/XAI to defend digital ecosystems against evolving cyber threats, this book provides insights, modeling, real-world applications and research issues. Throughout this journey, the authors discover innovation, challenges, and opportunities. It provides a holistic perspective on the transformative role of AI in securing the digital world.Overall, the useof AI can transform the way one detects, responds and defends against threats, by enabling proactive threat detection, rapid response and adaptive defense mechanisms. AI-driven cybersecurity systems excel at analyzing vast datasets rapidly, identifying patterns that indicate malicious activities, detecting threats in real time as well as conducting predictive analytics for proactive solution. Moreover, AI enhances the ability to detect anomalies, predict potential threats, and respond swiftly, preventing risks from escalated. As cyber threats become increasingly diverse and relentless, incorporating AI/XAI into cybersecurity is not just a choice, but a necessity for improving resilience and staying ahead of ever-changing threats. This book targets advanced-level students in computer science as a secondary textbook. Researchers and industry professionals working in various areas, such as Cyber AI, Explainable and Responsible AI, Human-AI Collaboration, Automation and Intelligent Systems, Adaptive and Robust Security Systems, Cybersecurity Data Science and Data-Driven Decision Making will also find this book useful as reference book.

AI for Diversity (AI for Everything)

by Roger A. Søraa

Artificial intelligence (AI) is increasingly impacting many aspects of people’s lives across the globe, from relatively mundane technology to more advanced digital systems that can make their own decisions. While AI has great potential, it also holds great peril depending on how it is designed and used. AI for Diversity questions how AI technology can lead to inclusion or exclusion for diverse groups in society. The way data is selected, trained, used, and embedded into societies can have unfortunate consequences unless we critically investigate the dangers of systems left unchecked, and can lead to misogynistic, homophobic, racist, ageist, transphobic, or ableist outcomes. This book encourages the reader to take a step back to see how AI is impacting diverse groups of people and how diversity-awareness strategies can impact AI.

AI for Immunology (AI for Everything)

by Louis J. Catania

The bioscience of immunology has given us a better understanding of human health and disease. Artificial intelligence (AI) has elevated that understanding and its applications in immunology to new levels. Together, AI for immunology is an advancing horizon in health care, disease diagnosis, and prevention. From the simple cold to the most advanced autoimmune disorders and now pandemics, AI for immunology is unlocking the causes and cures. Key features: A highly accessible and wide-ranging short introduction to AI for immunology Includes a chapter on COVID-19 and pandemics Includes scientific and clinical considerations, as well as immune and autoimmune diseases

AI for Learning (AI for Everything)

by Carmel Kent Benedict du Boulay

What is artificial intelligence (AI)? How can AI help a learner, a teacher or a system designer? What are the positive impacts of AI on human learning? AI for Learning examines how artificial intelligence can, and should, positively impact human learning, whether it be in formal or informal educational and training contexts. The notion of ‘can’ is bound up with ongoing technological developments. The notion of ‘should’ is bound up with an ethical stance that recognises the complementary capabilities of human and artificial intelligence, as well as the objectives of doing good, not doing harm, increasing justice and maintaining fairness. The book considers the different supporting roles that can help a learner – from AI as a tutor and learning aid to AI as a classroom moderator, among others – and examines both the opportunities and risks associated with each.

AI for People, Democratizing AI: Second EAI International Conference, CAIP 2023, Bologna, Italy, November 24-26, 2023, Proceedings (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering #591)

by Marta Ziosi Giovanni Sartor João Miguel Cunha Angelo Trotta Philipp Wicke

This book constitutes the refereed post-conference proceedings of the Second EAI International Conference on AI for People, Democratizing AI, CAIP 2023, held in Bologna, Italy, during November 24-26, 2023. The 11 regular papers were carefully reviewed and selected from 27 submissions. The papers are organized in thematic sessions on ethical AI and innovation; democratization of AI and governance; AI in society and legal aspects; and data privacy and technology ethics.

AI for School Teachers (AI for Everything)

by Rose Luckin Karine George Mutlu Cukurova

What is artificial intelligence? Can I realistically use it in my school? What’s best done by human intelligence vs. artificial intelligence, and how do I bring these strengths together? What would it look like for me, and my school, to be AI Ready? AI for School Teachers will help teachers and headteachers understand enough about AI to build a strategy for how it can be used in their school. Examining the needs of schools to ensure they are ready to leverage the power of AI and drawing examples from early years to high school students, this book outlines the educational implications and benefits that AI brings to school education in practical ways. It develops an understanding of what AI is and isn't and how we define and measure what we value and provides a framework which supports a step-by-step approach to developing an AI mindset, focusing on ways to improve educational opportunities for students with evidence-informed interventions.

AI for Sports (AI for Everything)

by Chris Brady Karl Tuyls Shayegan Omidshafiei

It seems that artificial intelligence (AI) is always just five years away, but it never arrives. Recently, however, developments have made the practical utility of game theory a genuine reality. Will sport provide the petri dish in which AI will prove itself? What do domain specialists like managers and coaches want to know that they can’t currently find out, and can AI provide the answer? What competitive advantages might AI provide for recruitment, performance and tactics, health and fitness, pedagogy, broadcasting, eSports, gambling and stadium design in the future? Written by leading experts in both sports management and AI, AI for Sports begins to answer these and many other questions on the future of AI for sports.

AI*IA 2016 Advances in Artificial Intelligence: XVth International Conference of the Italian Association for Artificial Intelligence, Genova, Italy, November 29 – December 1, 2016, Proceedings (Lecture Notes in Computer Science #10037)

by Giovanni Adorni, Stefano Cagnoni, Marco Gori and Marco Maratea

This book constitutes the refereed proceedings of the 15th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2016, held in Genova, Italy, in November/December 2016. The 39 full papers presented were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections on optimization and evolutionary algorithms; classification, pattern recognition, and computer vision; multi-agent systems; machine learning; semantic web and description logics; natural language processing; planning and scheduling; and formal verification.

AI*IA 2017 Advances in Artificial Intelligence: XVIth International Conference of the Italian Association for Artificial Intelligence, Bari, Italy, November 14-17, 2017, Proceedings (Lecture Notes in Computer Science #10640)

by Stefano Ferilli Roberto Basili Floriana Esposito Francesca A. Lisi

This book constitutes the refereed proceedings of the 16th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2017, held in Bari, Italy, in November 2017. The 37 full papers presented were carefully reviewed and selected from 91 submissions. The papers are organized in topical sections on applications of AI; natural language processing; knowledge representation and reasoning; knowledge engineering, ontologies and the semantic web; machine learning; philosophical foundations, metacognitive modeling and ethics; and planning and scheduling.

AI*IA 2018 – Advances in Artificial Intelligence: XVIIth International Conference of the Italian Association for Artificial Intelligence, Trento, Italy, November 20–23, 2018, Proceedings (Lecture Notes in Computer Science #11298)

by Paolo Traverso Andrea Passerini Bernardo Magnini Chiara Ghidini

This book constitutes the refereed proceedings of the XVIIth International Conference of the Italian Association for Artificial Intelligence, AI*IA 2018, held in Trento, Italy, in November 2018. The 41 full papers were carefully reviewed and selected from 67 submissions. The papers have been organized in the following topical sections: Agents and Multi-Agent Systems; Applications of AI; Knowledge Engineering, Ontologies and the Semantic Web; Knowledge Representation and Reasoning; Machine Learning; Natural Language Processing; Planning and Scheduling; and Recommendation Systems and Decision Making.

AI*IA 2019 – Advances in Artificial Intelligence: XVIIIth International Conference of the Italian Association for Artificial Intelligence, Rende, Italy, November 19–22, 2019, Proceedings (Lecture Notes in Computer Science #11946)

by Mario Alviano Gianluigi Greco Francesco Scarcello

This book constitutes the proceedings of the XVIIIth International Conference of the Italian Association for Artificial Intelligence, AI*IA 2019, held in Rende, Italy, in November 2019. The 41 full papers were carefully reviewed and selected from 67 submissions. The papers have been organized in the following topical sections: Knowledge Representation for AI, AI and Computation, Machine Learning for AI, and AI and Humans.

AI in and for Africa: A Humanistic Perspective (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)

by Susan Brokensha Eduan Kotzé Burgert A. Senekal

AI in and for Africa: A Humanistic Perspective explores the convoluted intersection of artificial intelligence (AI) with Africa’s unique socio-economic realities. This book is the first of its kind to provide a comprehensive overview of how AI is currently being deployed on the African continent. Given the existence of significant disparities in Africa related to gender, race, labour, and power, the book argues that the continent requires different AI solutions to its problems, ones that are not founded on technological determinism or exclusively on the adoption of Eurocentric or Western-centric worldviews. It embraces a decolonial approach to exploring and addressing issues such as AI’s diversity crisis, the absence of ethical policies around AI that are tailor-made for Africa, the ever-widening digital divide, and the ongoing practice of dismissing African knowledge systems in the contexts of AI research and education. Although the book suggests a number of humanistic strategies with the goal of ensuring that Africa does not appropriate AI in a manner that is skewed in favour of a privileged few, it does not support the notion that the continent should simply opt for a "one-size-fits-all" solution either. Rather, in light of Africa’s rich diversity, the book embraces the need for plurality within different regions’ AI ecosystems. The book advocates that Africa-inclusive AI policies incorporate a relational ethics of care which explicitly addresses how Africa’s unique landscape is entwined in an AI ecosystem. The book also works to provide actionable AI tenets that can be incorporated into policy documents that suit Africa’s needs. This book will be of great interest to researchers, students, and readers who wish to critically appraise the different facets of AI in the context of Africa, across many areas that run the gamut from education, gender studies, and linguistics to agriculture, data science, and economics. This book is of special appeal to scholars in disciplines including anthropology, computer science, philosophy, and sociology, to name a few.

AI in Business: Volume 2 (Studies in Systems, Decision and Control #516)

by Reem Khamis Amina Buallay

This book is a comprehensive guide to understanding the potential of artificial intelligence (AI) in improving business functions, as well as the limitations and challenges that come with its implementation. In this book, readers will learn about the various opportunities that AI presents in business, including how it can automate routine tasks, reduce errors, and increase efficiency. The book covers a range of topics, including how AI can be used in financial reporting, auditing, fraud detection, and tax preparation. However, the book also explores the limitations of AI in business, such as the need for skilled professionals, data quality, and the potential for bias. It examines the challenges that companies face when implementing AI in business functions, including the need for ethical considerations, transparency, and accountability. The book is written for business professionals, business leaders, and anyone interested in the potential of AI in business functions. It offers practical advice on how to implement AI effectively and provides insights into the latest developments in AI technology. Through case studies and real-world examples, readers will gain a deeper understanding of how AI can be used to enhance business functions, as well as the potential pitfalls and limitations to be aware of. Overall, this book is an essential guide for anyone looking to harness the power of AI to improve their business functions and to stay ahead in an increasingly competitive business environment.

AI in Drug Discovery: First International Workshop, AIDD 2024, Held in Conjunction with ICANN 2024, Lugano, Switzerland, September 19, 2024, Proceedings (Lecture Notes in Computer Science #14894)

by Djork-Arné Clevert Michael Wand Kristína Malinovská Jürgen Schmidhuber Igor V. Tetko

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.

The AI Ladder: Accelerate Your Journey to AI

by Rob Thomas Paul Zikopoulos

AI may be the greatest opportunity of our time, with the potential to add nearly $16 trillion to the global economy over the next decade. But so far, adoption has been much slower than anticipated, or so headlines may lead you to believe. With this practical guide, business leaders will discover where they are in their AI journey and learn the steps necessary to successfully scale AI throughout their organization.Authors Rob Thomas and Paul Zikopoulos from IBM introduce C-suite executives and business professionals to the AI Ladder—a unified, prescriptive approach to help them understand and accelerate the AI journey. <P><P>Complete with real-world examples and real-life experiences, this book explores AI drivers, value, and opportunity, as well as the adoption challenges organizations face. Understand why you can’t have AI without an information architecture (IA) <P><P>Appreciate how AI is as much a cultural change as it is a technological one <P><P>Collect data and make it simple and accessible, regardless of where it lives <P><P>Organize data to create a business-ready analytics foundation <P><P>Analyze data, and build and scale AI with trust and transparency <P><P>Infuse AI throughout your entire business and create intelligent workflows

AI-ML for Decision and Risk Analysis: Challenges and Opportunities for Normative Decision Theory (International Series in Operations Research & Management Science #345)

by Louis Anthony Cox Jr.

This book explains and illustrates recent developments and advances in decision-making and risk analysis. It demonstrates how artificial intelligence (AI) and machine learning (ML) have not only benefitted from classical decision analysis concepts such as expected utility maximization but have also contributed to making normative decision theory more useful by forcing it to confront realistic complexities. These include skill acquisition, uncertain and time-consuming implementation of intended actions, open-world uncertainties about what might happen next and what consequences actions can have, and learning to cope effectively with uncertain and changing environments. The result is a more robust and implementable technology for AI/ML-assisted decision-making.The book is intended to inform a wide audience in related applied areas and to provide a fun and stimulating resource for students, researchers, and academics in data science and AI-ML, decision analysis, and other closely linked academic fields. It will also appeal to managers, analysts, decision-makers, and policymakers in financial, health and safety, environmental, business, engineering, and security risk management.

The AI Revolution: Volume 1 (Studies in Systems, Decision and Control #524)

by Bahaa Awwad

This comprehensive book explores the transformative role of artificial intelligence (AI) in business innovation and research. It provides a solid foundation in AI technologies, such as machine learning, natural language processing, and computer vision, and examines how they reshape business models and revolutionize industries. The book highlights the strategic implications of AI in enhancing customer experience, optimizing operations, and enabling data-driven decision-making. It explores the integration of AI with emerging trends like IoT, blockchain, and cloud computing for innovation. The role of AI in advancing scientific discovery and academic research is also explored, addressing challenges and opportunities in AI-driven methodologies. Organizational and ethical dimensions of AI implementation are considered, including talent acquisition, skills development, and data governance. Real-world case studies showcase AI's transformative power across diverse industries. This forward-thinking guide equips academics, researchers, and business leaders with knowledge and insights to harness the potential of AI and contribute to innovation and research.

The AI Revolution: Volume 2 (Studies in Systems, Decision and Control #525)

by Bahaa Awwad

This comprehensive book explores the transformative role of artificial intelligence (AI) in business innovation and research. It provides a solid foundation in AI technologies, such as machine learning, natural language processing, and computer vision, and examines how they reshape business models and revolutionize industries. The book highlights the strategic implications of AI in enhancing customer experience, optimizing operations, and enabling data-driven decision-making. It explores the integration of AI with emerging trends like IoT, blockchain, and cloud computing for innovation. The role of AI in advancing scientific discovery and academic research is also explored, addressing challenges and opportunities in AI-driven methodologies. Organizational and ethical dimensions of AI implementation are considered, including talent acquisition, skills development, and data governance. Real-world case studies showcase AI's transformative power across diverse industries. This forward-thinking guide equips academics, researchers, and business leaders with knowledge and insights to harness the potential of AI and contribute to innovation and research.

AI Versus Epidemics (Synthesis Lectures on Learning, Networks, and Algorithms)

by James Hughes Sheridan Houghten Michael Dubé Daniel Ashlock Joseph Alexander Brown Wendy Ashlock Matthew Stoodley

This book presents algorithms and tools that are designed to model and extract information from personal contact networks, which represent which individuals in a population are physically in contact with one another. The authors developed these tools based on research they conducted during the COVID-19 pandemic, with the goal of improving responses to epidemics in the future. The book provides methods for modelling the transmission of infection across a population. The authors explain how an epidemic model can be used to strategically distribute vaccines and minimize the spread of a virus. The book shows how evolutionary computation, graph compression, and network induction can be utilized to manage issues that arise from an epidemic.

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