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Artificial Intelligence in Marketing (Review of Marketing Research #20)

Review of Marketing Research pushes the boundaries of marketing—broadening the marketing concept to make the world a better place. Here, leading scholars explore how marketing is currently shaping, and being shaped by, the evolution of Artificial Intelligence (AI). Topics covered include the effects of AI on: economics; personalisation; pricing; content generation; the identification, structuring, and prioritization of customer needs; customer feedback; Natural Language Processing; image analytics; deep learning; and the anthropomorphism of AI, such as in virtual assistants and chatbots. Each chapter provides thought provoking discussions which will be relevant to researchers, professionals, and students.

Artificial Intelligence in Medicine: Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, AIMDM'99, Aalborg, Denmark, June 20-24, 1999, Proceedings (Lecture Notes in Computer Science #1620)

Artificial Intelligence in Operational Research: (pdf)

Artificial Intelligence in Practice: How 50 Successful Companies Used AI and Machine Learning to Solve Problems

Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.

Artificial Intelligence in Practice: How 50 Successful Companies Used AI and Machine Learning to Solve Problems

Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.

Artificial Intelligence in Project Management and Making Decisions (Studies in Computational Intelligence #1035)

This book presents new developments and advances in the theory, applications, and design methods of computational intelligence, integrated in various areas of project management and BIM environments. The chapters of the book span different soft computing techniques, such as: linguistic data summarization, fuzzy systems, evolutionary algorithms, estimation distribution algorithms, computing with words, augmented reality, and hybrid intelligence systems. In addition, different applications of the neutrosophic theory are presented for the treatment of uncertainty and indeterminacy in decision-making processes. Several chapters of the book constitute systematic reviews, useful for future investigations in the following topics: linguistic summarization of data, augmented reality, and the development of BIM technologies. It is a particularly interesting book for engineers, researchers, specialists, teachers, and students related to project management and the development of BIM technologies.

Artificial Intelligence in the Gulf: Challenges and Opportunities

This book presents the first broad reflection on the challenges, opportunities, and implications of Artificial Intelligence (AI) in the Gulf Cooperation Council (GCC). Unique results and insights are derived through case studies from diverse disciplines, including engineering, economics, data science, policy-making, governance, and humanscience. Particularly related to these ‘softer’ disciplines, we make some unexplored yet topical contributions to the literature, with a focus on the GCC (but by no means limited to it), including AI and implications for women, Islamic schools of thought on AI, and the power of AI to help deliver wellbeing and happiness in cities and urban spaces. Finally, the readers are provided with a synthesis of ideas, lessons learned, and a path forward based on the diverse content of the chapters. The book caters to the educated non specialist with interest in AI, targeting a wide audience including professionals, academics, government officials, policymakers, entrepreneurs, and non-governmental organizations.

Artificial Intelligence in Value Creation: Improving Competitive Advantage

This book analyses various models of value creation in projects and businesses by applying different forms of Artificial Intelligence in their products and services. First presenting the main concepts and ideas behind AI, Wodecki assesses different models of technology-based value creation based upon the analysis of over 400 case studies. This framework shows how AI may influence both value creation and competitive advantage (efficiency, creativity and flexibility) within a modern organization. Finally, a conceptual model is formulated to evaluate AI-supported in-company projects and new ventures and identify the key managerial and technical competencies required.

Artificial Intelligence Law

It is inevitable, given the enormous media-driven concern generated by the recent application of artificial intelligence (AI) to an ever-expanding spectrum of day-to-day human experience, that the need for a clearly articulated legal response has become imperative. This book both clarifies the controversial issues surrounding the use of AI and explores in great detail how, far from being “unregulated,” the creation, distribution, and operation of AI systems currently is, and will remain, subject to a vast array of existing laws and regulations all over the world. Demonstrating beyond any doubt that the traditional concepts of legal responsibility, including duty of care, negligence, and compensation for damages, will always be applicable to those humans who create and/or use artificially intelligent things or systems, the author shows how AI systems are clearly implicated in numerous existing legal regimes, including the following: relevant provisions under international law and EU law; applicable provisions in the laws of the United States, the United Kingdom, France, China, India, Japan, South Korea, and Singapore; and numerous national provisions in the legal fields of health and safety, intellectual property, competition, privacy and data protection, and military engagement. However, given the lack of international consensus on this vitally important issue, the author suggests that any worldwide agreement on the legal responsibilities relating to the use of AI will need to be carefully defined, and that provisions will need to be reviewed to determine how they will apply to any new range of artificially intelligent creations. The purpose of this book is to review those legal concepts, throughout the world, that currently govern the application of AI and to comment on modifications or extensions of the rule of law that are being proposed as necessary to serve and protect humanity in relation to the expanding applications of AI. It is important that anyone who uses or is affected by AI products understands the relationship between existing laws and regulations in major markets around the world and those areas where initial regulations may be required. For them, for their counsel, and for the various policy and regulatory authorities confronted with AI issues, this book will prove an essential guide.

Artificial Intelligence, Management and Trust (Routledge Studies in Trust Research)

The main challenge related to the development of artificial intelligence (AI) is to establish harmonious human-AI relations, necessary for the proper use of its potential. AI will eventually transform many businesses and industries; its pace of development is influenced by the lack of trust on the part of society. AI autonomous decision-making is still in its infancy, but use cases are evolving at an ever-faster pace. Over time, AI will be responsible for making more decisions, and those decisions will be of greater importance. The monograph aims to comprehensively describe AI technology in three aspects: organizational, psychological, and technological in the context of the increasingly bold use of this technology in management. Recognizing the differences between trust in people and AI agents and identifying the key psychological factors that determine the development of trust in AI is crucial for the development of modern Industry 4.0 organizations. So far, little is known about trust in human-AI relationships and almost nothing about the psychological mechanisms involved. The monograph will contribute to a better understanding of how trust is built between people and AI agents, what makes AI agents trustworthy, and how their morality is assessed. It will therefore be of interest to researchers, academics, practitioners, and advanced students with an interest in trust research, management of technology and innovation, and organizational management.

Artificial Intelligence, Management and Trust (Routledge Studies in Trust Research)

The main challenge related to the development of artificial intelligence (AI) is to establish harmonious human-AI relations, necessary for the proper use of its potential. AI will eventually transform many businesses and industries; its pace of development is influenced by the lack of trust on the part of society. AI autonomous decision-making is still in its infancy, but use cases are evolving at an ever-faster pace. Over time, AI will be responsible for making more decisions, and those decisions will be of greater importance. The monograph aims to comprehensively describe AI technology in three aspects: organizational, psychological, and technological in the context of the increasingly bold use of this technology in management. Recognizing the differences between trust in people and AI agents and identifying the key psychological factors that determine the development of trust in AI is crucial for the development of modern Industry 4.0 organizations. So far, little is known about trust in human-AI relationships and almost nothing about the psychological mechanisms involved. The monograph will contribute to a better understanding of how trust is built between people and AI agents, what makes AI agents trustworthy, and how their morality is assessed. It will therefore be of interest to researchers, academics, practitioners, and advanced students with an interest in trust research, management of technology and innovation, and organizational management.

Artificial Intelligence Marketing and Predicting Consumer Choice: An Overview of Tools and Techniques

The ability to predict consumer choice is a fundamental aspect to success for any business. In the context of artificial intelligence marketing, there are a wide array of predictive analytic techniques available to achieve this purpose, each with its own unique advantages and disadvantages. Artificial Intelligence Marketing and Predicting Consumer Choice serves to integrate these widely disparate approaches, and show the strengths, weaknesses, and best applications of each. It provides a bridge between the person who must apply or learn these problem-solving methods and the community of experts who do the actual analysis. It is also a practical and accessible guide to the many remarkable advances that have been recently made in this fascinating field. Online resources: bonus chapters on AI, ensembles and neural nets, and finishing experiments, plus single and multiple product simulators.

Artificial Intelligence Marketing and Predicting Consumer Choice: An Overview of Tools and Techniques

The ability to predict consumer choice is a fundamental aspect to success for any business. In the context of artificial intelligence marketing, there are a wide array of predictive analytic techniques available to achieve this purpose, each with its own unique advantages and disadvantages. Artificial Intelligence Marketing and Predicting Consumer Choice serves to integrate these widely disparate approaches, and show the strengths, weaknesses, and best applications of each. It provides a bridge between the person who must apply or learn these problem-solving methods and the community of experts who do the actual analysis. It is also a practical and accessible guide to the many remarkable advances that have been recently made in this fascinating field. Online resources: bonus chapters on AI, ensembles and neural nets, and finishing experiments, plus single and multiple product simulators.

Artificial Intelligence of Health-Enabled Spaces

Artificial Intelligence of Health-Enabled Spaces (AIoH) has made a number of revolutionary advances in clinical studies that we are aware of. Among these advances, intelligent and medical services are gaining a great deal of interest. Nowadays, AI-powered technologies are not only used in saving lives, but also in our daily life activities in diagnosing, controlling, and even tracking of COVID-19 patients. These AI-powered solutions are expected to communicate with cellular networks smoothly in the next-generation networks (5G/6G and beyond) for more effective/critical medical applications. This will open the door for other interesting research areas. This book focuses on the development and analysis of artificial intelligence (AI) model applications across multiple disciplines. AI-based deep learning models, fuzzy and hybrid intelligent systems, and intrinsic explainable models are also presented in this book. Some of the fields considered in this smart health-oriented book include AI applications in electrical engineering, biomedical engineering, environmental engineering, computer engineering, education, cyber security, chemistry, pharmacy, molecular biology, and tourism. This book is dedicated to addressing the major challenges in fighting diseases and psychological issues using AI. These challenges vary from cost and complexity to availability and accuracy. The aim of this book is hence to focus on both the design and implementation aspects of AI-based approaches in the proposed health-related solutions. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via intelligent enabling technologies.

Artificial Intelligence of Health-Enabled Spaces

Artificial Intelligence of Health-Enabled Spaces (AIoH) has made a number of revolutionary advances in clinical studies that we are aware of. Among these advances, intelligent and medical services are gaining a great deal of interest. Nowadays, AI-powered technologies are not only used in saving lives, but also in our daily life activities in diagnosing, controlling, and even tracking of COVID-19 patients. These AI-powered solutions are expected to communicate with cellular networks smoothly in the next-generation networks (5G/6G and beyond) for more effective/critical medical applications. This will open the door for other interesting research areas. This book focuses on the development and analysis of artificial intelligence (AI) model applications across multiple disciplines. AI-based deep learning models, fuzzy and hybrid intelligent systems, and intrinsic explainable models are also presented in this book. Some of the fields considered in this smart health-oriented book include AI applications in electrical engineering, biomedical engineering, environmental engineering, computer engineering, education, cyber security, chemistry, pharmacy, molecular biology, and tourism. This book is dedicated to addressing the major challenges in fighting diseases and psychological issues using AI. These challenges vary from cost and complexity to availability and accuracy. The aim of this book is hence to focus on both the design and implementation aspects of AI-based approaches in the proposed health-related solutions. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via intelligent enabling technologies.

Artificial Intelligence, Strategic Communicators and Activism (Global PR Insights)

In a world that is increasingly wary of artificial intelligence (AI), this book explores the pressing need for strategic communicators to move away from being advocates for AI and move towards a more critical activist role that enables them to counter AI-driven threats to communities and relationships. AI is contributing to inequality, misinformation and environmental damage, among other problems. This book argues that strategic communicators are uniquely placed to help counter AI-driven challenges because of their skills in relationship-building and their ability to craft and deliver messages effectively. By discussing the different professional activist approaches that communicators can take in relation to growing AI challenges, the book offers multiple perspectives that will help to build knowledge in diverse settings and develop practice, especially in community and activist strategic communication. Research-based and combining theory with practice, this thought-provoking book will be welcomed by strategic communication scholars and practitioners alike eager to develop a critical approach to the challenges surrounding AI.

Artificial Intelligence, Strategic Communicators and Activism (Global PR Insights)

In a world that is increasingly wary of artificial intelligence (AI), this book explores the pressing need for strategic communicators to move away from being advocates for AI and move towards a more critical activist role that enables them to counter AI-driven threats to communities and relationships. AI is contributing to inequality, misinformation and environmental damage, among other problems. This book argues that strategic communicators are uniquely placed to help counter AI-driven challenges because of their skills in relationship-building and their ability to craft and deliver messages effectively. By discussing the different professional activist approaches that communicators can take in relation to growing AI challenges, the book offers multiple perspectives that will help to build knowledge in diverse settings and develop practice, especially in community and activist strategic communication. Research-based and combining theory with practice, this thought-provoking book will be welcomed by strategic communication scholars and practitioners alike eager to develop a critical approach to the challenges surrounding AI.

Artificial Intelligence Techniques for a Scalable Energy Transition: Advanced Methods, Digital Technologies, Decision Support Tools, and Applications

This book presents research in artificial techniques using intelligence for energy transition, outlining several applications including production systems, energy production, energy distribution, energy management, renewable energy production, cyber security, industry 4.0 and internet of things etc. The book goes beyond standard application by placing a specific focus on the use of AI techniques to address the challenges related to the different applications and topics of energy transition. The contributions are classified according to the market and actor interactions (service providers, manufacturers, customers, integrators, utilities etc.), to the SG architecture model (physical layer, infrastructure layer, and business layer), to the digital twin of SG (business model, operational model, fault/transient model, and asset model), and to the application domain (demand side management, load monitoring, micro grids, energy consulting (residents, utilities), energy saving, dynamic pricing revenue management and smart meters, etc.).

Artificial Intelligence Techniques for Rational Decision Making (Advanced Information and Knowledge Processing)

Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon’s bounded rationality theory are flexible due to advanced signal processing techniques, Moore’s Law and artificial intelligence.Artificial Intelligence Techniques for Rational Decision Making examines and defines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making:Theory of the marginalization of irrelevant information Principal component analysis Independent component analysisAutomatic relevance determination methodIn addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence.Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas.

Artificial Intelligence Techniques in Human Resource Management (21st Century Business Management)

This new volume presents a range of techniques that aim to enhance the operation of human resource management by applying state-of-the-art artificial intelligence technology. With illustrative case studies, the volume uses examples from several real-life problems and includes their possible solutions using advanced AI technology. The book explores the confluence of smart computing and traditional businesses to foster productivity, profitability, and prosperity and goes on to apply AI techniques in the recruitment process, with enterprise resource planning management software, for manpower optimization systems in colleges, for creating uniformity in HRM across organizations, for creating conflicting strategy management techniques, and more. One pandemicrelated chapter discusses the use of radio frequency-based technology for monitoring social distancing.

Artificial Intelligence Techniques in Human Resource Management (21st Century Business Management)

This new volume presents a range of techniques that aim to enhance the operation of human resource management by applying state-of-the-art artificial intelligence technology. With illustrative case studies, the volume uses examples from several real-life problems and includes their possible solutions using advanced AI technology. The book explores the confluence of smart computing and traditional businesses to foster productivity, profitability, and prosperity and goes on to apply AI techniques in the recruitment process, with enterprise resource planning management software, for manpower optimization systems in colleges, for creating uniformity in HRM across organizations, for creating conflicting strategy management techniques, and more. One pandemicrelated chapter discusses the use of radio frequency-based technology for monitoring social distancing.

Artificial Intelligence (WIRED guides): How Machine Learning Will Shape the Next Decade

The past decade has witnessed extraordinary advances in artificial intelligence. But what precisely is it and where does its future lie?In this brilliant, one-stop guide WIRED journalist Matt Burgess explains everything you need to know about AI. He describes how it works. He looks at the ways in which it has already brought us everything from voice recognition software to self-driving cars, and explores its potential for further revolutionary change in almost every area of our daily lives. He examines the darker side of machine learning: its susceptibility to hacking; its tendency to discriminate against particular groups; and its potential misuse by governments. And he addresses the fundamental question: can machines become as intelligent as human beings?

Artificial Intelligence with Power BI: Take your data analytics skills to the next level by leveraging the AI capabilities in Power BI

Learn how to create your own AI model and consume it in your Power BI reports to gain better insights from your dataKey FeaturesLearn how to gain better insights from your data by applying different AI techniques within Power BISave time by creating machine learning models independently and integrating them within your BI reportsUnderstand how to combine Cognitive Services and Azure Machine Learning together with Power BIBook DescriptionThe artificial intelligence (AI) capabilities in Power BI enable organizations to quickly and easily gain more intelligent insights from unstructured and structured data.This book will teach you how to make use of the many AI features available today in Power BI to quickly and easily enrich your data and gain better insights into patterns that can be found in your data.You'll begin by understanding the benefits of AI and how it can be used in Power BI. Next, you'll focus on exploring and preparing your data for building AI projects and then progress to using prominent AI features already available in Power BI, such as forecasting, anomaly detection, and Q&A. Later chapters will show you how to apply text analytics and computer vision within Power BI reports. This will help you create your own Q&A functionality in Power BI, which allows you to ask FAQs from another knowledge base and then integrate it with PowerApps. Toward the concluding chapters, you'll be able to create and deploy AutoML models trained in Azure ML and consume them in Power Query Editor. After your models have been trained, you'll work through principles such as privacy, fairness, and transparency to use AI responsibly.By the end of this book, you'll have learned when and how to enrich your data with AI using the out-of-the-box AI capabilities in Power BI.What you will learnApply techniques to mitigate bias and handle outliers in your dataPrepare time series data for forecasting in Power BIPrepare and shape your data for anomaly detectionUse text analytics in Power Query EditorIntegrate QnA Maker with PowerApps and create an appTrain your own models and identify the best one with AutoMLIntegrate an Azure ML workspace with Power BI and use endpoints to generate predictionsWho this book is forThis artificial intelligence BI book is for data analysts and BI developers who want to explore advanced analytics or artificial intelligence possibilities with their data. Prior knowledge of Power BI will help you get the most out of this book.

Artificial Market Experiments with the U-Mart System (Agent-Based Social Systems #4)

Economics went through great development in the 20th century. This development, which was based mainly on mathematical methods, is not an appropriate method of analyzing markets that change every hour and every day. In a stock market, prices constantly change depending on speculation. U-Mart, a manmade market, has been proposed in order to study such instantly moving markets. Although the U-Mart system is internationally acclaimed for being at the forefront of market research, its use is by no means limited to a small number of researchers on the fringe. The whole system, including its source code, is open and is distributed without charge, testifying to a philosophy of creating and providing a common test bed for research into financial markets.

Artificial Markets Modeling: Methods and Applications (Lecture Notes in Economics and Mathematical Systems #599)

This volume features contributions to agent-based computational modeling from the social sciences and computer sciences. It presents applications of methodologies and tools, focusing on the uses, requirements, and constraints of agent-based models used by social scientists. Topics include agent-based macroeconomics, the emergence of norms and conventions, the dynamics of social and economic networks, and behavioral models in financial markets.