The field of artificial intelligence (AI) has made tremendous advances in the last two decades, but as smart as AI is now, it is getting smarter and becoming more autonomous. This raises a host of challenges to current legal doctrine, including whether AI/algorithms should count as ‘speech’, whether AI should be regulated under antitrust and criminal law statutes, and whether AI should be considered as an agent under agency law or be held responsible for injuries under tort law. This book contains chapters from US and international law scholars on the role of law in an age of increasingly smart AI, addressing these and other issues that are critical to the evolution of the field.
Featuring state-of-the-art research from leading academics in technology and organization studies, this timely Research Handbook provides a comprehensive overview of how AI becomes embedded in decision making in organizations, from the initial considerations when implementing AI to the use of such solutions in strategic decision making.
The technology and application of artificial intelligence (AI) throughout society continues to grow at unprecedented rates, which raises numerous legal questions that to date have been largely unexamined. Although AI now plays a role in almost all areas of society, the need for a better understanding of its impact, from legal and ethical perspectives, is pressing, and regulatory proposals are urgently needed. This book responds to these needs, identifying the issues raised by AI and providing practical recommendations for regulatory, technical, and theoretical frameworks aimed at making AI compatible with existing legal rules, principles, and democratic values. An international roster of authors including professors of specialized areas of law, technologists, and practitioners bring their expertise to the interdisciplinary nature of AI.
Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students.
To date, a plethora of companies and organizations are investing vast amounts of money on the latest technologies. Information technology can be used to improve market share, profits, sales, competitive advantage, and customer/employee satisfaction. Unfortunately, the individuals meant to use these technologies are not well equipped on how to effectively and efficiently use these tools for competitive advantage and decision making. The Handbook of Research on IT Applications for Strategic Competitive Advantage and Decision Making is a collection of innovative research relevant to the methodologies, theoretical frameworks, and latest empirical research findings in information technology applications, strategic competitive advantage, and decision making. While highlighting topics including agility, knowledge management, and business intelligence, this book is ideally designed for information technology professionals, academics, researchers, managers, executives, and government officials interested in using information technology for strategic competitive advantage and better decision making.
The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.
This book presents innovative theories, methodologies, and techniques in the field of risk management and decision making. It introduces new research developments and provides a comprehensive image of their potential applications to readers interested in the area. The collection includes: computational intelligence applications in decision making, multi-criteria decision making under risk, risk modelling,forecasting and evaluation, public security and community safety, risk management in supply chain and other business decision making, political risk management and disaster response systems. The book is directed to academic and applied researchers working on risk management, decision making, and management information systems.
Consumer needs and demands are constantly changing. Because of this, marketing science and finance have their own concepts and theoretical backgrounds for evaluating consumer-related challenges. However, examining the function of finance with a marketing discipline can help to better understand internal management processes and compete in today’s market. The Handbook of Research on Decision-Making Techniques in Financial Marketing is a collection of innovative research that integrates financial and marketing functions to make better sense of the workplace environment and business-related challenges. Different financial challenges are taken into consideration while many of them are based on marketing theories such as agency theory, product life cycle, and optimal consumer experience. While highlighting topics including behavioral financing, corporate ethics, and Islamic banking, this book is ideally designed for financiers, marketers, financial analysts, marketing strategists, researchers, policymakers, government officials, academicians, students, and industry professionals.
The Oxford Handbook of Decision-Making comprehensively surveys theory and research on organizational decision-making, broadly conceived. Emphasizing psychological perspectives, while encompassing the insights of economics, political science, and sociology, it provides coverage at theindividual, group, organizational, and inter-organizational levels of analysis. In-depth case studies illustrate the practical implications of the work surveyed.Each chapter is authored by one or more leading scholars, thus ensuring that this Handbook is an authoritative reference work for academics, researchers, advanced students, and reflective practitioners concerned with decision-making in the areas of Management, Psychology, and HRM.Contributors: Eric Abrahamson, Julia Balogun, Michael L Barnett, Philippe Baumard, Nicole Bourque, Laure Cabantous, Prithviraj Chattopadhyay, Kevin Daniels, Jerker Denrell, Vinit M Desai, Giovanni Dosi, Roger L M Dunbar, Stephen M Fiore, Mark A Fuller, Michael Shayne Gary, Elizabeth George,Jean-Pascal Gond, Paul Goodwin, Terri L Griffith, Mark P Healey, Gerard P Hodgkinson, Gerry Johnson, Michael E Johnson-Cramer, Alfred Kieser, Ann Langley, Eleanor T Lewis, Dan Lovallo, Rebecca Lyons, Peter M Madsen, A. John Maule, John M Mezias, Nigel Nicholson, Gregory B Northcraft, David Oliver,Annie Pye, Karlene H Roberts, Jacques Rojot, Michael A Rosen, Isabelle Royer, Eugene Sadler-Smith, Eduardo Salas, Kristyn A Scott, Zur Shapira, Carolyne Smart, Gerald F Smith, Emma Soane, Paul R Sparrow, William H Starbuck, Matt Statler, Kathleen M Sutcliffe, Michal Tamuz , Teri JaneUrsacki-Bryant, Ilan Vertinsky, Benedicte Vidaillet, Jane Webster, Karl E Weick, Benjamin Wellstein, George Wright, Kuo Frank Yu, and David Zweig.
With the emergence of smart technology and automated systems in today’s world, artificial intelligence (AI) is being incorporated into an array of professions. The aviation and aerospace industry, specifically, is a field that has seen the successful implementation of early stages of automation in daily flight operations through flight management systems and autopilot. However, the effectiveness of aviation systems and the provision of flight safety still depend primarily upon the reliability of aviation specialists and human decision making. The Handbook of Research on Artificial Intelligence Applications in the Aviation and Aerospace Industries is a pivotal reference source that explores best practices for AI implementation in aviation to enhance security and the ability to learn, improve, and predict. While highlighting topics such as computer-aided design, automated systems, and human factors, this publication explores the enhancement of global aviation security as well as the methods of modern information systems in the aeronautics industry. This book is ideally designed for pilots, scientists, engineers, aviation operators, air crash investigators, teachers, academicians, researchers, and students seeking current research on the application of AI in the field of aviation.
