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Artificial Intelligence In Economics And Managment
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Book Synopsis The Economics of Artificial Intelligence by : Ajay Agrawal
Download or read book The Economics of Artificial Intelligence written by Ajay Agrawal and published by University of Chicago Press. This book was released on 2024-03-05 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
Book Synopsis Economics and Law of Artificial Intelligence by : Georgios I. Zekos
Download or read book Economics and Law of Artificial Intelligence written by Georgios I. Zekos and published by Springer Nature. This book was released on 2021-01-11 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive analysis of the alterations and problems caused by new technologies in all fields of the global digital economy. The impact of artificial intelligence (AI) not only on law but also on economics is examined. In the first part, the economics of AI are explored, including topics such as e-globalization and digital economy, corporate governance, risk management, and risk development, followed by a quantitative econometric analysis which utilizes regressions stipulating the scale of the impact. In the second part, the author presents the law of AI, covering topics such as the law of electronic technology, legal issues, AI and intellectual property rights, and legalizing AI. Case studies from different countries are presented, as well as a specific analysis of international law and common law. This book is a must-read for scholars and students of law, economics, and business, as well as policy-makers and practitioners, interested in a better understanding of legal and economic aspects and issues of AI and how to deal with them.
Book Synopsis Artificial Intelligence in Economics and Management by : International Federation of Automatic Control
Download or read book Artificial Intelligence in Economics and Management written by International Federation of Automatic Control and published by North Holland. This book was released on 1986 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence in Economics and Finance Theories by : Tankiso Moloi
Download or read book Artificial Intelligence in Economics and Finance Theories written by Tankiso Moloi and published by Springer Nature. This book was released on 2020-05-07 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: As Artificial Intelligence (AI) seizes all aspects of human life, there is a fundamental shift in the way in which humans are thinking of and doing things. Ordinarily, humans have relied on economics and finance theories to make sense of, and predict concepts such as comparative advantage, long run economic growth, lack or distortion of information and failures, role of labour as a factor of production and the decision making process for the purpose of allocating resources among other theories. Of interest though is that literature has not attempted to utilize these advances in technology in order to modernize economic and finance theories that are fundamental in the decision making process for the purpose of allocating scarce resources among other things. With the simulated intelligence in machines, which allows machines to act like humans and to some extent even anticipate events better than humans, thanks to their ability to handle massive data sets, this book will use artificial intelligence to explain what these economic and finance theories mean in the context of the agent wanting to make a decision. The main feature of finance and economic theories is that they try to eliminate the effects of uncertainties by attempting to bring the future to the present. The fundamentals of this statement is deeply rooted in risk and risk management. In behavioural sciences, economics as a discipline has always provided a well-established foundation for understanding uncertainties and what this means for decision making. Finance and economics have done this through different models which attempt to predict the future. On its part, risk management attempts to hedge or mitigate these uncertainties in order for “the planner” to reach the favourable outcome. This book focuses on how AI is to redefine certain important economic and financial theories that are specifically used for the purpose of eliminating uncertainties so as to allow agents to make informed decisions. In effect, certain aspects of finance and economic theories cannot be understood in their entirety without the incorporation of AI.
Book Synopsis Artificial Intelligence in Economics and Managment by : Phillip Ein-Dor
Download or read book Artificial Intelligence in Economics and Managment written by Phillip Ein-Dor and published by Springer Science & Business Media. This book was released on 1996-08-31 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past decades several researchers have developed statistical models for the prediction of corporate bankruptcy, e. g. Altman (1968) and Bilderbeek (1983). A model for predicting corporate bankruptcy aims to describe the relation between bankruptcy and a number of explanatory financial ratios. These ratios can be calculated from the information contained in a company's annual report. The is to obtain a method for timely prediction of bankruptcy, a so ultimate purpose called "early warning" system. More recently, this subject has attracted the attention of researchers in the area of machine learning, e. g. Shaw and Gentry (1990), Fletcher and Goss (1993), and Tam and Kiang (1992). This research is usually directed at the comparison of machine learning methods, such as induction of classification trees and neural networks, with the "standard" statistical methods of linear discriminant analysis and logistic regression. In earlier research, Feelders et al. (1994) performed a similar comparative analysis. The methods used were linear discriminant analysis, decision trees and neural networks. We used a data set which contained 139 annual reports of Dutch industrial and trading companies. The experiments showed that the estimated prediction error of both the decision tree and neural network were below the estimated error of the linear discriminant. Thus it seems that we can gain by replacing the "traditionally" used linear discriminant by a more flexible classification method to predict corporate bankruptcy. The data set used in these experiments was very small however.
Author :International Workshop on Artificial Intelligence in Economics and Management Publisher : ISBN 13 : Total Pages :292 pages Book Rating :4.:/5 (471 download)
Book Synopsis Artificial Intelligence in Economics and Management by : International Workshop on Artificial Intelligence in Economics and Management
Download or read book Artificial Intelligence in Economics and Management written by International Workshop on Artificial Intelligence in Economics and Management and published by . This book was released on 1986 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence in Financial Markets by : Christian L. Dunis
Download or read book Artificial Intelligence in Financial Markets written by Christian L. Dunis and published by Springer. This book was released on 2016-11-21 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
Book Synopsis The Economics of Artificial Intelligence by : Ajay Agrawal
Download or read book The Economics of Artificial Intelligence written by Ajay Agrawal and published by University of Chicago Press. This book was released on 2019-05-22 with total page 643 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in artificial intelligence (AI) highlight the potential of this technology to affect productivity, growth, inequality, market power, innovation, and employment. This volume seeks to set the agenda for economic research on the impact of AI. It covers four broad themes: AI as a general purpose technology; the relationships between AI, growth, jobs, and inequality; regulatory responses to changes brought on by AI; and the effects of AI on the way economic research is conducted. It explores the economic influence of machine learning, the branch of computational statistics that has driven much of the recent excitement around AI, as well as the economic impact of robotics and automation and the potential economic consequences of a still-hypothetical artificial general intelligence. The volume provides frameworks for understanding the economic impact of AI and identifies a number of open research questions. Contributors: Daron Acemoglu, Massachusetts Institute of Technology Philippe Aghion, Collège de France Ajay Agrawal, University of Toronto Susan Athey, Stanford University James Bessen, Boston University School of Law Erik Brynjolfsson, MIT Sloan School of Management Colin F. Camerer, California Institute of Technology Judith Chevalier, Yale School of Management Iain M. Cockburn, Boston University Tyler Cowen, George Mason University Jason Furman, Harvard Kennedy School Patrick Francois, University of British Columbia Alberto Galasso, University of Toronto Joshua Gans, University of Toronto Avi Goldfarb, University of Toronto Austan Goolsbee, University of Chicago Booth School of Business Rebecca Henderson, Harvard Business School Ginger Zhe Jin, University of Maryland Benjamin F. Jones, Northwestern University Charles I. Jones, Stanford University Daniel Kahneman, Princeton University Anton Korinek, Johns Hopkins University Mara Lederman, University of Toronto Hong Luo, Harvard Business School John McHale, National University of Ireland Paul R. Milgrom, Stanford University Matthew Mitchell, University of Toronto Alexander Oettl, Georgia Institute of Technology Andrea Prat, Columbia Business School Manav Raj, New York University Pascual Restrepo, Boston University Daniel Rock, MIT Sloan School of Management Jeffrey D. Sachs, Columbia University Robert Seamans, New York University Scott Stern, MIT Sloan School of Management Betsey Stevenson, University of Michigan Joseph E. Stiglitz. Columbia University Chad Syverson, University of Chicago Booth School of Business Matt Taddy, University of Chicago Booth School of Business Steven Tadelis, University of California, Berkeley Manuel Trajtenberg, Tel Aviv University Daniel Trefler, University of Toronto Catherine Tucker, MIT Sloan School of Management Hal Varian, University of California, Berkeley
Book Synopsis Machine Learning and Artificial Intelligence for Agricultural Economics by : Chandrasekar Vuppalapati
Download or read book Machine Learning and Artificial Intelligence for Agricultural Economics written by Chandrasekar Vuppalapati and published by Springer Nature. This book was released on 2021-10-04 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses machine learning and artificial intelligence (AI) for agricultural economics. It is written with a view towards bringing the benefits of advanced analytics and prognostics capabilities to small scale farmers worldwide. This volume provides data science and software engineering teams with the skills and tools to fully utilize economic models to develop the software capabilities necessary for creating lifesaving applications. The book introduces essential agricultural economic concepts from the perspective of full-scale software development with the emphasis on creating niche blue ocean products. Chapters detail several agricultural economic and AI reference architectures with a focus on data integration, algorithm development, regression, prognostics model development and mathematical optimization. Upgrading traditional AI software development paradigms to function in dynamic agricultural and economic markets, this volume will be of great use to researchers and students in agricultural economics, data science, engineering, and machine learning as well as engineers and industry professionals in the public and private sectors.
Book Synopsis Handbook of Research on Applied AI for International Business and Marketing Applications by : Christiansen, Bryan
Download or read book Handbook of Research on Applied AI for International Business and Marketing Applications written by Christiansen, Bryan and published by IGI Global. This book was released on 2020-09-25 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Artificial Intelligence in Economics and Management by : P Ein-Dor
Download or read book Artificial Intelligence in Economics and Management written by P Ein-Dor and published by Pergamon. This book was released on 1996-01-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence by : Wim Naudé
Download or read book Artificial Intelligence written by Wim Naudé and published by Cambridge University Press. This book was released on 2024-05-31 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides essential economic tools to think about the impact of Artificial Intelligence on society, both over the short-and long term.
Book Synopsis The Feeling Economy by : Roland T. Rust
Download or read book The Feeling Economy written by Roland T. Rust and published by Springer Nature. This book was released on 2021-01-19 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: As machines are trained to “think,” many tasks that previously required human intelligence are becoming automated through artificial intelligence. However, it is more difficult to automate emotional intelligence, and this is where the human worker’s competitive advantage over machines currently lies. This book explores the impact of AI on everyday life, looking into workers’ adaptation to these changes, the ways in which managers can change the nature of jobs in light of AI developments, and the potential for humans and AI to continue working together. The book argues that AI is rapidly assuming a larger share of thinking tasks, leaving human intelligence to focus on feeling. The result is the “Feeling Economy,” in which both employees and consumers emphasize feeling to an unprecedented extent, with thinking tasks largely delegated to AI. The book shows both theoretical and empirical evidence that this shift is well underway. Further, it explores the effect of the Feeling Economy on our everyday lives in the areas such as shopping, politics, and education. Specifically, it argues that in this new economy, through empathy and people skills, women may gain an unprecedented degree of power and influence. This book will appeal to readers across disciplines interested in understanding the impact of AI on business and our daily lives. It represents a bold, potentially controversial attempt to gauge the direction in which society is heading.
Book Synopsis Economic and Policy Implications of Artificial Intelligence by : Domenico Marino
Download or read book Economic and Policy Implications of Artificial Intelligence written by Domenico Marino and published by Springer Nature. This book was released on 2020-05-20 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents original research articles addressing various aspects of artificial intelligence as applied to economics, law, management and optimization. The topics discussed include economics, policies, finance, law, resource allocation strategies and information technology. Combining the input of contributing professors and researchers from Italian and international universities, the book will be of interest to students, researchers and practitioners, as well as members of the general public interested in the economic and policy implications of artificial intelligence.
Book Synopsis Transforming Management with AI, Big-Data, and IoT by : Fadi Al-Turjman
Download or read book Transforming Management with AI, Big-Data, and IoT written by Fadi Al-Turjman and published by Springer Nature. This book was released on 2022-02-17 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the effect that artificial intelligence (AI) and Internet of Things (IoT) have on industry. The authors start by showing how the application of these technologies has already stretched across domains such as law, political science, policy, and economics and how it will soon permeate areas of autonomous transportation, education, and space exploration, only to name a few. The authors then discuss applications in a variety of industries. Throughout the volume, the authors provide detailed, well-illustrated treatments of each topic with abundant examples and exercises. This book provides relevant theoretical frameworks and the latest empirical research findings in various applications. The book is written for professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society, that is, trust at the level of the global economy, of networks and organizations, of teams and work groups, of information systems and, finally, trust at the level of individuals as actors in the networked environments. Presents research in various industries and how artificial intelligence and Internet of Things is changing the landscape of business and management; Includes new and innovative features in artificial intelligence and IoT that can help in raising economic efficiency at both micro and macro levels; Examines case studies with tried and tested approaches to resolution of typical problems in each application of study.
Book Synopsis Artificial Intelligence and Machine Learning in Business Management by : Sandeep Kumar Panda
Download or read book Artificial Intelligence and Machine Learning in Business Management written by Sandeep Kumar Panda and published by CRC Press. This book was released on 2021-11-04 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence and Machine Learning in Business Management The focus of this book is to introduce artificial intelligence (AI) and machine learning (ML) technologies into the context of business management. The book gives insights into the implementation and impact of AI and ML to business leaders, managers, technology developers, and implementers. With the maturing use of AI or ML in the field of business intelligence, this book examines several projects with innovative uses of AI beyond data organization and access. It follows the Predictive Modeling Toolkit for providing new insight on how to use improved AI tools in the field of business. It explores cultural heritage values and risk assessments for mitigation and conservation and discusses on-shore and off-shore technological capabilities with spatial tools for addressing marketing and retail strategies, and insurance and healthcare systems. Taking a multidisciplinary approach for using AI, this book provides a single comprehensive reference resource for undergraduate, graduate, business professionals, and related disciplines.
Book Synopsis Data Science for Economics and Finance by : Sergio Consoli
Download or read book Data Science for Economics and Finance written by Sergio Consoli and published by Springer Nature. This book was released on 2021 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
