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artificial intelligence in the field of economics: The Economics of Artificial Intelligence Ajay Agrawal, Joshua Gans, Avi Goldfarb, Catherine Tucker, 2024-03-05 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. |
artificial intelligence in the field of economics: Artificial Intelligence in Economics and Finance Theories Tankiso Moloi, Tshilidzi Marwala, 2020-05-07 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. |
artificial intelligence in the field of economics: Artificial Intelligence and Economic Analysis Scott J. Moss, John Rae, 1992-01-01 This important book presents new and original work at the frontiers of economics, namely the interface between artificial intelligence (AI) and neoclassical economics. Artificial Intelligence and Economic Analysis focuses on three quite distinct lines of AI orientated research in economics: applications intended to extend neoclassical theory, applications intended to undermine neoclassical theory and applications which ignore neoclassical theory in the quest for new modelling techniques and fields of analysis. The contributors - all of whom are well established in the field - do not simply report established results but seek to identify those areas where the science of artificial intelligence could enrich standard economic analysis. It includes material from mainstream economists who are willing to express their own views about the limits of mainstream economic modelling and AI based economic modelling. The book makes an important contribution to a new and exciting area of economics which holds much hope for the future. |
artificial intelligence in the field of economics: The AI Economy Roger Bootle, 2019-11-26 Gold winner in Business Technology category, 2020 Axiom Business Book Awards Extraordinary innovations in technology promise to transform the world, but how realistic is the claim that AI will change our lives? In this much needed book the acclaimed economist Roger Bootle responds to the fascinating economic questions posed by the age of the robot, steering a path away from tech jargon and alarmism towards a rational explanation of the ways in which the AI revolution will affect us all. Tackling the implications of Artificial Intelligence on growth, productivity, inflation and the distribution of wealth and power, THE AI ECONOMY also examines coming changes to the the way we educate, work and spend our leisure time. A fundamentally optimistic view which will help you plan for changing times, this book explains AI and leads you towards a more certain future. Extraordinary innovations in technology promise to transform the world, but how realistic is the claim that AI will change our lives? In this much needed book the acclaimed economist Roger Bootle responds to the fascinating economic questions posed by the age of the robot, steering a path away from tech jargon and alarmism towards a rational explanation of the ways in which the AI revolution will affect us all. Tackling the implications of Artificial Intelligence on growth, productivity, inflation and the distribution of wealth and power, THE AI ECONOMY also examines coming changes to the the way we educate, work and spend our leisure time. A fundamentally optimistic view which will help you plan for changing times, this book explains AI and leads you towards a more certain future. |
artificial intelligence in the field of economics: Economics and Law of Artificial Intelligence Georgios I. Zekos, 2021-01-11 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. |
artificial intelligence in the field of economics: Artificial Intelligence in Society OECD, 2019-06-11 The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises. |
artificial intelligence in the field of economics: Artificial Economics Ruben Mercado, 2021-11-04 An introductory overview of the methods, models and interdisciplinary links of artificial economics. Addresses the differences between the assumptions and methods of artificial economics and those of mainstream economics. This is one of the first books to fully address, in an intuitive and conceptual form, this new way of doing economics. |
artificial intelligence in the field of economics: Artificial Intelligence and Economic Theory: Skynet in the Market Tshilidzi Marwala, Evan Hurwitz, 2017-09-18 This book theoretically and practically updates major economic ideas such as demand and supply, rational choice and expectations, bounded rationality, behavioral economics, information asymmetry, pricing, efficient market hypothesis, game theory, mechanism design, portfolio theory, causality and financial engineering in the age of significant advances in man-machine systems. The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence concepts such as the swarming of birds, the working of the brain and the pathfinding of the ants. Artificial Intelligence and Economic Theory: Skynet in the Market analyses the impact of artificial intelligence on economic theories, a subject that has not been studied. It also introduces new economic theories and these are rational counterfactuals and rational opportunity costs. These ideas are applied to diverse areas such as modelling of the stock market, credit scoring, HIV and interstate conflict. Artificial intelligence ideas used in this book include neural networks, particle swarm optimization, simulated annealing, fuzzy logic and genetic algorithms. It, furthermore, explores ideas in causality including Granger as well as the Pearl causality models. |
artificial intelligence in the field of economics: Artificial Intelligence and International Economic Law Shin-yi Peng, Ching-Fu Lin, Thomas Streinz, 2021-10-14 Artificial intelligence (AI) technologies are transforming economies, societies, and geopolitics. Enabled by the exponential increase of data that is collected, transmitted, and processed transnationally, these changes have important implications for international economic law (IEL). This volume examines the dynamic interplay between AI and IEL by addressing an array of critical new questions, including: How to conceptualize, categorize, and analyze AI for purposes of IEL? How is AI affecting established concepts and rubrics of IEL? Is there a need to reconfigure IEL, and if so, how? Contributors also respond to other cross-cutting issues, including digital inequality, data protection, algorithms and ethics, the regulation of AI-use cases (autonomous vehicles), and systemic shifts in e-commerce (digital trade) and industrial production (fourth industrial revolution). This title is also available as Open Access on Cambridge Core. |
artificial intelligence in the field of economics: The Feeling Economy Roland T. Rust, Ming-Hui Huang, 2021-01-19 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. |
artificial intelligence in the field of economics: Economic Modeling Using Artificial Intelligence Methods Tshilidzi Marwala, 2013-04-02 Economic Modeling Using Artificial Intelligence Methods examines the application of artificial intelligence methods to model economic data. Traditionally, economic modeling has been modeled in the linear domain where the principles of superposition are valid. The application of artificial intelligence for economic modeling allows for a flexible multi-order non-linear modeling. In addition, game theory has largely been applied in economic modeling. However, the inherent limitation of game theory when dealing with many player games encourages the use of multi-agent systems for modeling economic phenomena. The artificial intelligence techniques used to model economic data include: multi-layer perceptron neural networks radial basis functions support vector machines rough sets genetic algorithm particle swarm optimization simulated annealing multi-agent system incremental learning fuzzy networks Signal processing techniques are explored to analyze economic data, and these techniques are the time domain methods, time-frequency domain methods and fractals dimension approaches. Interesting economic problems such as causality versus correlation, simulating the stock market, modeling and controling inflation, option pricing, modeling economic growth as well as portfolio optimization are examined. The relationship between economic dependency and interstate conflict is explored, and knowledge on how economics is useful to foster peace – and vice versa – is investigated. Economic Modeling Using Artificial Intelligence Methods deals with the issue of causality in the non-linear domain and applies the automatic relevance determination, the evidence framework, Bayesian approach and Granger causality to understand causality and correlation. Economic Modeling Using Artificial Intelligence Methods makes an important contribution to the area of econometrics, and is a valuable source of reference for graduate students, researchers and financial practitioners. |
artificial intelligence in the field of economics: Artificial Intelligence in Financial Markets Christian L. Dunis, Peter W. Middleton, Andreas Karathanasopolous, Konstantinos Theofilatos, 2016-11-21 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. |
artificial intelligence in the field of economics: Machine Learning and Artificial Intelligence for Agricultural Economics Chandrasekar Vuppalapati, 2021-10-04 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. |
artificial intelligence in the field of economics: Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance El Bachir Boukherouaa, Mr. Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S Iskender, Mr. Alin T Mirestean, Rangachary Ravikumar, 2021-10-22 This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight. |
artificial intelligence in the field of economics: Artificial Intelligence as a Disruptive Technology Rosario Girasa, 2020-01-11 Artificial intelligence (AI) is the latest technological evolution which is transforming the global economy and is a major part of the “Fourth Industrial Revolution.” This book covers the meaning, types, subfields and applications of AI, including U.S. governmental policies and regulations, ethical and privacy issues, particularly as they pertain and affect facial recognition programs and the Internet-of Things (IoT). There is a lengthy analysis of bias, AI’s effect on the current and future job market, and how AI precipitated fake news. In addition, the text covers basics of intellectual property rights and how AI will transform their protection. The author then moves on to explore international initiatives from the European Union, China’s New Generation Development Plan, other regional areas, and international conventions. The book concludes with a discussion of super intelligence and the question and applicability of consciousness in machines. The interdisciplinary scope of the text will appeal to any scholars, students and general readers interested in the effects of AI on our society, particularly in the fields of STS, economics, law and politics. |
artificial intelligence in the field of economics: Artificial Intelligence Jacob Parakilas, Hannah Bryce, Kenneth Cukier, Heather Roff, Missy Cummings, 2018 The rise of AI must be better managed in the near term in order to mitigate longer term risks and to ensure that AI does not reinforce existing inequalities--Publisher. |
artificial intelligence in the field of economics: Handbook of Research on Applied AI for International Business and Marketing Applications Christiansen, Bryan, Škrinjari?, Tihana, 2020-09-25 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. |
artificial intelligence in the field of economics: Information Technology and the U.S. Workforce National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on Information Technology, Automation, and the U.S. Workforce, 2017-04-18 Recent years have yielded significant advances in computing and communication technologies, with profound impacts on society. Technology is transforming the way we work, play, and interact with others. From these technological capabilities, new industries, organizational forms, and business models are emerging. Technological advances can create enormous economic and other benefits, but can also lead to significant changes for workers. IT and automation can change the way work is conducted, by augmenting or replacing workers in specific tasks. This can shift the demand for some types of human labor, eliminating some jobs and creating new ones. Information Technology and the U.S. Workforce explores the interactions between technological, economic, and societal trends and identifies possible near-term developments for work. This report emphasizes the need to understand and track these trends and develop strategies to inform, prepare for, and respond to changes in the labor market. It offers evaluations of what is known, notes open questions to be addressed, and identifies promising research pathways moving forward. |
artificial intelligence in the field of economics: Redesigning AI Daron Acemoglu, 2021-05-25 A look at how new technologies can be put to use in the creation of a more just society. Artificial Intelligence (AI) is not likely to make humans redundant. Nor will it create superintelligence anytime soon. But it will make huge advances in the next two decades, revolutionize medicine, entertainment, and transport, transform jobs and markets, and vastly increase the amount of information that governments and companies have about individuals. AI for Good leads off with economist and best-selling author Daron Acemoglu, who argues that there are reasons to be concerned about these developments. AI research today pays too much attention to the technological hurtles ahead without enough attention to its disruptive effects on the fabric of society: displacing workers while failing to create new opportunities for them and threatening to undermine democratic governance itself. But the direction of AI development is not preordained. Acemoglu argues for its potential to create shared prosperity and bolster democratic freedoms. But directing it to that task will take great effort: It will require new funding and regulation, new norms and priorities for developers themselves, and regulations over new technologies and their applications. At the intersection of technology and economic justice, this book will bring together experts--economists, legal scholars, policy makers, and developers--to debate these challenges and consider what steps tech companies can do take to ensure the advancement of AI does not further diminish economic prospects of the most vulnerable groups of population. |
artificial intelligence in the field of economics: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
artificial intelligence in the field of economics: Understanding Artificial Intelligence Ralf T. Kreutzer, Marie Sirrenberg, 2019-09-25 Artificial Intelligence (AI) will change the lives of people and businesses more fundamentally than many people can even imagine today. This book illustrates the importance of AI in an era of digitalization. It introduces the foundations of AI and explains its benefits and challenges for companies and entire industries. In this regard, AI is approached not just as yet another technology, but as a fundamental innovation, which will spread into all areas of the economy and life, and will disrupt business processes and business models in the years to come. In turn, the book assesses the potential that AI holds, and clarifies the framework that is necessary for pursuing a responsible approach to AI. In a series of best-practice cases, the book subsequently highlights a broad range of sectors and industries, from production to services; from customer service to marketing and sales; and in industries like retail, health care, energy, transportation and many more. In closing, a dedicated chapter outlines a roadmap for a specific corporate AI journey. No one can ignore intensive work with AI today - neither as a private person, let alone as a top performer in companies. This book offers a thorough, carefully crafted, and easy to understand entry into the field of AI. The central terms used in the AI context are given a very good explanation. In addition, a number of cases show what AI can do today and where the journey is heading. An important book that you should not miss! Professor Dr. Harley Krohmer University of Bern Inspiring, thought provoking and comprehensive, this book is wittingly designed to be a catalyst for your individual and corporate AI journey.” Avo Schönbohm, Professor at the Berlin School of Economics and Law, Enterprise Game Designer at LUDEO and Business Punk |
artificial intelligence in the field of economics: The Butterfly Defect Ian Goldin, Mike Mariathasan, 2015-10-20 How to better manage systemic risks—from cyber attacks and pandemics to financial crises and climate change—in a globalized world The Butterfly Defect addresses the widening gap between the new systemic risks generated by globalization and their effective management. It shows how the dynamics of turbo-charged globalization has the potential and power to destabilize our societies. Drawing on the latest insights from a wide variety of disciplines, Ian Goldin and Mike Mariathasan provide practical guidance for how governments, businesses, and individuals can better manage globalization and risk. Goldin and Mariathasan demonstrate that systemic risk issues are now endemic everywhere—in supply chains, pandemics, infrastructure, ecology and climate change, economics, and politics. Unless we address these concerns, they will lead to greater protectionism, xenophobia, nationalism, and, inevitably, deglobalization, rising inequality, conflict, and slower growth. The Butterfly Defect shows that mitigating uncertainty and risk in an interconnected world is an essential task for our future. |
artificial intelligence in the field of economics: Artificial Intelligence Harvard Business Review, 2019 Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business. |
artificial intelligence in the field of economics: Towards an International Political Economy of Artificial Intelligence Tugrul Keskin, Ryan David Kiggins, 2022-07-16 This volume seeks to leverage academic interdisciplinarity to develop insight into how Artificial intelligence (AI), the latest GPT to emerge, may influence or radically change socio-political norms, practices, and institutions. AI may best be understood as a predictive technology. “Prediction is the process of filling in missing information. Prediction takes information you have, often called ‘data’, and uses it to generate information you don’t have” (Agrawal, Gans, and Goldfarb 2018, 13; also see Mayer-Schonberger and Ramge 2018). AI makes prediction cheap because the cost of information is now close to zero. Cheap prediction through AI technologies are radically altering how we govern ourselves, interact with each other, and sustain society. Contributors to this volume represent the academic disciplines of Sociology and Political Science working within a diverse set of intra-disciplinary fields that when combined, yield novel insights into the following questions guiding this volume: How might AI transform people? How might AI transform socio-political practices? How might AI transform socio-political institutions? |
artificial intelligence in the field of economics: Building the New Economy Alex Pentland, Alexander Lipton, Thomas Hardjono, 2021-10-12 How to empower people and communities with user-centric data ownership, transparent and accountable algorithms, and secure digital transaction systems. Data is now central to the economy, government, and health systems—so why are data and the AI systems that interpret the data in the hands of so few people? Building the New Economy calls for us to reinvent the ways that data and artificial intelligence are used in civic and government systems. Arguing that we need to think about data as a new type of capital, the authors show that the use of data trusts and distributed ledgers can empower people and communities with user-centric data ownership, transparent and accountable algorithms, machine learning fairness principles and methodologies, and secure digital transaction systems. It’s well known that social media generate disinformation and that mobile phone tracking apps threaten privacy. But these same technologies may also enable the creation of more agile systems in which power and decision-making are distributed among stakeholders rather than concentrated in a few hands. Offering both big ideas and detailed blueprints, the authors describe such key building blocks as data cooperatives, tokenized funding mechanisms, and tradecoin architecture. They also discuss technical issues, including how to build an ecosystem of trusted data, the implementation of digital currencies, and interoperability, and consider the evolution of computational law systems. |
artificial intelligence in the field of economics: Narrative Economics Robert J. Shiller, 2020-09-01 From Nobel Prize–winning economist and New York Times bestselling author Robert Shiller, a groundbreaking account of how stories help drive economic events—and why financial panics can spread like epidemic viruses Stories people tell—about financial confidence or panic, housing booms, or Bitcoin—can go viral and powerfully affect economies, but such narratives have traditionally been ignored in economics and finance because they seem anecdotal and unscientific. In this groundbreaking book, Robert Shiller explains why we ignore these stories at our peril—and how we can begin to take them seriously. Using a rich array of examples and data, Shiller argues that studying popular stories that influence individual and collective economic behavior—what he calls narrative economics—may vastly improve our ability to predict, prepare for, and lessen the damage of financial crises and other major economic events. The result is nothing less than a new way to think about the economy, economic change, and economics. In a new preface, Shiller reflects on some of the challenges facing narrative economics, discusses the connection between disease epidemics and economic epidemics, and suggests why epidemiology may hold lessons for fighting economic contagions. |
artificial intelligence in the field of economics: AI and Financial Markets Shigeyuki Hamori, Tetsuya Takiguchi, 2020-07-01 Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets. |
artificial intelligence in the field of economics: The Economic Singularity Calum Chace, 2016-07-18 Read The Economic Singularity if you want to think intelligently about the future. Aubrey de Grey Artificial intelligence (AI) is overtaking our human ability to absorb and process information. Robots are becoming increasingly dextrous, flexible, and safe to be around (except the military ones). It is our most powerful technology, and you need to understand it. This new book from best-selling AI writer Calum Chace argues that within a few decades, most humans will not be able to work for money. Self-driving cars will probably be the canary in the coal mine, providing a wake-up call for everyone who isn't yet paying attention. All jobs will be affected, from fast food McJobs to lawyers and journalists. This is the single most important development facing humanity in the first half of the 21st century. The fashionable belief that Universal Basic Income is the solution is only partly correct. We are probably going to need an entirely new economic system, and we better start planning soon - for the Economic Singularity! The outcome can be very good - a world in which machines do all the boring jobs and humans do pretty much what they please. But there are major risks, which we can only avoid by being alert to the possible futures and planning how to avoid the negative ones. |
artificial intelligence in the field of economics: Machine Learning for Economics and Finance in TensorFlow 2 Isaiah Hull, 2020-11-26 Work on economic problems and solutions with tools from machine learning. ML has taken time to move into the space of academic economics. This is because empirical work in economics is concentrated on the identification of causal relationships in parsimonious statistical models; whereas machine learning is oriented towards prediction and is generally uninterested in either causality or parsimony. That leaves a gap for both students and professionals in the economics industry without a standard reference. This book focuses on economic problems with an empirical dimension, where machine learning methods may offer something of value. This includes coverage of a variety of discriminative deep learning models (DNNs, CNNs, RNNs, LSTMs, the Transformer Model, etc.), generative machine learning models, random forests, gradient boosting, clustering, and feature extraction. You'll also learn about the intersection of empirical methods in economics and machine learning, including regression analysis, text analysis, and dimensionality reduction methods, such as principal components analysis. TensorFlow offers a toolset that can be used to setup and solve any mathematical model, including those commonly used in economics. This book is structured to teach through a sequence of complete examples, each framed in terms of a specific economic problem of interest or topic. Otherwise complicated content is then distilled into accessible examples, so you can use TensorFlow to solve workhorse models in economics and finance. What You'll Learn Define, train, and evaluate machine learning models in TensorFlow 2 Apply fundamental concepts in machine learning, such as deep learning and natural language processing, to economic and financial problems Solve workhorse models in economics and finance Who This Book Is For Students and data scientists working in the economics industry. Academic economists and social scientists who have an interest in machine learning are also likely to find this book useful. |
artificial intelligence in the field of economics: Introduction to Business Lawrence J. Gitman, Carl McDaniel, Amit Shah, Monique Reece, Linda Koffel, Bethann Talsma, James C. Hyatt, 2024-09-16 Introduction to Business covers the scope and sequence of most introductory business courses. The book provides detailed explanations in the context of core themes such as customer satisfaction, ethics, entrepreneurship, global business, and managing change. Introduction to Business includes hundreds of current business examples from a range of industries and geographic locations, which feature a variety of individuals. The outcome is a balanced approach to the theory and application of business concepts, with attention to the knowledge and skills necessary for student success in this course and beyond. This is an adaptation of Introduction to Business by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License. |
artificial intelligence in the field of economics: Essentials of Economics Paul Krugman, Paul R. Krugman, Robin Wells, Kathryn Graddy, 2010-10 Check out preview content for Essentials of Economics here. Essentials of Economics brings the same captivating writing and innovative features of Krugman/Wells to the one-term economics course. Adapted by Kathryn Graddy, it is the ideal text for teaching basic economic principles, with enough real-world applications to help students see the applicability, but not so much detail as to overwhelm them. Watch a video interview of Paul Krugman here. |
artificial intelligence in the field of economics: Artificial Intelligence for Business Ana Landeta Echeberria, 2022-01-22 This book seeks to build a shared understanding of Artificial Intelligence (AI) within the global business scenario today and in the near future. Drawing on academic theory and real-world case studies, it examines AI’s development and application across a number of business contexts. Taking current scholarship forward in its engagement with AI theory and practice for enterprises and applied research and innovation, it outlines international practices for the promotion of reliable AI systems, trends, research and development, fostering a digital ecosystem for AI and preparing companies for job transformation and building skills. This book will be of great interest to academics studying Digital Business, Digital Strategy, Innovation Management, and Information Technology. |
artificial intelligence in the field of economics: Unscaled Hemant Taneja, 2018-03-27 Unscaled identifies the forces that are reshaping the global economy and turning one of the fundamental laws of business and society -- the economies of scale -- on its head. An innovative trend combining technology with economics is unraveling behemoth industries -- including corporations, banks, farms, media conglomerates, energy systems, governments, and schools-that have long dominated business and society. Size and scale have become a liability. A new generation of upstarts is using artificial intelligence to automate tasks that once required expensive investment, and renting technology platforms to build businesses for hyper-focused markets, enabling them to grow big without the bloat of giant organizations. In Unscaled, venture capitalist Hemant Taneja explains how the unscaled phenomenon allowed Warby Parker to cheaply and easily start a small company, build a better product, and become a global competitor in no time, upending entrenched eyewear giant Luxottica. It similarly enabled Stripe to take on established payment processors throughout the world, and Livongo to help diabetics control their disease while simultaneously cutting the cost of treatment. The unscaled economy is remaking massive, deeply rooted industries and opening up fantastic possibilities for entrepreneurs, imaginative companies, and resourceful individuals. It can be the model for solving some of the world's greatest problems, including climate change and soaring health-care costs, but will also unleash new challenges that today's leaders must address. |
artificial intelligence in the field of economics: Robots, Artificial Intelligence and Service Automation in Travel, Tourism and Hospitality Stanislav Ivanov, Craig Webster, 2019-10-14 Using a combination of theoretical discussion and real-world case studies, this book focuses on current and future use of RAISA technologies in the tourism economy, including examples from the hotel, restaurant, travel agency, museum, and events industries. |
artificial intelligence in the field of economics: The AI Book Ivana Bartoletti, Anne Leslie, Shân M. Millie, 2020-06-29 Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important |
artificial intelligence in the field of economics: Scientific and Technical Revolution: Yesterday, Today and Tomorrow Elena G. Popkova, Bruno S. Sergi, 2020-06-05 This book presents a system view of the digital scientific and technological revolution, including its genesis and prerequisites, current trends, as well as current and potential issues and future prospects. It gathers selected research papers presented at the 12th International Scientific and Practical Conference, organized by the Institute of Scientific Communications. The conference “Artificial Intelligence: Anthropogenic Nature vs. Social Origin” took place on December 5–7, 2019 in Krasnoyarsk, Russia. The book is intended for academic researchers and independent experts studying the social and human aspects of the Fourth Industrial Revolution and the associated transition to the digital economy and Industry 4.0, as well as the creators of the legal framework for this process and its participants – entrepreneurs, managers, employees and consumers. It covers a variety of topics, including “intelligent” technologies and artificial intelligence, the digital economy, the social environment of the Fourth Industrial Revolution and its consequences for humans, the regulatory framework of the Fourth Industrial Revolution, and the “green” consequences, prospects and financing of the Fourth Industrial Revolution. |
artificial intelligence in the field of economics: Perspectives on Digital Humanism Hannes Werthner, Erich Prem, Edward A. Lee, Carlo Ghezzi, 2021-11-23 This open access book aims to set an agenda for research and action in the field of Digital Humanism through short essays written by selected thinkers from a variety of disciplines, including computer science, philosophy, education, law, economics, history, anthropology, political science, and sociology. This initiative emerged from the Vienna Manifesto on Digital Humanism and the associated lecture series. Digital Humanism deals with the complex relationships between people and machines in digital times. It acknowledges the potential of information technology. At the same time, it points to societal threats such as privacy violations and ethical concerns around artificial intelligence, automation and loss of jobs, ongoing monopolization on the Web, and sovereignty. Digital Humanism aims to address these topics with a sense of urgency but with a constructive mindset. The book argues for a Digital Humanism that analyses and, most importantly, influences the complex interplay of technology and humankind toward a better society and life while fully respecting universal human rights. It is a call to shaping technologies in accordance with human values and needs. |
artificial intelligence in the field of economics: Preparing for the Future of Artificial Intelligence Committee on Technology National Science and Technology Council, Committee on Technology, 2016-10-30 Advances in Artificial Intelligence (AI) technology have opened up new markets and new opportunities for progress in critical areas such as health, education, energy, and the environment. In recent years, machines have surpassed humans in the performance of certain specific tasks, such as some aspects of image recognition. Experts forecast that rapid progress in the field of specialized artificial intelligence will continue. Although it is very unlikely that machines will exhibit broadly-applicable intelligence comparable to or exceeding that of humans in the next 20 years, it is to be expected that machines will reach and exceed human performance on more and more tasks. As a contribution toward preparing the United States for a future in which AI plays a growing role, this report surveys the current state of AI, its existing and potential applications, and the questions that are raised for society and public policy by progress in AI. The report also makes recommendations for specific further actions by Federal agencies and other actors. |
artificial intelligence in the field of economics: Data Science for Economics and Finance Sergio Consoli, Diego Reforgiato Recupero, Michaela Saisana, 2021 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. |
artificial intelligence in the field of economics: Combating Inequality Olivier Blanchard, Dani Rodrik, 2021-02-02 Leading economists and policymakers consider what economic tools are most effective in reversing the rise in inequality. Economic inequality is the defining issue of our time. In the United States, the wealth share of the top 1% has risen from 25% in the late 1970s to around 40% today. The percentage of children earning more than their parents has fallen from 90% in the 1940s to around 50% today. In Combating Inequality, leading economists, many of them current or former policymakers, bring good news: we have the tools to reverse the rise in inequality. In their discussions, they consider which of these tools are the most effective at doing so. |
ARTIFICIAL Definition & Meaning - Merriam-Webster
The meaning of ARTIFICIAL is made, produced, or done by humans especially to seem like something natural : man-made. How to use artificial in a sentence.
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ARTIFICIAL definition: 1. made by people, often as a copy of something natural: 2. not sincere: 3. made by people, often…. Learn more.
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1. produced by man; not occurring naturally: artificial materials of great strength. 2. made in imitation of a natural product, esp as a substitute; not genuine: artificial cream. 3. pretended; …
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Artificial is used to describe things that are made or manufactured as opposed to occurring naturally. Artificial is often used as the opposite of natural. A close synonym of artificial is synthetic.
ARTIFICIAL definition and meaning | Collins English Dictionary
Artificial objects, materials, or processes do not occur naturally and are created by human beings, for example using science or technology.
artificial adjective - Definition, pictures, pronunciation and usage ...
Definition of artificial adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
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While artificial can simply mean “made by humans,” it’s often used in a negative sense, conveying the idea that an artificial product is inferior to the real thing. If you remark that your friend’s new …
artificial - Wiktionary, the free dictionary
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Artificial Intelligence Is Not Intelligent - The Atlantic
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Artificial intelligence and behavioral economics
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Comparison of Generative AI and Artificial Intelligence
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Does Artificial Intelligence Help or Hurt Gender Diversity?
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Artificial intelligence in the field of economics
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Economics Papers We investigate whether artificial intelligence can address the peer review crisis in economics by analyzing 27,090 evaluations of 9,030 unique submissions using a large …
Understanding Generative Artificial Intelligence's …
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KEYWORDS: artificial intelligence, computer, government, ethics, accounts I. INTRODUCTION Alan Turing was the first person to conduct substantial research in the field that he called …
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Original Contribution The Integration of Artificial …
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Artificial Intelligence and the Economics of Decision-Making
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The Transformative Effects of AI on International Economics
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F&D : THE MACROECONOMICS OF Artificial Intelligence - IMF
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Artificial intelligence, labour markets and inflation* - SUERF
Artificial intelligence (AI) is poised to reshape the economy by affecting aggregate demand (via consumption and investment) and aggregate supply (through productivity). We lay out a basic …
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1 Artificial Intelligence-Based Techniques for Emerging Robotics Communication: A Survey and Future Perspectives S. H. Alsamhi1, Ou Ma2, 3M.S. Ansari 1School of Aerospace, Tsinghua …
Comments of the International Center for Law & Economics
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A comprehensive review of artificial intelligence and …
Nevertheless, the implementation of artificial intelligence (AI) and machine learning (ML) technologies has the potential to improve energy management, efficiency, and sustainability. …
Generative Artificial Intelligence (OpenAI) Empowering …
May 16, 2025 · Generative Artificial Intelligence (OpenAI) Empowering . ... A Case . Study of Xi'an University of Finance and Economics. Zhang Yunyun. 1, a,* 1. College of . Economics, Xi’an …
Artificial Intelligence and the future of employment; a …
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A Survey of Explainable Artificial Intelligence (XAI) in …
CCS Concepts: • General and reference →Surveys and overviews; • Applied computing →Economics; • Computing method-ologies →Machine learning; Artificial intelligence. …
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“The One Hundred Year Study on Artificial Intelligence (AI100), launched in the fall of 2014, is a long-term investigation of the field of Artificial Intelligence (AI) and its influences on people, …
Artificial Intelligence and Economic Theories - ResearchGate
artificial intelligence on economic theories, a subject that has not been extensively studied. The theories that are considered are: demand and supply, asymmetrical information, pricing, rational
Artificial intelligence solutions enabling sustainable …
RESEARCH ARTICLE Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis Priya Rani Bhagat ID 1, Farheen Naz ID 1*, Robert Magda1,2 1 Institute …
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AI in Finance: A Review - Data Science
‘artificial intelligence in finance’, ‘artificial intelligence for finance’, ‘AI in finance’, and ‘AI for finance’. Similar keywords are set for collecting the search data for AI-Economics and AI …
ETHICAL CONCERNS ASSOCIATED WITH ARTIFICIAL …
Journal of Business Economics and Management, 2023, 24(2): 387–404 389 AI, a field at the beginning of the road in an emerging country imposed to some extent by
ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION. A …
Figure 4. Publication titles with highest numbers of papers in the field of artificial intelligence, in connection with higher education . An investigation in this field could not be completed without …