The Difference Between Economic And Artificial Intelligent Methods
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Author | : Ajay Agrawal |
Publisher | : University of Chicago Press |
Total Pages | : 172 |
Release | : 2024-03-05 |
Genre | : Business & Economics |
ISBN | : 0226833127 |
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.
Author | : Tshilidzi Marwala |
Publisher | : Springer Science & Business Media |
Total Pages | : 271 |
Release | : 2013-04-02 |
Genre | : Computers |
ISBN | : 1447150104 |
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.
Author | : Tankiso Moloi |
Publisher | : Springer Nature |
Total Pages | : 131 |
Release | : 2020-05-07 |
Genre | : Computers |
ISBN | : 3030429628 |
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.
Author | : El Bachir Boukherouaa |
Publisher | : International Monetary Fund |
Total Pages | : 35 |
Release | : 2021-10-22 |
Genre | : Business & Economics |
ISBN | : 1589063953 |
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.
Author | : Ruben Mercado |
Publisher | : Cambridge University Press |
Total Pages | : 197 |
Release | : 2021-11-04 |
Genre | : Business & Economics |
ISBN | : 1316517098 |
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.
Author | : Jacob Parakilas |
Publisher | : Chatham House (Formerly Riia) |
Total Pages | : 60 |
Release | : 2018 |
Genre | : Political Science |
ISBN | : 9781784132125 |
"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.
Author | : Tshilidzi Marwala |
Publisher | : Springer |
Total Pages | : 206 |
Release | : 2017-09-18 |
Genre | : Computers |
ISBN | : 3319661043 |
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.
Author | : Shin-yi Peng |
Publisher | : Cambridge University Press |
Total Pages | : 365 |
Release | : 2021-10-14 |
Genre | : Law |
ISBN | : 1108957153 |
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.
Author | : OECD |
Publisher | : OECD Publishing |
Total Pages | : 152 |
Release | : 2019-06-11 |
Genre | : |
ISBN | : 9264545190 |
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.
Author | : Harvard Business Review |
Publisher | : HBR Insights |
Total Pages | : 160 |
Release | : 2019 |
Genre | : Business & Economics |
ISBN | : 9781633697898 |
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.