Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
What Do We Know About Algorithmic Collusion Now New Insights From The Latest Academic Research
Download What Do We Know About Algorithmic Collusion Now New Insights From The Latest Academic Research full books in PDF, epub, and Kindle. Read online What Do We Know About Algorithmic Collusion Now New Insights From The Latest Academic Research ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis What Do We Know About Algorithmic Collusion Now? New Insights from the Latest Academic Research by : Ai Deng
Download or read book What Do We Know About Algorithmic Collusion Now? New Insights from the Latest Academic Research written by Ai Deng and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic collusion has captured the attention of the global antitrust community for the past several years. Deng (2020) provided a comprehensive survey of the pertinent literature in economics and computer science and a critical discussion. Over the past three years, new insights have emerged from academic research. These new insights have not only deepened our understanding of the intricate relationship between algorithms and competition but also begun challenging some previous findings once considered compelling evidence supporting the plausibility of autonomous algorithmic tacit collusion. In this article, I discuss these new insights, with a focus on four topics: (1) the nuanced ways algorithms affect prices, (2) the crucial role of algorithmic design, (3) the consequences of third-party pricing algorithms, and (4) some considerations when assessing algorithmic impact in litigation.
Book Synopsis What Do We Know About Algorithmic Tacit Collusion? by : Ai Deng
Download or read book What Do We Know About Algorithmic Tacit Collusion? written by Ai Deng and published by . This book was released on 2019 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past few years have seen many legal scholars and antitrust agencies expressing interest in and concerns with algorithmic collusion. In this paper, I survey and draw lessons from the literature on Artificial Intelligence and on the economics of algorithmic tacit collusion. I show that a good understanding of this literature is a crucial first step to better understand the antitrust risks of algorithmic pricing and devise antitrust policies to combat such risks.
Book Synopsis When Machines Learn to Collude by : Ai Deng
Download or read book When Machines Learn to Collude written by Ai Deng and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: From Professors Maurice Stucke and Ariel Ezrachi's Virtual Competition published a year ago, to speeches by the Federal Trade Commission Commissioner Terrell McSweeny and Acting Chair Maureen K. Ohlhausen, to an entire issue of a recent CPI Antitrust Chronicles, and a conference hosted by Organisation for Economic Co-operation and Development (OECD) in June this year, there has been an active and ongoing discussion in the antitrust community about computer algorithms. In this note, I briefly summarize the current views and concerns in the antitrust and artificial intelligence (AAI) literature pertaining to algorithmic collusion and then discuss the insights and lessons we could learn from a recent AI research study. As I argue in the article, not all assumptions in the antitrust scholarship have empirical support at this point.
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 Virtual Competition by : Ariel Ezrachi
Download or read book Virtual Competition written by Ariel Ezrachi and published by Harvard University Press. This book was released on 2016-11-14 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: “A fascinating book about how platform internet companies (Amazon, Facebook, and so on) are changing the norms of economic competition.” —Fast Company Shoppers with a bargain-hunting impulse and internet access can find a universe of products at their fingertips. But is there a dark side to internet commerce? This thought-provoking exposé invites us to explore how sophisticated algorithms and data-crunching are changing the nature of market competition, and not always for the better. Introducing into the policy lexicon terms such as algorithmic collusion, behavioral discrimination, and super-platforms, Ariel Ezrachi and Maurice E. Stucke explore the resulting impact on competition, our democratic ideals, our wallets, and our well-being. “We owe the authors our deep gratitude for anticipating and explaining the consequences of living in a world in which black boxes collude and leave no trails behind. They make it clear that in a world of big data and algorithmic pricing, consumers are outgunned and antitrust laws are outdated, especially in the United States.” —Science “A convincing argument that there can be a darker side to the growth of digital commerce. The replacement of the invisible hand of competition by the digitized hand of internet commerce can give rise to anticompetitive behavior that the competition authorities are ill equipped to deal with.” —Burton G. Malkiel, Wall Street Journal “A convincing case for the need to rethink competition law to cope with algorithmic capitalism’s potential for malfeasance.” —John Naughton, The Observer
Author :American Bar Association. Section of Antitrust Law Publisher :American Bar Association ISBN 13 :9781590315170 Total Pages :524 pages Book Rating :4.3/5 (151 download)
Book Synopsis Econometrics by : American Bar Association. Section of Antitrust Law
Download or read book Econometrics written by American Bar Association. Section of Antitrust Law and published by American Bar Association. This book was released on 2005 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The economic expert has become a central figure in virtually every antitrust litigation or merger matter, and the importance of econometrics has increased significantly. A basic understanding of econometric principles has now become almost essential to the serious antitrust practitioner. This volume is designed to introduce lawyers to the theoretical and practical issues of econometrics, providing necessary tools for working effectively with economic experts on both sides of a matter." -- from the Foreword, p. xv.
Book Synopsis The Theory of Collusion and Competition Policy by : Joseph E. Harrington, Jr.
Download or read book The Theory of Collusion and Competition Policy written by Joseph E. Harrington, Jr. and published by MIT Press. This book was released on 2017-11-16 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: A review of the theoretical research on unlawful collusion, focusing on the impact and optimal design of competition law and enforcement. Collusion occurs when firms in a market coordinate their behavior for the purpose of producing a supracompetitive outcome. The literature on the theory of collusion is deep and broad but most of that work does not take account of the possible illegality of collusion. Recently, there has been a growing body of research that explicitly focuses on collusion that runs afoul of competition law and thereby makes firms potentially liable for penalties. This book, by an expert on the subject, reviews the theoretical research on unlawful collusion, with a focus on two issues: the impact of competition law and enforcement on whether, how long, and how much firms collude; and the optimal design of competition law and enforcement. The book begins by discussing general issues that arise when models of collusion take into account competition law and enforcement. It goes on to consider game-theoretic models that encompass the probability of detection and penalties incurred when convicted, and examines how these policy instruments affect the frequency of cartels, cartel duration, cartel participation, and collusive prices. The book then considers the design of competition law and enforcement, examining such topics as the formula for penalties and leniency programs. The book concludes with suggested future lines of inquiry into illegal collusion.
Book Synopsis Algorithmic Audience in the Age of Artificial Intelligence by : Roselyn Du
Download or read book Algorithmic Audience in the Age of Artificial Intelligence written by Roselyn Du and published by AEJMC - Peter Lang Scholarsourcing Series. This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic Audience in the Age of Artificial Intelligence employs a mix-methods approach to examine and interpret the algorithmic news consumption phenomenon from several inter-related perspectives, including tailored communication, customization, gatekeeping, agenda-resisting, algorithmic literacy, and news literacy. Potential implications for an empowered or rather (information-) cocooned public are explored. The research aims to illuminate the renewed relationship between media and audience and the effects on users of algorithmic processes. The aim of the book is multifaceted: (1) to describe the phenomenon of AI-based news recommendation; (2) to explore the user experience of consuming recommended news; (3) to analyze the effects that algorithmic news consumption has on the audiences; (4) to raise awareness of the impact of algorithmic news consumption; (5) to inform the public, technocrats, and policy makers of the effects of algorithmic news consumption; and (6) to guide debate on ethical decision-making and possible policy change. Through an empirical investigation process, this volume examines algorithmic news consumption from a user perspective and dissects the complex effects caused by such consumption. This book is suitable to be a primary text for undergraduate-level courses relating to media literacy issues and graduate-level courses with a particular focus on audience analysis in the age of artificial intelligence. It can also serve as a supplemental text for core courses in media/communication studies, such as Introduction to Communication, Current Issues in Communication, Communication Theory, and Communication Ethics. "This comprehensive work uses original research to both focus and expand our understanding about the ways that the growing consumption of algorithmic news will impact both the news media business and participatory democracy. It provides sharp new insights at a critical moment in the evolution of journalism." --Ryan Thornburg, Associate Professor of Journalism, School of Journalism and Media, University of North Carolina at Chapel Hill "Roselyn Du's book is a roadmap to understanding how the audience of today's news are grappling with tailored communication, information cocoons, algorithmic literacy, and news literacy. This book is timely, insightful, and methodologically rigorous. This is a must read for students and scholars interested in algorithms and journalism." --Kerk F Kee, Associate Professor of Media & Communication, Texas Tech University "Guided by key theoretical considerations, this timely text details comprehensive empirical investigation of the effects of algorithmic news recommendations on news appreciation, news literacy, and public agenda priorities. Findings suggest that algorithmic news consumption may not be as dangerous as presumed and warned. A significant contribution of this work is support for the theoretical development of a renewed conception of the active audience and the redefinition of agenda-setting. A compelling case is made for the importance of research on algorithms and artificial intelligence for understanding the future of journalism and civic society." --Cynthia King, Professor of Communication, California State University, Fullerton
Book Synopsis How Much Inequality Is Fair? by : Venkat Venkatasubramanian
Download or read book How Much Inequality Is Fair? written by Venkat Venkatasubramanian and published by Columbia University Press. This book was released on 2017-08-08 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many in the United States feel that the nation’s current level of economic inequality is unfair and that capitalism is not working for 90% of the population. Yet some inequality is inevitable. The question is: What level of inequality is fair? Mainstream economics has offered little guidance on fairness and the ideal distribution of income. Political philosophy, meanwhile, has much to say about fairness yet relies on qualitative theories that cannot be verified by empirical data. To address inequality, we need to know what the goal is—and for this, we need a quantitative, testable theory of fairness for free-market capitalism. How Much Inequality Is Fair? synthesizes concepts from economics, political philosophy, game theory, information theory, statistical mechanics, and systems engineering into a mathematical framework for a fair free-market society. The key to this framework is the insight that maximizing fairness means maximizing entropy, which makes it possible to determine the fairest possible level of pay inequality. The framework therefore provides a moral justification for capitalism in mathematical terms. Venkat Venkatasubramanian also compares his theory’s predictions to actual inequality data from various countries—showing, for instance, that Scandinavia has near-ideal fairness, while the United States is markedly unfair—and discusses the theory’s implications for tax policy, social programs, and executive compensation.
Book Synopsis Big Data and Competition Policy by : Maurice E. Stucke
Download or read book Big Data and Competition Policy written by Maurice E. Stucke and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The first text to provide understanding of the important new issue of Big Data and how it relates to competition laws and policy, both in the EU and US.
Book Synopsis Twenty Lectures on Algorithmic Game Theory by : Tim Roughgarden
Download or read book Twenty Lectures on Algorithmic Game Theory written by Tim Roughgarden and published by Cambridge University Press. This book was released on 2016-08-30 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management.
Book Synopsis The Algorithmic Foundations of Differential Privacy by : Cynthia Dwork
Download or read book The Algorithmic Foundations of Differential Privacy written by Cynthia Dwork and published by . This book was released on 2014 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the application of these techniques in creative combinations, using the query-release problem as an ongoing example. A key point is that, by rethinking the computational goal, one can often obtain far better results than would be achieved by methodically replacing each step of a non-private computation with a differentially private implementation. Despite some powerful computational results, there are still fundamental limitations. Virtually all the algorithms discussed herein maintain differential privacy against adversaries of arbitrary computational power -- certain algorithms are computationally intensive, others are efficient. Computational complexity for the adversary and the algorithm are both discussed. The monograph then turns from fundamentals to applications other than query-release, discussing differentially private methods for mechanism design and machine learning. The vast majority of the literature on differentially private algorithms considers a single, static, database that is subject to many analyses. Differential privacy in other models, including distributed databases and computations on data streams, is discussed. The Algorithmic Foundations of Differential Privacy is meant as a thorough introduction to the problems and techniques of differential privacy, and is an invaluable reference for anyone with an interest in the topic.
Book Synopsis Algorithms and Law by : Martin Ebers
Download or read book Algorithms and Law written by Martin Ebers and published by Cambridge University Press. This book was released on 2020-07-23 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring issues from big-data to robotics, this volume is the first to comprehensively examine the regulatory implications of AI technology.
Book Synopsis The Antitrust Paradox by : Robert Bork
Download or read book The Antitrust Paradox written by Robert Bork and published by . This book was released on 2021-02-22 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most important book on antitrust ever written. It shows how antitrust suits adversely affect the consumer by encouraging a costly form of protection for inefficient and uncompetitive small businesses.
Book Synopsis Making Friends on the Fly: Advances in Ad Hoc Teamwork by : Samuel Barrett
Download or read book Making Friends on the Fly: Advances in Ad Hoc Teamwork written by Samuel Barrett and published by Springer. This book was released on 2015-05-25 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the encounter and interaction of agents such as robots with other agents and describes how they cooperate with their previously unknown teammates, forming an Ad Hoc team. It presents a new algorithm, PLASTIC, that allows agents to quickly adapt to new teammates by reusing knowledge learned from previous teammates. PLASTIC is instantiated in both a model-based approach, PLASTIC-Model and a policy-based approach, PLASTIC-Policy. In addition to reusing knowledge learned from previous teammates, PLASTIC also allows users to provide expert-knowledge and can use transfer learning (such as the new Two Stage Transfer algorithm) to quickly create models of new teammates when it has some information about its new teammates. The effectiveness of the algorithm is demonstrated on three domains, ranging from multi-armed bandits to simulated robot soccer games.
Book Synopsis How Do Cartels Operate? by : Joseph Emmett Harrington
Download or read book How Do Cartels Operate? written by Joseph Emmett Harrington and published by Now Publishers Inc. This book was released on 2006 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper distills and organizes facts about cartels from about 20 European Commission decisions over 2000-2004. It describes the properties of a collusive outcome in terms of the setting of price and a market allocation, monitoring of agreements with respect to price but more importantly sales, punishment methods for enforcing an agreement and also the use of buy-backs to compensate cartel members, methods for responding to external disruptions from non-cartel suppliers and handling over-zealous sales representatives, and operational procedures in terms of the frequency of meetings and the cartel's organizational structure.
Book Synopsis The Cambridge Handbook of the Law of Algorithms by : Woodrow Barfield
Download or read book The Cambridge Handbook of the Law of Algorithms written by Woodrow Barfield and published by Cambridge University Press. This book was released on 2020-11-05 with total page 1327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithms are a fundamental building block of artificial intelligence - and, increasingly, society - but our legal institutions have largely failed to recognize or respond to this reality. The Cambridge Handbook of the Law of Algorithms, which features contributions from US, EU, and Asian legal scholars, discusses the specific challenges algorithms pose not only to current law, but also - as algorithms replace people as decision makers - to the foundations of society itself. The work includes wide coverage of the law as it relates to algorithms, with chapters analyzing how human biases have crept into algorithmic decision-making about who receives housing or credit, the length of sentences for defendants convicted of crimes, and many other decisions that impact constitutionally protected groups. Other issues covered in the work include the impact of algorithms on the law of free speech, intellectual property, and commercial and human rights law.
