Download or read book Rational Machines and Artificial Intelligence written by Tshilidzi Marwala and published by Academic Press. This book was released on 2021-03-31 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent machines are populating our social, economic and political spaces. These intelligent machines are powered by Artificial Intelligence technologies such as deep learning. They are used in decision making. One element of decision making is the issue of rationality. Regulations such as the General Data Protection Regulation (GDPR) require that decisions that are made by these intelligent machines are explainable. Rational Machines and Artificial Intelligence proposes that explainable decisions are good but the explanation must be rational to prevent these decisions from being challenged. Noted author Tshilidzi Marwala studies the concept of machine rationality and compares this to the rationality bounds prescribed by Nobel Laureate Herbert Simon and rationality bounds derived from the work of Nobel Laureates Richard Thaler and Daniel Kahneman. Rational Machines and Artificial Intelligence describes why machine rationality is flexibly bounded due to advances in technology. This effectively means that optimally designed machines are more rational than human beings. Readers will also learn whether machine rationality can be quantified and identify how this can be achieved. Furthermore, the author discusses whether machine rationality is subjective. Finally, the author examines whether a population of intelligent machines collectively make more rational decisions than individual machines. Examples in biomedical engineering, social sciences and the financial sectors are used to illustrate these concepts. Provides an introduction to the key questions and challenges surrounding Rational Machines, including, When do we rely on decisions made by intelligent machines? What do decisions made by intelligent machines mean? Are these decisions rational or fair? Can we quantify these decisions? and Is rationality subjective? Introduces for the first time the concept of rational opportunity costs and the concept of flexibly bounded rationality as a rationality of intelligent machines and the implications of these issues on the reliability of machine decisions Includes coverage of Rational Counterfactuals, group versus individual rationality, and rational markets Discusses the application of Moore’s Law and advancements in Artificial Intelligence, as well as developments in the area of data acquisition and analysis technologies and how they affect the boundaries of intelligent machine rationality
Download or read book Rational Machines and Artificial Intelligence written by Tshilidzi Marwala and published by Academic Press. This book was released on 2021-03-31 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent machines are populating our social, economic and political spaces. These intelligent machines are powered by Artificial Intelligence technologies such as deep learning. They are used in decision making. One element of decision making is the issue of rationality. Regulations such as the General Data Protection Regulation (GDPR) require that decisions that are made by these intelligent machines are explainable. Rational Machines and Artificial Intelligence proposes that explainable decisions are good but the explanation must be rational to prevent these decisions from being challenged. Noted author Tshilidzi Marwala studies the concept of machine rationality and compares this to the rationality bounds prescribed by Nobel Laureate Herbert Simon and rationality bounds derived from the work of Nobel Laureates Richard Thaler and Daniel Kahneman. Rational Machines and Artificial Intelligence describes why machine rationality is flexibly bounded due to advances in technology. This effectively means that optimally designed machines are more rational than human beings. Readers will also learn whether machine rationality can be quantified and identify how this can be achieved. Furthermore, the author discusses whether machine rationality is subjective. Finally, the author examines whether a population of intelligent machines collectively make more rational decisions than individual machines. Examples in biomedical engineering, social sciences and the financial sectors are used to illustrate these concepts. Provides an introduction to the key questions and challenges surrounding Rational Machines, including, When do we rely on decisions made by intelligent machines? What do decisions made by intelligent machines mean? Are these decisions rational or fair? Can we quantify these decisions? and Is rationality subjective? Introduces for the first time the concept of rational opportunity costs and the concept of flexibly bounded rationality as a rationality of intelligent machines and the implications of these issues on the reliability of machine decisions Includes coverage of Rational Counterfactuals, group versus individual rationality, and rational markets Discusses the application of Moore’s Law and advancements in Artificial Intelligence, as well as developments in the area of data acquisition and analysis technologies and how they affect the boundaries of intelligent machine rationality
Download or read book Artificial Intelligence Techniques for Rational Decision Making written by Tshilidzi Marwala and published by Springer. This book was released on 2014-10-20 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon’s bounded rationality theory are flexible due to advanced signal processing techniques, Moore’s Law and artificial intelligence. Artificial Intelligence Techniques for Rational Decision Making examines and defines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making: Theory of the marginalization of irrelevant information Principal component analysis Independent component analysis Automatic relevance determination method In addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence. Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas.
Download or read book Causality Correlation and Artificial Intelligence for Rational Decision Making written by Tshilidzi Marwala and published by World Scientific. This book was released on 2015-01-02 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Causality has been a subject of study for a long time. Often causality is confused with correlation. Human intuition has evolved such that it has learned to identify causality through correlation. In this book, four main themes are considered and these are causality, correlation, artificial intelligence and decision making. A correlation machine is defined and built using multi-layer perceptron network, principal component analysis, Gaussian Mixture models, genetic algorithms, expectation maximization technique, simulated annealing and particle swarm optimization. Furthermore, a causal machine is defined and built using multi-layer perceptron, radial basis function, Bayesian statistics and Hybrid Monte Carlo methods. Both these machines are used to build a Granger non-linear causality model. In addition, the Neyman–Rubin, Pearl and Granger causal models are studied and are unified. The automatic relevance determination is also applied to extend Granger causality framework to the non-linear domain. The concept of rational decision making is studied, and the theory of flexibly-bounded rationality is used to extend the theory of bounded rationality within the principle of the indivisibility of rationality. The theory of the marginalization of irrationality for decision making is also introduced to deal with satisficing within irrational conditions. The methods proposed are applied in biomedical engineering, condition monitoring and for modelling interstate conflict. Contents:Introduction to Artificial Intelligence based Decision MakingWhat is a Correlation Machine?What is a Causal Machine?Correlation Machines Using Optimization MethodsNeural Networks for Modeling Granger CausalityRubin, Pearl and Granger Causality Models: A Unified ViewCausal, Correlation and Automatic Relevance Determination Machines for Granger CausalityFlexibly-bounded RationalityMarginalization of Irrationality in Decision MakingConclusions and Further Work Readership: Graduate students, researchers and professionals in the field of artificial intelligence. Key Features:It proposes fresh definition of causality and proposes two new theories i.e. flexibly bounded rationality and marginalization of irrationality theory for decision makingIt also applies these techniques to a diverse areas in engineering, political science and biomedical engineeringKeywords:Causality;Correlation;Artificial Intelligence;Rational Decision Making
Download or read book From Deep Learning to Rational Machines written by Cameron J. Buckner and published by Oxford University Press. This book was released on 2023 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides a framework for thinking about foundational philosophical questions surrounding machine learning as an approach to artificial intelligence. Specifically, it links recent breakthroughs in deep learning to classical empiricist philosophy of mind. In recent assessments of deep learning's current capabilities and future potential, prominent scientists have cited historical figures from the perennial philosophical debate between nativism and empiricism, which primarily concerns the origins of abstract knowledge. These empiricists were generally faculty psychologists; that is, they argued that the active engagement of general psychological faculties-such as perception, memory, imagination, attention, and empathy-enables rational agents to extract abstract knowledge from sensory experience. This book explains a number of recent attempts to model roles attributed to these faculties in deep neural network based artificial agents by appeal to the faculty psychology of philosophers such as Aristotle, Ibn Sina (Avicenna), John Locke David Hume, William James, and Sophie de Grouchy. It illustrates the utility of this interdisciplinary connection by showing how it can provide benefits to both philosophy and computer science: computer scientists can continue to mine the history of philosophy for ideas and aspirational targets to hit on the way to more robustly rational artificial agents, and philosophers can see how some of the historical empiricists' most ambitious speculations can be realized in specific computational systems"--
Download or read book From Deep Learning to Rational Machines written by Cameron J. Buckner and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides a framework for thinking about foundational philosophical questions surrounding machine learning as an approach to artificial intelligence. Specifically, it links recent breakthroughs in deep learning to classical empiricist philosophy of mind. In recent assessments of deep learning's current capabilities and future potential, prominent scientists have cited historical figures from the perennial philosophical debate between nativism and empiricism, which primarily concerns the origins of abstract knowledge. These empiricists were generally faculty psychologists; that is, they argued that the active engagement of general psychological faculties-such as perception, memory, imagination, attention, and empathy-enables rational agents to extract abstract knowledge from sensory experience. This book explains a number of recent attempts to model roles attributed to these faculties in deep neural network based artificial agents by appeal to the faculty psychology of philosophers such as Aristotle, Ibn Sina (Avicenna), John Locke David Hume, William James, and Sophie de Grouchy. It illustrates the utility of this interdisciplinary connection by showing how it can provide benefits to both philosophy and computer science: computer scientists can continue to mine the history of philosophy for ideas and aspirational targets to hit on the way to more robustly rational artificial agents, and philosophers can see how some of the historical empiricists' most ambitious speculations can be realized in specific computational systems"--
Download or read book An Introduction to the Philosophy of Mind written by E. Jonathan Lowe and published by Cambridge University Press. This book was released on 2000-01-20 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: A lucid and wide-ranging introduction to the philosophy of mind, suitable for readers with a basic grounding in philosophy.
Download or read book Human Compatible written by Stuart Jonathan Russell and published by Penguin Books. This book was released on 2019 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: A leading artificial intelligence researcher lays out a new approach to AI that will enable people to coexist successfully with increasingly intelligent machines.
Download or read book Representation and Reality in Humans Other Living Organisms and Intelligent Machines written by Gordana Dodig-Crnkovic and published by Springer. This book was released on 2017-08-29 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book enriches our views on representation and deepens our understanding of its different aspects. It arises out of several years of dialog between the editors and the authors, an interdisciplinary team of highly experienced researchers, and it reflects the best contemporary view of representation and reality in humans, other living beings, and intelligent machines. Structured into parts on the cognitive, computational, natural sciences, philosophical, logical, and machine perspectives, a theme of the field and the book is building and presenting networks, and the editors hope that the contributed chapters will spur understanding and collaboration between researchers in domains such as computer science, philosophy, logic, systems theory, engineering, psychology, sociology, anthropology, neuroscience, linguistics, and synthetic biology.
Download or read book Artificial Intelligence and its Impact on Business written by Wolfgang Amann and published by IAP. This book was released on 2020-06-01 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) technologies are one of top investment priorities in these days. They are aimed at finding applications in fields of special value for humans, including education. The fourth industrial revolution will replace not only human hands but also human brains, the time of machines requires new forms of work and new ways of business education, however we must be aware that if there is no control of human-chatbot interaction, there is a risk of losing sight of this interaction’s goal. First, it is important to get people to truly understand AI systems, to intentionally participate in their use, as well as to build their trust, because “the measure of success for AI applications is the value they create for human lives” (Stanford University 2016, 33). Consequently, society needs to adapt to AI applications if it is to extend its benefits and mitigate the inevitable errors and failures. This is why it is highly recommended to create new AI-powered tools for education that are the result of cooperation between AI researchers and humanities’ and social sciences’ researchers, who can identify cognitive processes and human behaviors. This book is authored by a range of international experts with a diversity of backgrounds and perspectives hopefully bringing us closer to the responses for the questions what we should teach (what the ‘right’ set of future skills is), how we should teach (the way in which schools should teach and assess them) and where we should teach (what implications does AI have for today’s education infrastructure). We must remember as we have already noticed before “…education institutions would need to ensure that that they have an appropriate infrastructure, as well as the safety and credibility of AI-based systems. Ultimately, the law and policies need to adjust to the rapid pace of AI development, because the formal responsibility for appropriate learning outcomes will in future be divided between a teacher and a machine. Above all, we should ensure that AI respect human and civil rights (Stachowicz-Stanusch, Amann, 2018)”.
Download or read book Artificial Intelligence written by Stuart Russell and published by Createspace Independent Publishing Platform. This book was released on 2016-09-10 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence: A Modern Approach offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.
Download or read book Hamiltonian Monte Carlo Methods in Machine Learning written by Tshilidzi Marwala and published by Elsevier. This book was released on 2023-02-03 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hamiltonian Monte Carlo Methods in Machine Learning introduces methods for optimal tuning of HMC parameters, along with an introduction of Shadow and Non-canonical HMC methods with improvements and speedup. Lastly, the authors address the critical issues of variance reduction for parameter estimates of numerous HMC based samplers. The book offers a comprehensive introduction to Hamiltonian Monte Carlo methods and provides a cutting-edge exposition of the current pathologies of HMC-based methods in both tuning, scaling and sampling complex real-world posteriors. These are mainly in the scaling of inference (e.g., Deep Neural Networks), tuning of performance-sensitive sampling parameters and high sample autocorrelation. Other sections provide numerous solutions to potential pitfalls, presenting advanced HMC methods with applications in renewable energy, finance and image classification for biomedical applications. Readers will get acquainted with both HMC sampling theory and algorithm implementation. Provides in-depth analysis for conducting optimal tuning of Hamiltonian Monte Carlo (HMC) parameters Presents readers with an introduction and improvements on Shadow HMC methods as well as non-canonical HMC methods Demonstrates how to perform variance reduction for numerous HMC-based samplers Includes source code from applications and algorithms
Download or read book Artificial Intelligence and Education an Ongoing Dialogue written by Otto Federico Von Feigenblatt and published by Ediciones Octaedro. This book was released on 2024-06-01 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present volume explores the broad impact of artificial intelligence in education by presenting a broad range of perspectives from some leading experts in the field. An initial chapter tackles macro level considerations from a social and anthropological perspective. Further, chapters explore more specific topics, ranging from philosophical aspects to the implications of AI in pedagogy and andragogy. The final chapter attempts to integrate the disparate aspects of the dialogue into a cohesive voice.
Download or read book The AI Does Not Hate You written by Tom Chivers and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A deep-dive into the weird and wonderful world of Artificial Intelligence. 'The AI does not hate you, nor does it love you, but you are made of atoms which it can use for something else'. This is a book about AI and AI risk. But it's also more importantly about a community of people who are trying to think rationally about intelligence, and the places that these thoughts are taking them, and what insight they can and can't give us about the future of the human race over the next few years. It explains why these people are worried, why they might be right, and why they might be wrong. It is a book about the cutting edge of our thinking on intelligence and rationality right now by the people who stay up all night worrying about it. Along the way, we discover why we probably don't need to worry about a future AI resurrecting a perfect copy of our minds and torturing us for not inventing it sooner, but we perhaps should be concerned about paperclips destroying life as we know it; how Mickey Mouse can teach us an important lesson about how to program AI; and how a more rational approach to life could be what saves us all. --
Download or read book Thinking Machines written by Alasdair GILCHRIST and published by . This book was released on 2017-07 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: IntroductionIn this series of books - Creating Thinking Machines - we will go on a journey to trace the evolution of the mechanical machine of the last century and its transformation into the intelligent, logical and even rational machine of today. It has progressed so quickly that concerns have been raised in the US senate and the EU parliament due to concerns that these machines have become too intelligent, too smart, and most worrying of all too independent. These autonomous, intelligent machines are not some near future problem their evolution and development started many decades ago. And as with most technological marvels their development progressed slowly and then very quickly leaving us with no time to put in place legislation or a strategy to manage them. Consequently, there is not even a rough plan as to how to handle their proliferation through industry, how they will redefine work and take jobs across the entire spectrum. Most importantly to society as these thinking machines are insidiously permeating into all fabric of our world, will be our relationship with the technology, will we ultimately become dependent upon them. But what are they, how did they come about, and what are the technologies that they are based upon? Those are the question that this series of books hopes to shine some light upon. By doing so, we will explain how a conflation of technologies matured at an opportune time to accelerate the development of such intelligent entities, which now stand on the precipice of an industrial revolution. That such a potentially existential threat could be within not our lifetimes but a handful of years was laughable just five years ago. Yet it has arrived at such speed that it has left us unprepared and with uncertain futures. Throughout this series of books we will examine through in-depth introductions into the fields of robotics, data science, artificial intelligence, machine learning, and neuroscience how to create a thinking machine. Further we will strive to reveal how incremental but hugely important advancements in electronics, algorithms, analytics and microbiology have fueled the transformation of the mechanical machines of the 90's into the thinking machines of 2017. For better or worse they will walk among us, we have created them and cannot un-invent them so you had better learn something about them.
Download or read book Artificial Intelligence and the Law written by Tshilidzi Marwala and published by Springer Nature. This book was released on with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Boomeritis written by Ken Wilber and published by Shambhala Publications. This book was released on 2003-09-09 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ken Wilber's latest book is a daring departure from his previous writings—a highly original work of fiction that combines brilliant scholarship with tongue-in-cheek storytelling to present the integral approach to human development that he expounded in more conventional terms in his recent A Theory of Everything. The story of a naïve young grad student in computer science and his quest for meaning in a fragmented world provides the setting in which Wilber contrasts the alienated "flatland" of scientific materialism with the integral vision, which embraces body, mind, soul, and spirit in self, culture, and nature. The book especially targets one of the most stubborn obstacles to realizing the integral vision: a disease of egocentrism and narcissism that Wilber calls "boomeritis" because it seems to plague the baby-boomer generation most of all. Through a series of sparkling seminar-lectures skillfully interwoven with the hero's misadventures in the realms of sex, drugs, and popular culture, all of the major tenets of extreme postmodernism are criticized—and exemplified—including the author's having a bad case of boomeritis himself. Parody, intellectual slapstick, and a mind-twisting surprise ending unite to produce a highly entertaining summary of the work of cutting-edge theorists in human development from around the world.
