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Rationality and Intelligence develops and justifies a prescriptive theory of rational thinking in terms of utility theory and the theory of rational life plans. The prescriptive theory, buttressed by other assumptions, suggests that people generally think too little and in a way that is insufficiently critical of the initial possibilities that occur to them.
How to assess critical aspects of cognitive functioning that are not measured by IQ tests: rational thinking skills. Why are we surprised when smart people act foolishly? Smart people do foolish things all the time. Misjudgments and bad decisions by highly educated bankers and money managers, for example, brought us the financial crisis of 2008. Smart people do foolish things because intelligence is not the same as the capacity for rational thinking. The Rationality Quotient explains that these two traits, often (and incorrectly) thought of as one, refer to different cognitive functions. The standard IQ test, the authors argue, doesn't measure any of the broad components of rationality—adaptive responding, good judgment, and good decision making. The authors show that rational thinking, like intelligence, is a measurable cognitive competence. Drawing on theoretical work and empirical research from the last two decades, they present the first prototype for an assessment of rational thinking analogous to the IQ test: the CART (Comprehensive Assessment of Rational Thinking). The authors describe the theoretical underpinnings of the CART, distinguishing the algorithmic mind from the reflective mind. They discuss the logic of the tasks used to measure cognitive biases, and they develop a unique typology of thinking errors. The Rationality Quotient explains the components of rational thought assessed by the CART, including probabilistic and scientific reasoning; the avoidance of “miserly” information processing; and the knowledge structures needed for rational thinking. Finally, the authors discuss studies of the CART and the social and practical implications of such a test. An appendix offers sample items from the test.
Critics of intelligence tests writers such as Robert Sternberg, Howard Gardner, and Daniel Goleman have argued in recent years that these tests neglect important qualities such as emotion, empathy, and interpersonal skills. However, such critiques imply that though intelligence tests may miss certain key noncognitive areas, they encompass most of what is important in the cognitive domain. In this book, Keith E. Stanovich challenges this widely held assumption.Stanovich shows that IQ tests (or their proxies, such as the SAT) are radically incomplete as measures of cognitive functioning. They fail to assess traits that most people associate with good thinking, skills such as judgment and decision making. Such cognitive skills are crucial to real-world behavior, affecting the way we plan, evaluate critical evidence, judge risks and probabilities, and make effective decisions. IQ tests fail to assess these skills of rational thought, even though they are measurable cognitive processes. Rational thought is just as important as intelligence, Stanovich argues, and it should be valued as highly as the abilities currently measured on intelligence tests.
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
In this book, Keith Stanovich attempts to resolve the Great Rationality Debate in cognitive science-the debate about how much irrationality to ascribe to human cognition. Stanovich shows how the insights of dual-process theory and evolutionary psychology can be combined to explain why humans are sometimes irrational even though they possess cognitive machinery of remarkable adaptiveness. Using a unique individual differences approach, Stanovich shows that to fully characterize differences in rational thinking, the traditional System 2 of dual-process theory must be partitioned into the reflective mind and the algorithmic mind. Using a new tripartite model of mind, Stanovich shows how rationality is a more encompassing construct than intelligence-when both are properly defined-and that IQ tests fail to assess individual differences in rational thought. Stanovich discusses the types of thinking processes that would be measured in an assessment of rational thinking.
Like Mooki, the hero of Spike Lee's film Do the Right Thing artificially, intelligent systems have a hard time knowing what to do in all circumstances. Classical theories of perfect rationality prescribe the right thing for any occasion, but no finite agent can compute their prescriptions fast enough. In Do the Right Thing, the authors argue that a new theoretical foundation for artificial intelligence can be constructed in which rationality is a property of programs within a finite architecture, and their behaviour over time in the task environment, rather than a property of individual decisions.
A lucid and wide-ranging introduction to the philosophy of mind, suitable for readers with a basic grounding in philosophy.
"More information is always better, and full information is best. More computation is always better, and optimization is best." More-is-better ideals such as these have long shaped our vision of rationality. Yet humans and other animals typically rely on simple heuristics to solve adaptive problems, focusing on one or a few important cues and ignoring the rest, and shortcutting computation rather than striving for as much as possible. In this book, we argue that in an uncertain world, more information and computation are not always better, and we ask when, and why, less can be more. The answers to these questions constitute the idea of ecological rationality: how we are able to achieve intelligence in the world by using simple heuristics matched to the environments we face, exploiting the structures inherent in our physical, biological, social, and cultural surroundings.
A TIMES BOOK OF THE YEAR 2021 'Punchy, funny and invigorating ... Pinker is the high priest of rationalism' Sunday Times 'If you've ever considered taking drugs to make yourself smarter, read Rationality instead. It's cheaper, more entertaining, and more effective' Jonathan Haidt, author of The Righteous Mind In the twenty-first century, humanity is reaching new heights of scientific understanding - and at the same time appears to be losing its mind. How can a species that discovered vaccines for Covid-19 in less than a year produce so much fake news, quack cures and conspiracy theorizing? In Rationality, Pinker rejects the cynical cliché that humans are simply an irrational species - cavemen out of time fatally cursed with biases, fallacies and illusions. After all, we discovered the laws of nature, lengthened and enriched our lives and set the benchmarks for rationality itself. Instead, he explains, we think in ways that suit the low-tech contexts in which we spend most of our lives, but fail to take advantage of the powerful tools of reasoning we have built up over millennia: logic, critical thinking, probability, causal inference, and decision-making under uncertainty. These tools are not a standard part of our educational curricula, and have never been presented clearly and entertainingly in a single book - until now. Rationality matters. It leads to better choices in our lives and in the public sphere, and is the ultimate driver of social justice and moral progress. Brimming with insight and humour, Rationality will enlighten, inspire and empower. 'A terrific book, much-needed for our time' Peter Singer
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.