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| example of artificial intelligence in psychology: Artificial Intelligence in Behavioral and Mental Health Care David D. Luxton, 2015-09-10 Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings |
| example of artificial intelligence in psychology: Artificial Psychology James A. Crowder, John Carbone, Shelli Friess, 2019-05-21 This book explores the subject of artificial psychology and how the field must adapt human neuro-psychological testing techniques to provide adequate cognitive testing of advanced artificial intelligence systems. It shows how classical testing methods will reveal nothing about the cognitive nature of the systems and whether they are learning, reasoning, and evolving correctly; for these systems, the authors outline how testing techniques similar to/adapted from human psychological testing must be adopted, particularly in understanding how the system reacts to failure or relearning something it has learned incorrectly or inferred incorrectly. The authors provide insights into future architectures/capabilities that artificial cognitive systems will possess and how we can evaluate how well they are functioning. It discusses at length the notion of human/AI communication and collaboration and explores such topics as knowledge development, knowledge modeling and ambiguity management, artificial cognition and self-evolution of learning, artificial brain components and cognitive architecture, and artificial psychological modeling. Explores the concepts of Artificial Psychology and Artificial Neuroscience as applied to advanced artificially cognitive systems; Provides insight into the world of cognitive architectures and biologically-based computing designs which will mimic human brain functionality in artificial intelligent systems of the future; Provides description and design of artificial psychological modeling to provide insight into how advanced artificial intelligent systems are learning and evolving; Explores artificial reasoning and inference architectures and the types of modeling and testing that will be required to trust an autonomous artificial intelligent systems. |
| example of artificial intelligence in psychology: Artificial Intelligence John Haugeland, 1989-01-06 Machines who think—how utterly preposterous, huff beleaguered humanists, defending their dwindling turf. Artificial Intelligence—it's here and about to surpass our own, crow techno-visionaries, proclaiming dominion. It's so simple and obvious, each side maintains, only a fanatic could disagree. Deciding where the truth lies between these two extremes is the main purpose of John Haugeland's marvelously lucid and witty book on what artificial intelligence is all about. Although presented entirely in non-technical terms, it neither oversimplifies the science nor evades the fundamental philosophical issues. Far from ducking the really hard questions, it takes them on, one by one. Artificial intelligence, Haugeland notes, is based on a very good idea, which might well be right, and just as well might not. That idea, the idea that human thinking and machine computing are radically the same, provides the central theme for his illuminating and provocative book about this exciting new field. After a brief but revealing digression in intellectual history, Haugeland systematically tackles such basic questions as: What is a computer really? How can a physical object mean anything? What are the options for computational organization? and What structures have been proposed and tried as actual scientific models for intelligence? In a concluding chapter he takes up several outstanding problems and puzzles—including intelligence in action, imagery, feelings and personality—and their enigmatic prospects for solution. |
| example of artificial intelligence in psychology: The Cambridge Handbook of Technology and Employee Behavior Richard N. Landers, 2019-02-14 Experts from across all industrial-organizational (IO) psychology describe how increasingly rapid technological change has affected the field. In each chapter, authors describe how this has altered the meaning of IO research within a particular subdomain and what steps must be taken to avoid IO research from becoming obsolete. This Handbook presents a forward-looking review of IO psychology's understanding of both workplace technology and how technology is used in IO research methods. Using interdisciplinary perspectives to further this understanding and serving as a focal text from which this research will grow, it tackles three main questions facing the field. First, how has technology affected IO psychological theory and practice to date? Second, given the current trends in both research and practice, could IO psychological theories be rendered obsolete? Third, what are the highest priorities for both research and practice to ensure IO psychology remains appropriately engaged with technology moving forward? |
| example of artificial intelligence in psychology: Artificial Intelligence Margaret A. Boden, 2018-08-13 The applications of Artificial Intelligence lie all around us; in our homes, schools and offices, in our cinemas, in art galleries and - not least - on the Internet. The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping to understand the processes of memory, learning, and language from a fresh angle. As a concept, Artificial Intelligence has fuelled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings. In this Very Short Introduction , Margaret A. Boden reviews the philosophical and technological challenges raised by Artificial Intelligence, considering whether programs could ever be really intelligent, creative or even conscious, and shows how the pursuit of Artificial Intelligence has helped us to appreciate how human and animal minds are possible. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable. |
| example of artificial intelligence in psychology: Artificial Psychology Jay Friedenberg, 2010-10-18 Is it possible to construct an artificial person? Researchers in the field of artificial intelligence have for decades been developing computer programs that emulate human intelligence. This book goes beyond intelligence and describes how close we are to recreating many of the other capacities that make us human. These abilities include learning, creativity, consciousness, and emotion. The attempt to understand and engineer these abilities constitutes the new interdisciplinary field of artificial psychology, which is characterized by contributions from philosophy, cognitive psychology, neuroscience, computer science, and robotics. This work is intended for use as a main or supplementary introductory textbook for a course in cognitive psychology, cognitive science, artificial intelligence, or the philosophy of mind. It examines human abilities as operating requirements that an artificial person must have and analyzes them from a multidisciplinary approach. The book is comprehensive in scope, covering traditional topics like perception, memory, and problem solving. However, it also describes recent advances in the study of free will, ethical behavior, affective architectures, social robots, and hybrid human-machine societies. |
| example of artificial intelligence in psychology: An Introduction to Ethics in Robotics and AI Christoph Bartneck, Christoph Lütge, Alan Wagner, Sean Welsh, 2020-08-11 This open access book introduces the reader to the foundations of AI and ethics. It discusses issues of trust, responsibility, liability, privacy and risk. It focuses on the interaction between people and the AI systems and Robotics they use. Designed to be accessible for a broad audience, reading this book does not require prerequisite technical, legal or philosophical expertise. Throughout, the authors use examples to illustrate the issues at hand and conclude the book with a discussion on the application areas of AI and Robotics, in particular autonomous vehicles, automatic weapon systems and biased algorithms. A list of questions and further readings is also included for students willing to explore the topic further. |
| example of artificial intelligence in psychology: Birth of Intelligence Daeyeol Lee, 2020 As man-made machines become more powerful and smarter, will their intelligence eventually exceed our own? To accurately predict how the relationship between human and artificial intelligence will change in the future, it is essential to understand the origin and limits of human intelligence. In Birth of Intelligence, distinguished neuroscientist Daeyeol Lee tackles these pressing fundamental issues. Lee reveals how intelligence is the ability of a biological agent to solve complex decision-making problems in diverse and unpredictable environments. Furthermore, understanding how intelligent behavior emerges from interaction among multiple learning systems will provide valuable insights into the ultimate nature of human intelligence. |
| example of artificial intelligence in psychology: Artificial Intelligence Stuart Russell, Peter Norvig, 2016-09-10 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. |
| example of artificial intelligence in psychology: Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence Gogate, Lakshmi, 2013-02-28 The process of learning words and languages may seem like an instinctual trait, inherent to nearly all humans from a young age. However, a vast range of complex research and information exists in detailing the complexities of the process of word learning. Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence strives to combine cross-disciplinary research into one comprehensive volume to help readers gain a fuller understanding of the developmental processes and influences that makeup the progression of word learning. Blending together developmental psychology and artificial intelligence, this publication is intended for researchers, practitioners, and educators who are interested in language learning and its development as well as computational models formed from these specific areas of research. |
| example of artificial intelligence in psychology: Human Level Artificial Intelligence Mitchell Kwok, 2006-01-01 In the Artificial Intelligence subject matter there are literally thousands and thousands of fields. Some of these fields are: neural networks, genetic programming, heuristic searches, planning programs, and so forth. This book is concerned about learning machines and human - robot interactions. Based on Mitchell's 6 year design of a learning computer program, he discusses the components that make up the human level artificial intelligence program. Instead of using complex matrixes or lengthy discrete mathematical algorithmns, the author explains the computer program in a basic but comprehensive way. The book also outlines some creative approaches to instill intelligence into robots. Most of the material is written in terms of theoretical analysis and has not been scientifically proven through discrete math or computer science. |
| example of artificial intelligence in psychology: Advances in Artificial General Intelligence Ben Goertzel, Pei Wang, 2007 Examines the creation of software programs displaying broad, deep, human-style general intelligence. This work features papers presented at the 2006 AGIRI (Artificial General Intelligence Research Institute) workshop, which illustrates that it is a fit and proper subject for serious science and engineering exploration. |
| example of artificial intelligence in psychology: Explainable and Interpretable Models in Computer Vision and Machine Learning Hugo Jair Escalante, Sergio Escalera, Isabelle Guyon, Xavier Baró, Yağmur Güçlütürk, Umut Güçlü, Marcel van Gerven, 2018-11-29 This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning. Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: · Evaluation and Generalization in Interpretable Machine Learning · Explanation Methods in Deep Learning · Learning Functional Causal Models with Generative Neural Networks · Learning Interpreatable Rules for Multi-Label Classification · Structuring Neural Networks for More Explainable Predictions · Generating Post Hoc Rationales of Deep Visual Classification Decisions · Ensembling Visual Explanations · Explainable Deep Driving by Visualizing Causal Attention · Interdisciplinary Perspective on Algorithmic Job Candidate Search · Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions · Inherent Explainability Pattern Theory-based Video Event Interpretations |
| example of artificial intelligence in psychology: Algorithms Are Not Enough Herbert L. Roitblat, 2020-10-13 Why a new approach is needed in the quest for general artificial intelligence. Since the inception of artificial intelligence, we have been warned about the imminent arrival of computational systems that can replicate human thought processes. Before we know it, computers will become so intelligent that humans will be lucky to kept as pets. And yet, although artificial intelligence has become increasingly sophisticated—with such achievements as driverless cars and humanless chess-playing—computer science has not yet created general artificial intelligence. In Algorithms Are Not Enough, Herbert Roitblat explains how artificial general intelligence may be possible and why a robopocalypse is neither imminent, nor likely. Existing artificial intelligence, Roitblat shows, has been limited to solving path problems, in which the entire problem consists of navigating a path of choices—finding specific solutions to well-structured problems. Human problem-solving, on the other hand, includes problems that consist of ill-structured situations, including the design of problem-solving paths themselves. These are insight problems, and insight is an essential part of intelligence that has not been addressed by computer science. Roitblat draws on cognitive science, including psychology, philosophy, and history, to identify the essential features of intelligence needed to achieve general artificial intelligence. Roitblat describes current computational approaches to intelligence, including the Turing Test, machine learning, and neural networks. He identifies building blocks of natural intelligence, including perception, analogy, ambiguity, common sense, and creativity. General intelligence can create new representations to solve new problems, but current computational intelligence cannot. The human brain, like the computer, uses algorithms; but general intelligence, he argues, is more than algorithmic processes. |
| example of artificial intelligence in psychology: Handbook of Artificial intelligence in psychology Farzin Forouzani Fard, 2024-01-14 In the vast expanse of human understanding, few domains captivate and baffle as much as the interplay between artificial intelligence (AI) and the intricacies of human psychology. It signifies the merging of two separate realms, each teeming with its unique complexities, mysterious enigmas, and profound implications. Our journey through this book manifests as an exploration, a quest to reveal the intricate dimensions of intellect, language, emotions, cognition, character, and neuropsychology in this AI-defined era. |
| example of artificial intelligence in psychology: The Psychology of Artificial Intelligence Tony Prescott, 2024-07-02 What is Artificial Intelligence? How will AI impact society? Is AI more powerful than human intelligence? The Psychology of AI explores all aspects of the psychology–AI relationship, asking how closely AI can resemble humans, and whether this means they could have some form of self-awareness. It considers how AI systems have been modelled on human intelligence and the similarities between brains and computers, along with the current limitations of AI and how these could be overcome in the future. It also looks at how people interact with AI in their everyday lives, exploring some of the ethical and societal risks, such as bias in AI algorithms, and the consequences for our long-term future if AIs do surpass humans in important ways. As AI continues to break new milestones, The Psychology of AI answers key questions about what it really means to be human, and how AI will impact our lives in every way, now and into the future. |
| example of artificial intelligence in psychology: An Intelligence in Our Image Osonde A. Osoba, William Welser IV, William Welser, 2017-04-05 Machine learning algorithms and artificial intelligence influence many aspects of life today. This report identifies some of their shortcomings and associated policy risks and examines some approaches for combating these problems. |
| example of artificial intelligence in psychology: The Question of Artificial Intelligence Brian P. Bloomfield, 2018-05-15 Originally published in 1987 when Artificial Intelligence (AI) was one of the most hotly debated subjects of the moment; there was widespread feeling that it was a field whose ‘time had come’, that intelligent machines lay ‘just around the corner’. Moreover, with the onset of the revolution in information technology and the proclamation from all corners that we were moving into an ‘information society’, developments in AI and advanced computing were seen in many countries as having both strategic and economic importance. Yet, aside from the glare of publicity that tends to surround new scientific ideas or technologies, it must be remembered that AI was a relative newcomer among the sciences; that it had often been the subject of bitter controversy; and that though it had been promising to create intelligent machines for some 40 years prior to publication, many believe that it had actually displayed very little substantive progress. With this background in mind, the aim of this collection of essays was to take a novel look at AI. Rather than following the path of old well-trodden arguments about definitions of intelligence or the status of computer chess programs, the objective was to bring new perspectives to the subject in order to present it in a different light. Indeed, instead of simply adding to the endless wrangling ‘for’ and ‘against’ AI, the source of such divisions is made a topic for analysis in its own right. Drawing on ideas from the philosophy and sociology of scientific knowledge, this collection therefore broke new ground. Moreover, although a great deal had been written about the social and cultural impact of AI, little had been said of the culture of AI scientists themselves – including their discourse and style of thought, as well as the choices, judgements, negotiations and competitive struggles for resources that had shaped the genesis and development of the paradigmatic structure of their discipline at the time. Yet, sociologists of science have demonstrated that the analysis of factors such as these is a necessary part of understanding the development of scientific knowledge. Hence, it was hoped that this collection would help to redress the imbalance and provide a broader and more interesting picture of AI. |
| example of artificial intelligence in psychology: The Cambridge Handbook of Artificial Intelligence Keith Frankish, William M. Ramsey, 2014-06-12 An authoritative, up-to-date survey of the state of the art in artificial intelligence, written for non-specialists. |
| example of artificial intelligence in psychology: The Routledge Social Science Handbook of AI Anthony Elliott, 2021-07-12 The Routledge Social Science Handbook of AI is a landmark volume providing students and teachers with a comprehensive and accessible guide to the major topics and trends of research in the social sciences of artificial intelligence (AI), as well as surveying how the digital revolution – from supercomputers and social media to advanced automation and robotics – is transforming society, culture, politics and economy. The Handbook provides representative coverage of the full range of social science engagements with the AI revolution, from employment and jobs to education and new digital skills to automated technologies of military warfare and the future of ethics. The reference work is introduced by editor Anthony Elliott, who addresses the question of relationship of social sciences to artificial intelligence, and who surveys various convergences and divergences between contemporary social theory and the digital revolution. The Handbook is exceptionally wide-ranging in span, covering topics all the way from AI technologies in everyday life to single-purpose robots throughout home and work life, and from the mainstreaming of human-machine interfaces to the latest advances in AI, such as the ability to mimic (and improve on) many aspects of human brain function. A unique integration of social science on the one hand and new technologies of artificial intelligence on the other, this Handbook offers readers new ways of understanding the rise of AI and its associated global transformations. Written in a clear and direct style, the Handbook will appeal to a wide undergraduate audience. |
| example of artificial intelligence in psychology: Mind as Machine Margaret A. Boden, 2008-06-19 The development of cognitive science is one of the most remarkable and fascinating intellectual achievements of the modern era. The quest to understand the mind is as old as recorded human thought; but the progress of modern science has offered new methods and techniques which have revolutionized this enquiry. Oxford University Press now presents a masterful history of cognitive science, told by one of its most eminent practitioners. Cognitive science is the project of understanding the mind by modeling its workings. Psychology is its heart, but it draws together various adjoining fields of research, including artificial intelligence; neuroscientific study of the brain; philosophical investigation of mind, language, logic, and understanding; computational work on logic and reasoning; linguistic research on grammar, semantics, and communication; and anthropological explorations of human similarities and differences. Each discipline, in its own way, asks what the mind is, what it does, how it works, how it developed - how it is even possible. The key distinguishing characteristic of cognitive science, Boden suggests, compared with older ways of thinking about the mind, is the notion of understanding the mind as a kind of machine. She traces the origins of cognitive science back to Descartes's revolutionary ideas, and follows the story through the eighteenth and nineteenth centuries, when the pioneers of psychology and computing appear. Then she guides the reader through the complex interlinked paths along which the study of the mind developed in the twentieth century. Cognitive science, in Boden's broad conception, covers a wide range of aspects of mind: not just 'cognition' in the sense of knowledge or reasoning, but emotion, personality, social communication, and even action. In each area of investigation, Boden introduces the key ideas and the people who developed them. No one else could tell this story as Boden can: she has been an active participant in cognitive science since the 1960s, and has known many of the key figures personally. Her narrative is written in a lively, swift-moving style, enriched by the personal touch of someone who knows the story at first hand. Her history looks forward as well as back: it is her conviction that cognitive science today--and tomorrow--cannot be properly understood without a historical perspective. Mind as Machine will be a rich resource for anyone working on the mind, in any academic discipline, who wants to know how our understanding of our mental activities and capacities has developed. |
| example of artificial intelligence in psychology: Biomedical Informatics Edward H. Shortliffe, James J. Cimino, 2013-12-02 The practice of modern medicine and biomedical research requires sophisticated information technologies with which to manage patient information, plan diagnostic procedures, interpret laboratory results, and carry out investigations. Biomedical Informatics provides both a conceptual framework and a practical inspiration for this swiftly emerging scientific discipline at the intersection of computer science, decision science, information science, cognitive science, and biomedicine. Now revised and in its third edition, this text meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. Authored by leaders in medical informatics and extensively tested in their courses, the chapters in this volume constitute an effective textbook for students of medical informatics and its areas of application. The book is also a useful reference work for individual readers needing to understand the role that computers can play in the provision of clinical services and the pursuit of biological questions. The volume is organized so as first to explain basic concepts and then to illustrate them with specific systems and technologies. |
| example of artificial intelligence in psychology: Artificial Intelligence in Psychology Margaret A. Boden, 1989 This collection of Margaret Boden's essays written between 1982 and 1988 focuses on the relevance of artificial intelligence to psychology. With her usual clarity and eye for the key role that each discipline plays in the science of the mind, Boden ties the essays together in a thorough synoptic overview. She outlines the various approaches, from Babbage's contributions, through the work of Turing and von Neumann, to the latest theories of parallel processing, and the questions that researchers in AI and psychology must ask to ascertain if there might be a discipline termed computational psychology Many theoretical psychologists today believe that the science of artificial intelligence can include all of the phenomena generated by the human mind. This functionalist approach views the mind as a representational system and psychology as the study of the various computational processes whereby mental representations are constructed, organized, and interpreted. Disagreements abound, however, about how various psychological phenomena can be explained in computational terms; there is disagreement, too, about which AI concepts and which of the computermodeling methodologies will prove most useful from the psychologist's point of view. All of these issues are raised and clearly investigated here. The essays include Fashions of Mind; Is Computational Psychology Constructivist? Does Artificial Intelligence Need Artificial Brains? Intentionality and Physical Systems; Escaping from the Chinese Room; Is Equilibration Important? Artificial Intelligence and Biological Intelligence. Educational Implications of Artificial Intelligence. Margaret A Boden is Professor of Philosophy and Psychology, and Founding Dean of the School of Cognitive Sciences at the University of Sussex. Artificial Intelligence in Psychology is included in the series Explorations in Cognitive Science, A Bradford Book |
| example of artificial intelligence in psychology: Artificial Intelligence For Dummies John Paul Mueller, Luca Massaron, 2018-03-16 Step into the future with AI The term Artificial Intelligence has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in the news, books, movies, and TV shows, and the exact definition is often misinterpreted. Artificial Intelligence For Dummies provides a clear introduction to AI and how it’s being used today. Inside, you’ll get a clear overview of the technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field. Learn about what AI has contributed to society Explore uses for AI in computer applications Discover the limits of what AI can do Find out about the history of AI The world of AI is fascinating—and this hands-on guide makes it more accessible than ever! |
| example of artificial intelligence in psychology: The Cyber Effect Mary Aiken, 2016 From one of the world's leading experts in cyberpsychology--a discipline that combines psychology, forensics, and technology--comes a groundbreaking exploration of the impact of technology on human behavior. In the first book of its kind, Mary Aiken applies her expertise in cyber-behavioral analysis to a range of subjects, including criminal activity on the Deep Web and Darknet; deviant behavior; Internet addictions; the impact of technology on the developing child; teenagers and the Web; cyber-romance and cyber-friendships; cyberchondria; the future of artificial intelligence; and the positive effects on our digital selves, such as online altruism-- |
| example of artificial intelligence in psychology: Cognitive Psychology Michael W. Eysenck, Mark T. Keane, 2000 This is a thorough revision and updating of the extremely successful third edition. As in previous editions, the following three perspectives are considered in depth: experimental cognitive psychology; cognitive science, with its focus on cognitive modelling; and cognitive neuropsychology with its focus on cognition following brain damage. In addition, and new to this edition, is detailed discussion of the cognitive neuroscience perspective, which uses advanced brain-scanning techniques to clarify the functioning of the human brain. There is detailed coverage of the dynamic impact of these four perspectives on the main areas of cognitive psychology, including perception, attention, memory, knowledge representation, categorisation, language, problem-solving, reasoning, and judgement. The aim is to provide comprehensive coverage that is up-to-date, authoritative, and accessible. All existing chapters have been extensively revised and re-organised. Some of the topics receiving much greater coverage in this edition are: brain structures in perception, visual attention, implicit learning, brain structures in memory, prospective memory, exemplar theories of categorisation, language comprehension, connectionist models in perception, neuroscience studies of thinking, judgement, and decision making. Cognitive Psychology: A Students Handbookwill be essential reading for undergraduate students of psychology. It will also be of interest to students taking related courses in computer science, education, linguistics, physiology, and medicine. |
| example of artificial intelligence in psychology: Information Retrieval Architecture and Algorithms Gerald Kowalski, 2010-12-01 This text presents a theoretical and practical examination of the latest developments in Information Retrieval and their application to existing systems. By starting with a functional discussion of what is needed for an information system, the reader can grasp the scope of information retrieval problems and discover the tools to resolve them. The book takes a system approach to explore every functional processing step in a system from ingest of an item to be indexed to displaying results, showing how implementation decisions add to the information retrieval goal, and thus providing the user with the needed outcome, while minimizing their resources to obtain those results. The text stresses the current migration of information retrieval from just textual to multimedia, expounding upon multimedia search, retrieval and display, as well as classic and new textual techniques. It also introduces developments in hardware, and more importantly, search architectures, such as those introduced by Google, in order to approach scalability issues. About this textbook: A first course text for advanced level courses, providing a survey of information retrieval system theory and architecture, complete with challenging exercises Approaches information retrieval from a practical systems view in order for the reader to grasp both scope and solutions Features what is achievable using existing technologies and investigates what deficiencies warrant additional exploration |
| example of artificial intelligence in psychology: Application of Artificial Intelligence to Assessment Hong Jiao, Robert W. Lissitz, 2020-03-01 The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased. Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers’ engagement in testing. In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices. |
| example of artificial intelligence in psychology: The Great Mental Models, Volume 1 Shane Parrish, Rhiannon Beaubien, 2024-10-15 Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage. |
| example of artificial intelligence in psychology: Noise Daniel Kahneman, Olivier Sibony, Cass R. Sunstein, 2021-05-18 From the Nobel Prize-winning author of Thinking, Fast and Slow and the coauthor of Nudge, a revolutionary exploration of why people make bad judgments and how to make better ones—a tour de force” (New York Times). Imagine that two doctors in the same city give different diagnoses to identical patients—or that two judges in the same courthouse give markedly different sentences to people who have committed the same crime. Suppose that different interviewers at the same firm make different decisions about indistinguishable job applicants—or that when a company is handling customer complaints, the resolution depends on who happens to answer the phone. Now imagine that the same doctor, the same judge, the same interviewer, or the same customer service agent makes different decisions depending on whether it is morning or afternoon, or Monday rather than Wednesday. These are examples of noise: variability in judgments that should be identical. In Noise, Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein show the detrimental effects of noise in many fields, including medicine, law, economic forecasting, forensic science, bail, child protection, strategy, performance reviews, and personnel selection. Wherever there is judgment, there is noise. Yet, most of the time, individuals and organizations alike are unaware of it. They neglect noise. With a few simple remedies, people can reduce both noise and bias, and so make far better decisions. Packed with original ideas, and offering the same kinds of research-based insights that made Thinking, Fast and Slow and Nudge groundbreaking New York Times bestsellers, Noise explains how and why humans are so susceptible to noise in judgment—and what we can do about it. |
| example of artificial intelligence in psychology: George Eliot's Intellectual Life Avrom Fleishman, 2010-02-18 It is well known that George Eliot's intelligence and her wide knowledge of literature, history, philosophy and religion shaped her fiction, but until now no study has followed the development of her thinking through her whole career. This intellectual biography traces the course of that development from her initial Christian culture, through her loss of faith and working out of a humanistic and cautiously progressive world view, to the thought-provoking achievements of her novels. It focuses on her responses to her reading in her essays, reviews and letters as well as in the historical pictures of Romola, the political implications of Felix Holt, the comprehensive view of English society in Middlemarch, and the visionary account of personal inspiration in Daniel Deronda. This portrait of a major Victorian intellectual is an important addition to our understanding of Eliot's mind and works, as well as of her place in nineteenth-century British culture. |
| example of artificial intelligence in psychology: Computer-Based Medical Consultations: MYCIN Edward Shortliffe, 2012-12-02 Computer-Based Medical Consultations: MYCIN focuses on MYCIN, a novel computer-based expert system designed to assist physicians with clinical decisions concerning the selection of appropriate therapy for patients with infections. It discusses medical computing, artificial intelligence, and the clinical problem areas for which the MYCIN program is designed, and it describes in detail how the MYCIN program helps physicians in making decisions. Comprised of seven chapters, this volume begins with an overview of MYCIN and the criteria used in its design. It then discusses data structures and control structures in the context of prior work regarding rule-based problem-solving, inferential model building and inexact reasoning in medicine. The book also explores MYCIN'S ability to answer questions with respect to its knowledge base and the details of a specific consultation, evaluation and future extensions of the MYCIN system, the limitations and accomplishments of MYCIN, and its contributions in artificial intelligence and computer-based medical decision making. This book is a valuable source of information for computer scientists and members of the medical community. |
| example of artificial intelligence in psychology: Artificial Intelligence versus Human Intelligence Christian Lexcellent, 2019-05-31 This book showcases the fascinating but problematic relationship between human intelligence and artificial intelligence: AI is often discussed in the media, as if bodiless intelligence could exist, without a consciousness, without an unconscious, without thoughts. Using a wealth of anecdotes, data from academic literature, and original research, this short book examines in what circumstances robots can replace humans, and demonstrates that by operating beyond direct human control, strong artificial intelligence may pose serious problems, paving the way for all manner of extrapolations, for example implanting silicon chips in the brains of a privileged caste, and exposing the significant gap still present between the proponents of singularity and certain philosophers. With insights from mathematics, cognitive neuroscience and philosophy, it enables readers to understand and continue this open debate on AI, which presents concrete ethical problems for which meaningful answers are still in their infancy. |
| example of artificial intelligence in psychology: Rebooting AI Gary Marcus, Ernest Davis, 2019-09-10 Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a robust artificial intelligence that can make our lives better. “Finally, a book that tells us what AI is, what AI is not, and what AI could become if only we are ambitious and creative enough.” —Garry Kasparov, former world chess champion and author of Deep Thinking Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust—in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better. |
| example of artificial intelligence in psychology: Artificial Minds Stan Franklin, 1997 Stan Franklin is the perfect tour guide through the contemporary interdisciplinary matrix of artificial intelligence, cognitive science, cognitive neuroscience, artificial neural networks, artificial life, and robotics that is producing a new paradigm of mind. Along the way, Franklin makes the case for a perspective that rejects a rigid distinction between mind and non-mind in favor of a continuum from less to more mind. |
| example of artificial intelligence in psychology: A Program for the Solution of a Class of Geometric-analogy Intelligence-test Questions Thomas G. Evans, 1964 The novel organization of the program in terms of figure descriptions, which are analyzed to find transformation rules, and rule descriptions, which are analyzed to find 'common generalizations' of pairs of transformation rules, has implications for the design of problem-solving programs and for machine learning. These implications are discussed at some length and suggestions are made for work on pattern-recognition and learning techniques based on ideas developed in the course of the present investigation. |
| example of artificial intelligence in psychology: Outsmarting IQ David Perkins, 1995-03-01 Since the turn of the century, the idea that intellectual capacity is fixed has been generally accepted. But increasingly, psychologists, educators, and others have come to challenge this premise. Outsmarting IQ reveals how earlier discoveries about IQ, together with recent research, show that intelligence is not genetically fixed. Intelligence can be taught. David Perkins, renowned for his research on thinking, learning, and education, identifies three distinct kinds of intelligence: the fixed neurological intelligence linked to IQ tests; the specialized knowledge and experience that individuals acquire over time; and reflective intelligence, the ability to become aware of one's mental habits and transcend limited patterns of thinking. Although all of these forms of intelligence function simultaneously, it is reflective intelligence, Perkins shows, that affords the best opportunity to amplify human intellect. This is the kind of intelligence that helps us to make wise personal decisions, solve challenging technical problems, find creative ideas, and learn complex topics in mathematics, the sciences, management, and other areas. It is the kind of intelligence most needed in an increasingly competitive and complicated world. Using his own pathbreaking research at Harvard and a rich array of other sources, Perkins paints a compelling picture of the skills and attitudes underlying learnable intelligence. He identifies typical pitfalls in multiple perspectives, and neglecting evidence. He reveals the underlying mechanisms of intelligent behavior. And he explores new frontiers in the development of intelligence in education, business, and other settings. This book will be of interest to people who have a personal or professional stake in increasing their intellectual skills, to those who look toward better education and a more thoughtful society, and not least to those who follow today's heated debates about the nature of intelligence. |
| example of artificial intelligence in psychology: The SAGE Handbook of Evolutionary Psychology Todd K. Shackelford, 2021-08-04 Evolutionary psychology is an important and rapidly expanding area in the life, social, and behavioral sciences, and this Handbook represents the most comprehensive and up-to-date reference text in the field today. Over three volumes, the Handbook provides a rich overview of the most important theoretical and empirical work in the field. Chapters cover a broad range of topics, including theoretical foundations, the integration of evolutionary psychology with other life, social, and behavioral sciences, as well as with the arts and the humanities, and the increasing power of evolutionary psychology to inform applied fields, including medicine, psychiatry, law, and education. Each of the volumes has been carefully curated to have a strong thematic focus, covering: - The foundations of evolutionary psychology; - The integration of evolutionary psychology with other disciplines, and; - The applications of evolutionary psychology. The SAGE Handbook of Evolutionary Psychology is an essential resource for researchers, graduate students, and advanced undergraduate students in all areas of psychology, and in related disciplines across the life, social, and behavioral sciences. |
| example of artificial intelligence in psychology: An Introduction to Artificial Psychology Hojjatollah Farahani, Marija Blagojević, Parviz Azadfallah, Peter Watson, Forough Esrafilian, Sara Saljoughi, 2023-05-18 Artificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep rooted limitations. These approaches are excellent on paper but often fail to model the real world. Mind researchers have been trying to overcome this by simplifying the models being studied. This stance has not received much practical attention recently. Promoting and improving artificial intelligence helps mind researchers to find a holistic model of mental models. This development achieves this goal by using multiple perspectives and multiple data sets together with interactive, and realistic models. In this book, the methodology of approximate inference in psychological research from a theoretical and practical perspective has been considered. Quantitative variable-oriented methodology and qualitative case-oriented methods are both used to explain the set-oriented methodology and this book combines the precision of quantitative methods with information from qualitative methods. This is a book that many researchers can use to expand and deepen their psychological research and is a book which can be useful to postgraduate students. The reader does not need an in-depth knowledge of mathematics or statistics because statistical and mathematical intuitions are key here and they will be learned through practice. What is important is to understand and use the new application of the methods for finding new, dynamic and realistic interpretations. This book incorporates theoretical fuzzy inference and deep machine learning algorithms in practice. This is the kind of book that we wished we had had when we were students. This book covers at least some of the most important issues in mind research including uncertainty, fuzziness, continuity, complexity and high dimensionality which are inherent to mind data. These are elements of artificial psychology. This book implements models using R software. |
| example of artificial intelligence in psychology: Bots and Beasts Paul Thagard, 2021-10-19 An expert on mind considers how animals and smart machines measure up to human intelligence. Octopuses can open jars to get food, and chimpanzees can plan for the future. An IBM computer named Watson won on Jeopardy! and Alexa knows our favorite songs. But do animals and smart machines really have intelligence comparable to that of humans? In Bots and Beasts, Paul Thagard looks at how computers (bots) and animals measure up to the minds of people, offering the first systematic comparison of intelligence across machines, animals, and humans. Thagard explains that human intelligence is more than IQ and encompasses such features as problem solving, decision making, and creativity. He uses a checklist of twenty characteristics of human intelligence to evaluate the smartest machines--including Watson, AlphaZero, virtual assistants, and self-driving cars--and the most intelligent animals--including octopuses, dogs, dolphins, bees, and chimpanzees. Neither a romantic enthusiast for nonhuman intelligence nor a skeptical killjoy, Thagard offers a clear assessment. He discusses hotly debated issues about animal intelligence concerning bacterial consciousness, fish pain, and dog jealousy. He evaluates the plausibility of achieving human-level artificial intelligence and considers ethical and policy issues. A full appreciation of human minds reveals that current bots and beasts fall far short of human capabilities. |
EXAMPLE Definition & Meaning - Merriam-Webster
The meaning of EXAMPLE is one that serves as a pattern to be imitated or not to be imitated. How to use example in a sentence. Synonym Discussion of Example.
EXAMPLE | English meaning - Cambridge Dictionary
EXAMPLE definition: 1. something that is typical of the group of things that it is a member of: 2. a way of helping…. Learn more.
EXAMPLE Definition & Meaning | Dictionary.com
one of a number of things, or a part of something, taken to show the character of the whole. This painting is an example of his early work. a pattern or model, as of something to be imitated or …
Example - definition of example by The Free Dictionary
1. one of a number of things, or a part of something, taken to show the character of the whole. 2. a pattern or model, as of something to be imitated or avoided: to set a good example. 3. an …
Example Definition & Meaning - YourDictionary
To be illustrated or exemplified (by). Wear something simple; for example, a skirt and blouse.
EXAMPLE - Meaning & Translations | Collins English Dictionary
An example of something is a particular situation, object, or person which shows that what is being claimed is true. 2. An example of a particular class of objects or styles is something that …
example noun - Definition, pictures, pronunciation and usage …
used to emphasize something that explains or supports what you are saying; used to give an example of what you are saying. There is a similar word in many languages, for example in …
Example - Definition, Meaning & Synonyms - Vocabulary.com
An example is a particular instance of something that is representative of a group, or an illustration of something that's been generally described. Example comes from the Latin word …
example - definition and meaning - Wordnik
noun Something that serves as a pattern of behaviour to be imitated (a good example) or not to be imitated (a bad example). noun A person punished as a warning to others. noun A parallel …
EXAMPLE Synonyms: 20 Similar Words - Merriam-Webster
Some common synonyms of example are case, illustration, instance, sample, and specimen. While all these words mean "something that exhibits distinguishing characteristics in its …
EXAMPLE Definition & Meaning - Merriam-Webster
The meaning of EXAMPLE is one that serves as a pattern to be imitated or not to be imitated. How to use example in a sentence. Synonym Discussion of Example.
EXAMPLE | English meaning - Cambridge Dictionary
EXAMPLE definition: 1. something that is typical of the group of things that it is a member of: 2. a way of helping…. Learn more.
EXAMPLE Definition & Meaning | Dictionary.com
one of a number of things, or a part of something, taken to show the character of the whole. This painting is an example of his early work. a pattern or model, as of something to be imitated or …
Example - definition of example by The Free Dictionary
1. one of a number of things, or a part of something, taken to show the character of the whole. 2. a pattern or model, as of something to be imitated or avoided: to set a good example. 3. an …
Example Definition & Meaning - YourDictionary
To be illustrated or exemplified (by). Wear something simple; for example, a skirt and blouse.
EXAMPLE - Meaning & Translations | Collins English Dictionary
An example of something is a particular situation, object, or person which shows that what is being claimed is true. 2. An example of a particular class of objects or styles is something that has …
example noun - Definition, pictures, pronunciation and usage notes ...
used to emphasize something that explains or supports what you are saying; used to give an example of what you are saying. There is a similar word in many languages, for example in French …
Example - Definition, Meaning & Synonyms - Vocabulary.com
An example is a particular instance of something that is representative of a group, or an illustration of something that's been generally described. Example comes from the Latin word for …
example - definition and meaning - Wordnik
noun Something that serves as a pattern of behaviour to be imitated (a good example) or not to be imitated (a bad example). noun A person punished as a warning to others. noun A parallel or …
EXAMPLE Synonyms: 20 Similar Words - Merriam-Webster
Some common synonyms of example are case, illustration, instance, sample, and specimen. While all these words mean "something that exhibits distinguishing characteristics in its category," …
