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Author: Paul R. Cohen
Publisher: Bradford Books
Published: 1995
Total Pages: 405
ISBN-13: 9780262032254
DOWNLOAD EBOOKThis book presents empirical methods for studying complex computer programs: exploratory tools to help find patterns in data, experiment designs and hypothesis-testing tools to help data speak convincingly, and modeling tools to help explain data.
Author: Bernd Carsten Stahl
Publisher: Springer Nature
Published: 2021-03-17
Total Pages: 128
ISBN-13: 3030699781
DOWNLOAD EBOOKThis open access book proposes a novel approach to Artificial Intelligence (AI) ethics. AI offers many advantages: better and faster medical diagnoses, improved business processes and efficiency, and the automation of boring work. But undesirable and ethically problematic consequences are possible too: biases and discrimination, breaches of privacy and security, and societal distortions such as unemployment, economic exploitation and weakened democratic processes. There is even a prospect, ultimately, of super-intelligent machines replacing humans. The key question, then, is: how can we benefit from AI while addressing its ethical problems? This book presents an innovative answer to the question by presenting a different perspective on AI and its ethical consequences. Instead of looking at individual AI techniques, applications or ethical issues, we can understand AI as a system of ecosystems, consisting of numerous interdependent technologies, applications and stakeholders. Developing this idea, the book explores how AI ecosystems can be shaped to foster human flourishing. Drawing on rich empirical insights and detailed conceptual analysis, it suggests practical measures to ensure that AI is used to make the world a better place.
Author: Robert R. Hoffman
Publisher: Psychology Press
Published: 2014-02-25
Total Pages: 622
ISBN-13: 1317779533
DOWNLOAD EBOOKThis volume investigates our ability to capture, and then apply, expertise. In recent years, expertise has come to be regarded as an increasingly valuable and surprisingly elusive resource. Experts, who were the sole active dispensers of certain kinds of knowledge in the days before AI, have themselves become the objects of empirical inquiry, in which their knowledge is elicited and studied -- by knowledge engineers, experimental psychologists, applied psychologists, or other experts -- involved in the development of expert systems. This book achieves a marriage between experimentalists, applied scientists, and theoreticians who deal with expertise. It envisions the benefits to society of an advanced technology for capturing and disseminating the knowledge and skills of the best corporate managers, the most seasoned pilots, and the most renowned medical diagnosticians. This book should be of interest to psychologists as well as to knowledge engineers who are "out in the trenches" developing expert systems, and anyone pondering the nature of expertise and the question of how it can be elicited and studied scientifically. The book's scope and the pivotal concepts that it elucidates and appraises, as well as the extensive categorized bibliographies it includes, make this volume a landmark in the field of expert systems and AI as well as the field of applied experimental psychology.
Author: Paul R. Cohen
Publisher:
Published: 2004
Total Pages: 405
ISBN-13: 9788120325319
DOWNLOAD EBOOKAuthor: Bernhard Schölkopf
Publisher: Springer Science & Business Media
Published: 2013-12-11
Total Pages: 295
ISBN-13: 3642411363
DOWNLOAD EBOOKThis book honours the outstanding contributions of Vladimir Vapnik, a rare example of a scientist for whom the following statements hold true simultaneously: his work led to the inception of a new field of research, the theory of statistical learning and empirical inference; he has lived to see the field blossom; and he is still as active as ever. He started analyzing learning algorithms in the 1960s and he invented the first version of the generalized portrait algorithm. He later developed one of the most successful methods in machine learning, the support vector machine (SVM) – more than just an algorithm, this was a new approach to learning problems, pioneering the use of functional analysis and convex optimization in machine learning. Part I of this book contains three chapters describing and witnessing some of Vladimir Vapnik's contributions to science. In the first chapter, Léon Bottou discusses the seminal paper published in 1968 by Vapnik and Chervonenkis that lay the foundations of statistical learning theory, and the second chapter is an English-language translation of that original paper. In the third chapter, Alexey Chervonenkis presents a first-hand account of the early history of SVMs and valuable insights into the first steps in the development of the SVM in the framework of the generalised portrait method. The remaining chapters, by leading scientists in domains such as statistics, theoretical computer science, and mathematics, address substantial topics in the theory and practice of statistical learning theory, including SVMs and other kernel-based methods, boosting, PAC-Bayesian theory, online and transductive learning, loss functions, learnable function classes, notions of complexity for function classes, multitask learning, and hypothesis selection. These contributions include historical and context notes, short surveys, and comments on future research directions. This book will be of interest to researchers, engineers, and graduate students engaged with all aspects of statistical learning.
Author: Barry Boehm
Publisher: Springer Science & Business Media
Published: 2005-05-13
Total Pages: 452
ISBN-13: 9783540245476
DOWNLOAD EBOOKAlthough software engineering can trace its beginnings to a NATO conf- ence in 1968, it cannot be said to have become an empirical science until the 1970s with the advent of the work of Prof. Victor Robert Basili of the University of Maryland. In addition to the need to engineer software was the need to understand software. Much like other sciences, such as physics, chemistry, and biology, software engineering needed a discipline of obs- vation, theory formation, experimentation, and feedback. By applying the scientific method to the software engineering domain, Basili developed concepts like the Goal-Question-Metric method, the Quality-Improvement- Paradigm, and the Experience Factory to help bring a sense of order to the ad hoc developments so prevalent in the software engineering field. On the occasion of Basili’s 65th birthday, we present this book c- taining reprints of 20 papers that defined much of his work. We divided the 20 papers into 6 sections, each describing a different facet of his work, and asked several individuals to write an introduction to each section. Instead of describing the scope of this book in this preface, we decided to let one of his papers, the keynote paper he gave at the International C- ference on Software Engineering in 1996 in Berlin, Germany to lead off this book. He, better than we, can best describe his views on what is - perimental software engineering.
Author: Jack Copeland
Publisher: John Wiley & Sons
Published: 2015-07-29
Total Pages: 331
ISBN-13: 1119189845
DOWNLOAD EBOOKPresupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding. There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. John Searle's attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer.
Author: J.H. Fetzer
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 386
ISBN-13: 9400926995
DOWNLOAD EBOOKThis series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data-processing systems of all kinds, no matter whether human, (other) animal or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual and epistemological aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. The present volume illustrates the approach represented by this series. It addresses fundamental questions lying at the heart of artificial intelligence, including those of the relative virtues of computational and of non-computational conceptions of language and of mind, whether AI should be envisioned as a philosophical or as a scientific discipline, the theoretical character of patterns of inference and modes of argumenta tion (especially, defeasible and inductive reasoning), and the relations that may obtain between AI and epistemology. Alternative positions are developed in detail and subjected to vigorous debate in the justifiable expectation that - here as elsewhere - critical inquiry provides the most promising path to discovering the truth about ourselves and the world around us. lH.F.
Author:
Publisher:
Published: 1992
Total Pages: 395
ISBN-13:
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