Towards a Code of Ethics for Artificial Intelligence
The author investigates how to produce realistic and workable ethical codes or regulations in this rapidly developing field to address the immediate and realistic longer-term issues facing us. She spells out the key ethical debates concisely, exposing all
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Paula Boddington
Towards a Code of Ethics for Artificial Intelligence
Artificial Intelligence: Foundations, Theory, and Algorithms
Series editors Barry O’Sullivan, Cork, Ireland Michael Wooldridge, Oxford, United Kingdom
More information about this series at http://www.springer.com/series/13900
Paula Boddington
Towards a Code of Ethics for Artificial Intelligence
Paula Boddington Dept of Computer Science University of Oxford Oxford, United Kingdom
ISSN 2365-3051 ISSN 2365-306X (electronic) Artificial Intelligence: Foundations, Theory, and Algorithms ISBN 978-3-319-60647-7 ISBN 978-3-319-60648-4 (eBook) DOI 10.1007/978-3-319-60648-4 Library of Congress Control Number: 2017950394 © Springer International Publishing AG 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
This work is dedicated to the memory of my dear friend and colleague, Professor Pamela Sue Anderson, 1955–2017
Foreword
Few academic disciplines have suffered as many reversals of fortune as artificial intelligence (AI). Early AI researchers seemed to make rapid progress and became convinced that they were on the fast track to the grand dreams of AI—only to find that progress petered out, amid claims that AI was nothing more than modern-day alchemy. Successive waves of subsequent AI technologies have promised progress, but in the end progress proved possible only on very narrow problems. We are currently in one of the periodic boom times for AI. There has been genuinely impressive progress in the area of machine learning, prompted in part by the availability of cheap computer power and big data and in part by scientific breakthroughs. This progress has caused mas
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