An AI Threats Bibliography "AI Principles". Future of Life Institute
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Artificial Intelligence: What Is It, Can It Be Leveraged, and What Are the Ramifications?
ARTIFICIAL INTELLIGENCE: WHAT IS IT, CAN IT BE LEVERAGED, AND WHAT ARE THE RAMIFICATIONS? Major James R. Barker JCSP 45 PCEMI 45 Service Paper Étude militaire Disclaimer Avertissement Opinions expressed remain those of the author and do Les opinons exprimées n’engagent que leurs auteurs et not represent Department of National Defence or ne reflètent aucunement des politiques du Ministère de Canadian Forces policy. This paper may not be used la Défense nationale ou des Forces canadiennes. Ce without written permission. papier ne peut être reproduit sans autorisation écrite © Her Majesty the Queen in Right of Canada, as represented by the © Sa Majesté la Reine du Chef du Canada, représentée par le Minister of National Defence, 2019. ministre de la Défense nationale, 2019. CANADIAN FORCES COLLEGE/COLLÈGE DES FORCES CANADIENNES JCSP 45 OCTOBER 15 2018 DS545 COMPONENT CAPABILITIES ARTIFICIAL INTELLIGENCE: WHAT IS IT, CAN IT BE LEVERAGED, AND WHAT ARE THE RAMIFICATIONS? By Major James R. Barker “This paper was written by a candidate « La présente étude a été rédigée par un attending the Canadian Force College in stagiaire du Collège des Forces fulfillment of one of the requirements of the canadiennes pour satisfaire à l’une des exigences du cours. L’étude est un Course of Studies. The paper is a scholastic document qui se rapporte au cours et document, and thus contains facts and Contient donc des faits et des opinions que opinions which the author alone considered seul l’auteur considère appropriés et appropriate and correct for the subject. It convenables au sujet. Elle ne reflète pas does not necessarily reflect the policy or the nécessairement la politique ou l’opinion opinion of any agency, including Government d’un organisme quelconque, y compris le of Canada and the Canadian Department of gouvernement du Canada et le ministère de la Défense nationale du Canada. -
Copyrighted Material
Index affordances 241–2 apps 11, 27–33, 244–5 afterlife 194, 227, 261 Ariely, Dan 28 Agar, Nicholas 15, 162, 313 Aristotle 154, 255 Age of Spiritual Machines, The 47, 54 Arkin, Ronald 64 AGI (Artificial General Intelligence) Armstrong, Stuart 12, 311 61–86, 98–9, 245, 266–7, Arp, Hans/Jean 240–2, 246 298, 311 artificial realities, see virtual reality AGI Nanny 84, 311 Asimov, Isaac 45, 268, 274 aging 61, 207, 222, 225, 259, 315 avatars 73, 76, 201, 244–5, 248–9 AI (artificial intelligence) 3, 9, 12, 22, 30, 35–6, 38–44, 46–58, 72, 91, Banks, Iain M. 235 95, 99, 102, 114–15, 119, 146–7, Barabási, Albert-László 311 150, 153, 157, 198, 284, 305, Barrat, James 22 311, 315 Berger, T.W. 92 non-determinism problem 95–7 Bernal,J.D.264–5 predictions of 46–58, 311 biological naturalism 124–5, 128, 312 altruism 8 biological theories of consciousness 14, Amazon Elastic Compute Cloud 40–1 104–5, 121–6, 194, 312 Andreadis, Athena 223 Blackford, Russell 16–21, 318 androids 44, 131, 194, 197, 235, 244, Blade Runner 21 265, 268–70, 272–5, 315 Block, Ned 117, 265 animal experimentationCOPYRIGHTED 24, 279–81, Blue Brain MATERIAL Project 2, 180, 194, 196 286–8, 292 Bodington, James 16, 316 animal rights 281–2, 285–8, 316 body, attitudes to 4–5, 222–9, 314–15 Anissimov, Michael 12, 311 “Body by Design” 244, 246 Intelligence Unbound: The Future of Uploaded and Machine Minds, First Edition. Edited by Russell Blackford and Damien Broderick. -
Classification Schemas for Artificial Intelligence Failures
Journal XX (XXXX) XXXXXX https://doi.org/XXXX/XXXX Classification Schemas for Artificial Intelligence Failures Peter J. Scott1 and Roman V. Yampolskiy2 1 Next Wave Institute, USA 2 University of Louisville, Kentucky, USA [email protected], [email protected] Abstract In this paper we examine historical failures of artificial intelligence (AI) and propose a classification scheme for categorizing future failures. By doing so we hope that (a) the responses to future failures can be improved through applying a systematic classification that can be used to simplify the choice of response and (b) future failures can be reduced through augmenting development lifecycles with targeted risk assessments. Keywords: artificial intelligence, failure, AI safety, classification 1. Introduction Artificial intelligence (AI) is estimated to have a $4-6 trillion market value [1] and employ 22,000 PhD researchers [2]. It is estimated to create 133 million new roles by 2022 but to displace 75 million jobs in the same period [6]. Projections for the eventual impact of AI on humanity range from utopia (Kurzweil, 2005) (p.487) to extinction (Bostrom, 2005). In many respects AI development outpaces the efforts of prognosticators to predict its progress and is inherently unpredictable (Yampolskiy, 2019). Yet all AI development is (so far) undertaken by humans, and the field of software development is noteworthy for unreliability of delivering on promises: over two-thirds of companies are more likely than not to fail in their IT projects [4]. As much effort as has been put into the discipline of software safety, it still has far to go. Against this background of rampant failures we must evaluate the future of a technology that could evolve to human-like capabilities, usually known as artificial general intelligence (AGI). -
On the Differences Between Human and Machine Intelligence
On the Differences between Human and Machine Intelligence Roman V. Yampolskiy Computer Science and Engineering, University of Louisville [email protected] Abstract [Legg and Hutter, 2007a]. However, widespread implicit as- Terms Artificial General Intelligence (AGI) and Hu- sumption of equivalence between capabilities of AGI and man-Level Artificial Intelligence (HLAI) have been HLAI appears to be unjustified, as humans are not general used interchangeably to refer to the Holy Grail of Ar- intelligences. In this paper, we will prove this distinction. tificial Intelligence (AI) research, creation of a ma- Others use slightly different nomenclature with respect to chine capable of achieving goals in a wide range of general intelligence, but arrive at similar conclusions. “Lo- environments. However, widespread implicit assump- cal generalization, or “robustness”: … “adaptation to tion of equivalence between capabilities of AGI and known unknowns within a single task or well-defined set of HLAI appears to be unjustified, as humans are not gen- tasks”. … Broad generalization, or “flexibility”: “adapta- eral intelligences. In this paper, we will prove this dis- tion to unknown unknowns across a broad category of re- tinction. lated tasks”. …Extreme generalization: human-centric ex- treme generalization, which is the specific case where the 1 Introduction1 scope considered is the space of tasks and domains that fit within the human experience. We … refer to “human-cen- Imagine that tomorrow a prominent technology company tric extreme generalization” as “generality”. Importantly, as announces that they have successfully created an Artificial we deliberately define generality here by using human cog- Intelligence (AI) and offers for you to test it out. -
The Forthcoming Artificial Intelligence (AI) Revolution: Its Impact on Society
Futures 90 (2017) 46–60 Contents lists available at ScienceDirect Futures journal homepage: www.elsevier.com/locate/futures Review The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms Professor Spyros Makridakis Director Institute For the Future (IFF), University of Nicosia, Cyprus A R T I C L E I N F O A B S T R A C T Article history: Received 10 January 2017 The impact of the industrial and digital (information) revolutions has, undoubtedly, been Received in revised form 17 March 2017 substantial on practically all aspects of our society, life, firms and employment. Will the Accepted 28 March 2017 forthcoming AI revolution produce similar, far-reaching effects? By examining analogous Available online 3 April 2017 inventions of the industrial, digital and AI revolutions, this article claims that the latter is on target and that it would bring extensive changes that will also affect all aspects of our Keywords: society and life. In addition, its impact on firms and employment will be considerable, Artificial Intelligence (AI) resulting in richly interconnected organizations with decision making based on the Industrial revolution analysis and exploitation of “big” data and intensified, global competition among firms. Digital revolution People will be capable of buying goods and obtaining services from anywhere in the world AI revolution using the Internet, and exploiting the unlimited, additional benefits that will open through Impact of AI revolution the widespread usage of AI inventions. The paper concludes that significant competitive Benefits and dangers of AI technologies advantages will continue to accrue to those utilizing the Internet widely and willing to take entrepreneurial risks in order to turn innovative products/services into worldwide commercial success stories. -
Public Response to RFI on AI
White House Office of Science and Technology Policy Request for Information on the Future of Artificial Intelligence Public Responses September 1, 2016 Respondent 1 Chris Nicholson, Skymind Inc. This submission will address topics 1, 2, 4 and 10 in the OSTP’s RFI: • the legal and governance implications of AI • the use of AI for public good • the social and economic implications of AI • the role of “market-shaping” approaches Governance, anomaly detection and urban systems The fundamental task in the governance of urban systems is to keep them running; that is, to maintain the fluid movement of people, goods, vehicles and information throughout the system, without which it ceases to function. Breakdowns in the functioning of these systems and their constituent parts are therefore of great interest, whether it be their energy, transport, security or information infrastructures. Those breakdowns may result from deteriorations in the physical plant, sudden and unanticipated overloads, natural disasters or adversarial behavior. In many cases, municipal governments possess historical data about those breakdowns and the events that precede them, in the form of activity and sensor logs, video, and internal or public communications. Where they don’t possess such data already, it can be gathered. Such datasets are a tremendous help when applying learning algorithms to predict breakdowns and system failures. With enough lead time, those predictions make pre- emptive action possible, action that would cost cities much less than recovery efforts in the wake of a disaster. Our choice is between an ounce of prevention or a pound of cure. Even in cases where we don’t have data covering past breakdowns, algorithms exist to identify anomalies in the data we begin gathering now. -
AI and You Transcript Guest: Roman Yampolskiy Episode 16 First Aired: Monday, October 5, 2020
AI and You Transcript Guest: Roman Yampolskiy Episode 16 First Aired: Monday, October 5, 2020 Hi, welcome to episode 16. Today we have a feast, because I am talking with Dr. Roman Yampolskiy, a legend within the AI community. He is a tenured associate professor in the department of Computer Engineering and Computer Science at the University of Louisville in Kentucky where he is the director of Cyber Security. Look up his home page and Wikipedia entry because he has qualifications too numerous to detail here. Some of those include that he is also a Visiting Fellow at the Singularity Institute, he was also one of the scientists at the Asilomar conference on the future of AI, and the author of over 100 publications, including the book Artificial Superintelligence: A Futuristic Approach, which I would strongly recommend, and many peer-reviewed papers, including one coauthored with yours truly. Most of them are on the subject of AI Safety. In this episode we will talk mostly about a recent paper of his, a table-thumping 73 pages titled “On Controllability of Artificial Intelligence,” which you may recognize is talking about what we call the Control Problem. That’s the most fundamental problem in the whole study of the long-term impact of AI, and Roman explains it very well in this episode. If you’re looking at the possible future of artificial intelligence having serious negative as well as positive consequences for everyone, which is a concept that’s gotten a lot of popularization in the last few years, of course, and you’re finding computer professionals pooh-poohing that idea because AI right now requires a great deal of specialized effort on their part to do even narrow tasks, and the idea of it becoming an existential threat is just too sensationalist, the product of watching too many Terminator movies, then pay attention to Roman, because he has impeccable computer science credentials and yet does not shy away from exploring fundamental threats of AI. -
Artificial Intelligence and Its Implications for Income Distribution
Artificial Intelligence and Its Implications ... The Economics of Artifi cial Intelligence National Bureau of Economic Research Conference Report The Economics of Artifi cial Intelligence: An Agenda Edited by Ajay Agrawal, Joshua Gans, and Avi Goldfarb The University of Chicago Press Chicago and London The University of Chicago Press, Chicago 60637 The University of Chicago Press, Ltd., London © 2019 by the National Bureau of Economic Research, Inc. All rights reserved. No part of this book may be used or reproduced in any manner whatsoever without written permission, except in the case of brief quotations in critical articles and reviews. For more information, contact the University of Chicago Press, 1427 E. 60th St., Chicago, IL 60637. Published 2019 Printed in the United States of America 28 27 26 25 24 23 22 21 20 19 1 2 3 4 5 ISBN-13: 978-0-226-61333-8 (cloth) ISBN-13: 978-0-226-61347-5 (e-book) DOI: https:// doi .org / 10 .7208 / chicago / 9780226613475 .001 .0001 Library of Congress Cataloging-in-Publication Data Names: Agrawal, Ajay, editor. | Gans, Joshua, 1968– editor. | Goldfarb, Avi, editor. Title: The economics of artifi cial intelligence : an agenda / Ajay Agrawal, Joshua Gans, and Avi Goldfarb, editors. Other titles: National Bureau of Economic Research conference report. Description: Chicago ; London : The University of Chicago Press, 2019. | Series: National Bureau of Economic Research conference report | Includes bibliographical references and index. Identifi ers: LCCN 2018037552 | ISBN 9780226613338 (cloth : alk. paper) | ISBN 9780226613475 (ebook) Subjects: LCSH: Artifi cial intelligence—Economic aspects. Classifi cation: LCC TA347.A78 E365 2019 | DDC 338.4/ 70063—dc23 LC record available at https:// lccn .loc .gov / 2018037552 ♾ This paper meets the requirements of ANSI/ NISO Z39.48-1992 (Permanence of Paper). -
The Age of Artificial Intelligence an Exploration
THE AGE OF ARTIFICIAL INTELLIGENCE AN EXPLORATION Edited by Steven S. Gouveia University of Minho, Portugal Cognitive Science and Psychology Copyright © 2020 by the Authors. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of Vernon Art and Science Inc. www.vernonpress.com In the Americas: In the rest of the world: Vernon Press Vernon Press 1000 N West Street, C/Sancti Espiritu 17, Suite 1200, Wilmington, Malaga, 29006 Delaware 19801 Spain United States Cognitive Science and Psychology Library of Congress Control Number: 2020931461 ISBN: 978-1-62273-872-4 Product and company names mentioned in this work are the trademarks of their respective owners. While every care has been taken in preparing this work, neither the authors nor Vernon Art and Science Inc. may be held responsible for any loss or damage caused or alleged to be caused directly or indirectly by the information contained in it. Every effort has been made to trace all copyright holders, but if any have been inadvertently overlooked the publisher will be pleased to include any necessary credits in any subsequent reprint or edition. Cover design by Vernon Press using elements designed by FreePik. TABLE OF CONTENTS LIST OF ACRONYMS vii LIST OF FIGURES xi LIST OF TABLES xiii INTRODUCTION xv SECTION I: INTELLIGENCE IN ARTIFICIAL INTELLIGENCE 1 CHAPTER 1 TOWARDS THE MATHEMATICS OF INTELLIGENCE 3 Soenke Ziesche Maldives National University, Maldives Roman V. Yampolskiy University of Louisville, USA CHAPTER 2 MINDS , BRAINS AND TURING 15 Stevan Harnad Université du Québec à Montréal, Canada; University of Southampton, UK CHAPTER 3 THE AGE OF POST -INTELLIGENT DESIGN 27 Daniel C. -
Leakproofing the Singularity Artificial Intelligence Confinement Problem
Roman V.Yampolskiy Leakproofing the Singularity Artificial Intelligence Confinement Problem Abstract: This paper attempts to formalize and to address the ‘leakproofing’ of the Singularity problem presented by David Chalmers. The paper begins with the definition of the Artificial Intelli- gence Confinement Problem. After analysis of existing solutions and their shortcomings, a protocol is proposed aimed at making a more secure confinement environment which might delay potential negative effect from the technological singularity while allowing humanity to benefit from the superintelligence. Keywords: AI-Box, AI Confinement Problem, Hazardous Intelligent Software, Leakproof Singularity, Oracle AI. ‘I am the slave of the lamp’ Genie from Aladdin 1. Introduction With the likely development of superintelligent programs in the near future, many scientists have raised the issue of safety as it relates to such technology (Yudkowsky, 2008; Bostrom, 2006; Hibbard, 2005; Chalmers, 2010; Hall, 2000). A common theme in Artificial Intelli- gence (AI)1 safety research is the possibility of keeping a super- intelligent agent in a sealed hardware so as to prevent it from doing any harm to humankind. Such ideas originate with scientific Correspondence: Roman V. Yampolskiy, Department of Computer Engineering and Computer Sci- ence University of Louisville. Email: [email protected] [1] In this paper the term AI is used to represent superintelligence. Journal of Consciousness Studies, 19, No. 1–2, 2012, pp. 194–214 Copyright (c) Imprint Academic 2011 For personal use only -- not for reproduction LEAKPROOFING THE SINGULARITY 195 visionaries such as Eric Drexler, who has suggested confining transhuman machines so that their outputs could be studied and used safely (Drexler, 1986). -
Agent Foundations for Aligning Machine Intelligence with Human Interests: a Technical Research Agenda
Agent Foundations for Aligning Machine Intelligence with Human Interests: A Technical Research Agenda In The Technological Singularity: Managing the Journey. Springer. 2017 Nate Soares and Benya Fallenstein Machine Intelligence Research Institute fnate,[email protected] Contents 1 Introduction 1 1.1 Why These Problems? . .2 2 Highly Reliable Agent Designs 3 2.1 Realistic World-Models . .4 2.2 Decision Theory . .5 2.3 Logical Uncertainty . .6 2.4 Vingean Reflection . .7 3 Error-Tolerant Agent Designs 8 4 Value Specification 9 5 Discussion 11 5.1 Toward a Formal Understanding of the Problem . 11 5.2 Why Start Now? . 11 1 Introduction Since artificial agents would not share our evolution- ary history, there is no reason to expect them to be The property that has given humans a dominant ad- driven by human motivations such as lust for power. vantage over other species is not strength or speed, but However, nearly all goals can be better met with more intelligence. If progress in artificial intelligence continues resources (Omohundro 2008). This suggests that, by unabated, AI systems will eventually exceed humans in default, superintelligent agents would have incentives general reasoning ability. A system that is \superintelli- to acquire resources currently being used by humanity. gent" in the sense of being \smarter than the best human (Just as artificial agents would not automatically acquire brains in practically every field” could have an enormous a lust for power, they would not automatically acquire a impact upon humanity (Bostrom 2014). Just as human human sense of fairness, compassion, or conservatism.) intelligence has allowed us to develop tools and strate- Thus, most goals would put the agent at odds with gies for controlling our environment, a superintelligent human interests, giving it incentives to deceive or ma- system would likely be capable of developing its own nipulate its human operators and resist interventions tools and strategies for exerting control (Muehlhauser designed to change or debug its behavior (Bostrom 2014, and Salamon 2012). -
Portrayals and Perceptions of AI and Why They Matter
Portrayals and perceptions of AI and why they matter 1 Portrayals and perceptions of AI and why they matter Cover Image Turk playing chess, design by Wolfgang von Kempelen (1734 – 1804), built by Christoph 2 Portrayals and perceptions of AI and why they matter Mechel, 1769, colour engraving, circa 1780. Contents Executive summary 4 Introduction 5 Narratives and artificial intelligence 5 The AI narratives project 6 AI narratives 7 A very brief history of imagining intelligent machines 7 Embodiment 8 Extremes and control 9 Narrative and emerging technologies: lessons from previous science and technology debates 10 Implications 14 Disconnect from the reality of the technology 14 Underrepresented narratives and narrators 15 Constraints 16 The role of practitioners 20 Communicating AI 20 Reshaping AI narratives 21 The importance of dialogue 22 Annexes 24 Portrayals and perceptions of AI and why they matter 3 Executive summary The AI narratives project – a joint endeavour by the Leverhulme Centre for the Future of Intelligence and the Royal Society – has been examining how researchers, communicators, policymakers, and publics talk about artificial intelligence, and why this matters. This write-up presents an account of how AI is portrayed Narratives are essential to the development of science and perceived in the English-speaking West, with a and people’s engagement with new knowledge and new particular focus on the UK. It explores the limitations applications. Both fictional and non-fictional narratives of prevalent fictional and non-fictional narratives and have real world effects. Recent historical examples of the suggests how practitioners might move beyond them. evolution of disruptive technologies and public debates Its primary audience is professionals with an interest in with a strong science component (such as genetic public discourse about AI, including those in the media, modification, nuclear energy and climate change) offer government, academia, and industry.