Machine Ethics and Superintelligence
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Sustainable Development, Technological Singularity and Ethics
European Research Studies Journal Volume XXI, Issue 4, 2018 pp. 714- 725 Sustainable Development, Technological Singularity and Ethics Vyacheslav Mantatov1, Vitaly Tutubalin2 Abstract: The development of modern convergent technologies opens the prospect of a new technological order. Its image as a “technological singularity”, i.e. such “transhuman” stage of scientific and technical progress, on which the superintelligence will be practically implemented, seems to be quite realistic. The determination of the basic philosophical coordinates of this future reality in the movement along the path of sustainable development of mankind is the most important task of modern science. The article is devoted to the study of the basic ontological, epistemological and moral aspects in the reception of the coming technological singularity. The method of this study is integrating dialectical and system approach. The authors come to the conclusion: the technological singularity in the form of a “computronium” (superintelligence) opens up broad prospects for the sustainable development of mankind in the cosmic dimension. This superintelligence will become an ally of man in the process of cosmic evolution. Keywords: Technological Singularity, Superintelligence, Convergent Technologies, Cosmocentrism, Human and Universe JEL code: Q01, Q56. 1East Siberia State University of Technology and Management, Ulan-Ude, Russia [email protected] 2East Siberia State University of Technology and Management, Ulan-Ude, Russia, [email protected] V. Mantatov, V. Tutubalin 715 1. Introduction Intelligence organizes the world by organizing itself. J. Piaget Technological singularity is defined as a certain moment or stage in the development of mankind, when scientific and technological progress will become so fast and complex that it will be unpredictable. -
Blame, What Is It Good For?
Blame, What is it Good For? Gordon Briggs1 Abstract— Blame is an vital social and cognitive mechanism [6] and reside in a much more ambiguous moral territory. that humans utilize in their interactions with other agents. In Additionally, it is not enough to be able to correctly reason this paper, we discuss how blame-reasoning mechanisms are about moral scenarios to ensure ethical or otherwise desirable needed to enable future social robots to: (1) appropriately adapt behavior in the context of repeated and/or long-term outcomes from human-robot interactions, the robot must interactions and relationships with other social agents; (2) avoid have other social competencies that support this reasoning behaviors that are perceived to be rude due to inappropriate mechanism. Deceptive interaction partners or incorrect per- and unintentional connotations of blame; and (3) avoid behav- ceptions/predictions about morally-charged scenarios may iors that could damage long-term, working relationships with lead even a perfect ethical-reasoner to make choices with other social agents. We also discuss how current computational models of blame and other relevant competencies (e.g. natural unethical outcomes [7]. What these challenges stress is the language generation) are currently insufficient to address these need to look beyond the ability to simply generate the proper concerns. Future work is necessary to increase the social answer to a moral dilemma in theory, and to consider the reasoning capabilities of artificially intelligent agents to achieve social mechanisms needed in practice. these goals. One such social mechanism that others have posited as I. INTRODUCTION being necessary to the construction of a artificial moral agent is blame [8]. -
The Technological Singularity and the Transhumanist Dream
ETHICAL CHALLENGES The technological singularity and the transhumanist dream Miquel Casas Araya Peralta In 1997, an AI beat a human world chess champion for the first time in history (it was IBM’s Deep Blue playing Garry Kasparov). Fourteen years later, in 2011, IBM’s Watson beat two winners of Jeopardy! (Jeopardy is a general knowledge quiz that is very popular in the United States; it demands a good command of the language). In late 2017, DeepMind’s AlphaZero reached superhuman levels of play in three board games (chess, go and shogi) in just 24 hours of self-learning without any human intervention, i.e. it just played itself. Some of the people who have played against it say that the creativity of its moves make it seem more like an alien that a computer program. But despite all that, in 2019 nobody has yet designed anything that can go into a strange kitchen and fry an egg. Are our machines truly intelligent? Successes and failures of weak AI The fact is that today AI can solve ever more complex specific problems with a level of reliability and speed beyond our reach at an unbeatable cost, but it fails spectacularly in the face of any challenge for which it has not been programmed. On the other hand, human beings have become used to trivialising everything that can be solved by an algorithm and have learnt to value some basic human skills that we used to take for granted, like common sense, because they make us unique. Nevertheless, over the last decade, some influential voices have been warning that our skills PÀGINA 1 / 9 may not always be irreplaceable. -
On How to Build a Moral Machine
On How to Build a Moral Machine Paul Bello [email protected] Human & Bioengineered Systems Division - Code 341, Office of Naval Research, 875 N. Randolph St., Arlington, VA 22203 USA Selmer Bringsjord [email protected] Depts. of Cognitive Science, Computer Science & the Lally School of Management, Rensselaer Polytechnic Institute, Troy, NY 12180 USA Abstract Herein we make a plea to machine ethicists for the inclusion of constraints on their theories con- sistent with empirical data on human moral cognition. As philosophers, we clearly lack widely accepted solutions to issues regarding the existence of free will, the nature of persons and firm conditions on moral agency/patienthood; all of which are indispensable concepts to be deployed by any machine able to make moral judgments. No agreement seems forthcoming on these mat- ters, and we don’t hold out hope for machines that can both always do the right thing (on some general ethic) and produce explanations for its behavior that would be understandable to a human confederate. Our tentative solution involves understanding the folk concepts associated with our moral intuitions regarding these matters, and how they might be dependent upon the nature of hu- man cognitive architecture. It is in this spirit that we begin to explore the complexities inherent in human moral judgment via computational theories of the human cognitive architecture, rather than under the extreme constraints imposed by rational-actor models assumed throughout much of the literature on philosophical ethics. After discussing the various advantages and challenges of taking this particular perspective on the development of artificial moral agents, we computationally explore a case study of human intuitions about the self and causal responsibility. -
Which Consequentialism? Machine Ethics and Moral Divergence
MIRI MACHINE INTELLIGENCE RESEARCH INSTITUTE Which Consequentialism? Machine Ethics and Moral Divergence Carl Shulman, Henrik Jonsson MIRI Visiting Fellows Nick Tarleton Carnegie Mellon University, MIRI Visiting Fellow Abstract Some researchers in the field of machine ethics have suggested consequentialist or util- itarian theories as organizing principles for Artificial Moral Agents (AMAs) (Wallach, Allen, and Smit 2008) that are ‘full ethical agents’ (Moor 2006), while acknowledging extensive variation among these theories as a serious challenge (Wallach, Allen, and Smit 2008). This paper develops that challenge, beginning with a partial taxonomy ofconse- quentialisms proposed by philosophical ethics. We discuss numerous ‘free variables’ of consequentialism where intuitions conflict about optimal values, and then consider spe- cial problems of human-level AMAs designed to implement a particular ethical theory, by comparison to human proponents of the same explicit principles. In conclusion, we suggest that if machine ethics is to fully succeed, it must draw upon the developing field of moral psychology. Shulman, Carl, Nick Tarleton, and Henrik Jonsson. 2009. “Which Consequentialism? Machine Ethics and Moral Divergence.” In AP-CAP 2009: The Fifth Asia-Pacific Computing and Philosophy Conference, October 1st-2nd, University of Tokyo, Japan, Proceedings, edited by Carson Reynolds and Alvaro Cassinelli, 23–25. AP-CAP 2009. http://ia-cap.org/ap-cap09/proceedings.pdf. This version contains minor changes. Carl Shulman, Henrik Jonsson, Nick Tarleton 1. Free Variables of Consequentialism Suppose that the recommendations of a broadly utilitarian view depend on decisions about ten free binary variables, where we assign a probability of 80% to our favored option for each variable; in this case, if our probabilities are well-calibrated and our errors are not correlated across variables, then we will have only slightly more than a 10% chance of selecting the correct (in some meta-ethical framework) specification. -
Philosophy of Artificial Intelligence
David Gray Grant Philosophy of Artificial Intelligence Note to the reader: this syllabus is for an introductory undergraduate lecture course with no prerequisites. Course Description In this course, we will explore the philosophical implications of artificial intelligence. Could we build machines with minds like ours out of computer chips? Could we cheat death by uploading our minds to a computer server? Are we living in a software-based simulation? Should a driverless car kill one pedestrian to save five? Will artificial intelligence be the end of work (and if so, what should we do about it)? This course is also a general introduction to philosophical problems and methods. We will dis- cuss classic problems in several areas of philosophy, including philosophy of mind, metaphysics, epistemology, and ethics. In the process, you will learn how to engage with philosophical texts, analyze and construct arguments, investigate controversial questions in collaboration with others, and express your views with greater clarity and precision. Contact Information Instructor: David Gray Grant Email: [email protected] Office: 303 Emerson Hall Office hours: Mondays 3:00-5:00 and by appointment Assignments and Grading You must complete all required assignments in order to pass this course. Your grade will be determined as follows: • 10%: Participation • 25%: 4 short written assignments (300-600 words) • 20%: Paper 1 (1200-1500 words) • 25%: Paper 2 (1200-1500 words) • 20%: Final exam Assignments should be submitted in .docx or .pdf format (.docx is preferred), Times New Roman 12 point font, single-spaced. Submissions that exceed the word limits specified above (including footnotes) will not be accepted. -
Impact of Technological Singularity in Human Life
IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727 PP 06-09 www.iosrjournals.org Impact of Technological Singularity in Human Life Mayur Umesh Ushir1, Prof. Pooja Kadam 2 1(MCA, BVIMIT, Navi Mumbai, India) 2(MCA, BVIMIT, Navi Mumbai, India) Abstract: The technological singularity is a situation that the invention of artificial superintelligence unexpectedly triggers technological growth, resulting in incalculable changes in human life. As we said it is artificial superintelligence, once a machine is learning to develop then it will improve technologies recursively and it will scale up to an exponential level, however, this change can evolve the human civilization rapidly. This is the point beyond which events may become unpredictable or even obscure to human intelligence. This paper will focus on the current state of the experiments on AI Software’s and deeply analyze the experiment results either positively or negatively impacting human society and life which can change them in the future. Keywords: Artificial Intelligence, Technological Singularity, Technical singularity, artificial superintelligence, technological growth, human intelligence, AI. I. Introduction In an artificial superintelligence, once a machine is learning to develop the new things then it will improve technologies recursively and it will scale up to an exponential level. This is the point beyond which events may become unpredictable or even obscure to human intelligence. We have seen many fiction movies and stories on technological singularity, which overcome the human society and destroy the human life. Lots of top research companies have given negative comments on the technological singularity. To understand ground reality, we have discovered some artificial intelligence experiments in the current year which may lead to the root of technological singularity which results may impact the human society and life. -
Machine Learning Ethics in the Context of Justice Intuition
SHS Web of Conferences 69, 00150 (2019) https://doi.org/10.1051/shsconf/20196900150 CILDIAH-2019 Machine Learning Ethics in the Context of Justice Intuition Natalia Mamedova1,*, Arkadiy Urintsov1, Nina Komleva1, Olga Staroverova1 and Boris Fedorov1 1Plekhanov Russian University of Economics, 36, Stremyanny lane, 117997, Moscow, Russia Abstract. The article considers the ethics of machine learning in connection with such categories of social philosophy as justice, conviction, value. The ethics of machine learning is presented as a special case of a mathematical model of a dilemma - whether it corresponds to the “learning” algorithm of the intuition of justice or not. It has been established that the use of machine learning for decision making has a prospect only within the limits of the intuition of justice field based on fair algorithms. It is proposed to determine the effectiveness of the decision, considering the ethical component and given ethical restrictions. The cyclical nature of the relationship between the algorithmic algorithms subprocesses in machine learning and the stages of conducting mining analysis projects using the CRISP methodology has been established. The value of ethical constraints for each of the algorithmic processes has been determined. The provisions of the Theory of System Restriction are applied to find a way to measure the effect of ethical restrictions on the “learning” algorithm 1 Introduction Accepting the freedom of thought is authentic intuition of justice of one individual in relation to The intuition of justice is regarded as a sincere, himself and others. But for artificial intelligence emotionally saturated belief in the justice of some (hereinafter - AI) freedom of thought is not supposed - position. -
Why Machine Ethics?
www.computer.org/intelligent Why Machine Ethics? Colin Allen, Indiana University Wendell Wallach, Yale University Iva Smit, E&E Consultants Vol. 21, No. 4 July/August 2006 This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. © 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. For more information, please see www.ieee.org/portal/pages/about/documentation/copyright/polilink.html. Machine Ethics Why Machine Ethics? Colin Allen, Indiana University Wendell Wallach, Yale University Iva Smit, E&E Consultants runaway trolley is approaching a fork in the tracks. If the trolley runs on its cur- A rent track, it will kill a work crew of five. If the driver steers the train down the other branch, the trolley will kill a lone worker. If you were driving the trolley, what would you do? What would a computer or robot do? Trolley cases, first introduced by philosopher which decisions must be made? It’s easy to argue Philippa Foot in 19671 and a staple of introductory from a position of ignorance that such a goal is impos- Machine ethics isn’t ethics courses, have multiplied in the past four sible to achieve. -
Ead Safety Beneficence V2
The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems Safety and Beneficence of Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI) The concept of intelligence can be difficult to precisely define, and there are many proposed definitions. Legg and Hutter (2007) surveyed 70-odd definitions of intelligence, pulling out the key features and commonalities between them, and settled on the following: “intelligence measures an agent’s ability to achieve goals in a wide range of environments.” In the context of autonomous and intelligent systems (A/IS), artificial general intelligence (AGI) is often used to refer to A/IS that perform comparably to humans on intellectual tasks, and artificial superintelligence (ASI or superintelligence) is commonly defined as “an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills” Bostrom( 2014), passing some threshold of generality, well-roundedness, and versatility that present-day AI systems do not yet achieve. Although today’s state-of-the-art A/IS do not match humans in this capacity (since today’s systems are only capable of performing well in limited and narrow environments or domains), many independent researchers and organizations are working on creating AGI systems (including leading AI labs like DeepMind, OpenAI, Microsoft, and Facebook’s FAIR), and most AI experts expect A/IS to surpass human-level intelligence sometime this century (Grace et al. 2017). When reasoning about the impacts that AGI systems will have, it is tempting to anthropomorphize, assume that these systems will have a “mind” similar to that of a human, and conflate intelligence with consciousness. -
APA Newsletter on Philosophy and Computers, Vol. 14, No. 2
NEWSLETTER | The American Philosophical Association Philosophy and Computers SPRING 2015 VOLUME 14 | NUMBER 2 FROM THE GUEST EDITOR John P. Sullins NOTES FROM THE COMMUNITY ON PAT SUPPES ARTICLES Patrick Suppes Patrick Suppes Autobiography Luciano Floridi Singularitarians, AItheists, and Why the Problem with Artificial Intelligence is H.A.L. (Humanity At Large), not HAL Peter Boltuc First-Person Consciousness as Hardware D. E. Wittkower Social Media and the Organization Man Niklas Toivakainen The Moral Roots of Conceptual Confusion in Artificial Intelligence Research Xiaohong Wang, Jian Wang, Kun Zhao, and Chaolin Wang Increase or Decrease of Entropy: To Construct a More Universal Macroethics (A Discussion of Luciano Floridi’s The Ethics of Information) VOLUME 14 | NUMBER 2 SPRING 2015 © 2015 BY THE AMERICAN PHILOSOPHICAL ASSOCIATION ISSN 2155-9708 APA NEWSLETTER ON Philosophy and Computers JOHN P. SULLINS, GUEST EDITOR VOLUME 14 | NUMBER 2 | SPRING 2015 but here we wish to celebrate his accomplishments in the FROM THE GUEST EDITOR fields of philosophy and computing one last time. John P. Sullins To accomplish that goal I have compiled some interesting SONOMA STATE UNIVERSITY pieces from an autobiography that Pat wrote some years ago but that he added to a bit for an event held in his honor November 17, 2014, marked the end of an inspiring at Stanford. In this document he explains his motivations career. On that day Patrick Suppes died quietly at the and accomplishments in various fields of study that are age of ninety-two in his house on the Stanford Campus, of interest to our community. In that section you will see which had been his home both physically and intellectually just how ambitious Pat was in the world of computer since 1950. -
Global Catastrophic Risks 2017 INTRODUCTION
Global Catastrophic Risks 2017 INTRODUCTION GLOBAL CHALLENGES ANNUAL REPORT: GCF & THOUGHT LEADERS SHARING WHAT YOU NEED TO KNOW ON GLOBAL CATASTROPHIC RISKS 2017 The views expressed in this report are those of the authors. Their statements are not necessarily endorsed by the affiliated organisations or the Global Challenges Foundation. ANNUAL REPORT TEAM Carin Ism, project leader Elinor Hägg, creative director Julien Leyre, editor in chief Kristina Thyrsson, graphic designer Ben Rhee, lead researcher Erik Johansson, graphic designer Waldemar Ingdahl, researcher Jesper Wallerborg, illustrator Elizabeth Ng, copywriter Dan Hoopert, illustrator CONTRIBUTORS Nobuyasu Abe Maria Ivanova Janos Pasztor Japanese Ambassador and Commissioner, Associate Professor of Global Governance Senior Fellow and Executive Director, C2G2 Japan Atomic Energy Commission; former UN and Director, Center for Governance and Initiative on Geoengineering, Carnegie Council Under-Secretary General for Disarmament Sustainability, University of Massachusetts Affairs Boston; Global Challenges Foundation Anders Sandberg Ambassador Senior Research Fellow, Future of Humanity Anthony Aguirre Institute Co-founder, Future of Life Institute Angela Kane Senior Fellow, Vienna Centre for Disarmament Tim Spahr Mats Andersson and Non-Proliferation; visiting Professor, CEO of NEO Sciences, LLC, former Director Vice chairman, Global Challenges Foundation Sciences Po Paris; former High Representative of the Minor Planetary Center, Harvard- for Disarmament Affairs at the United Nations Smithsonian