Nine Ways to Bias Open-Source AGI Toward Friendliness
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GNU/Linux AI & Alife HOWTO
GNU/Linux AI & Alife HOWTO GNU/Linux AI & Alife HOWTO Table of Contents GNU/Linux AI & Alife HOWTO......................................................................................................................1 by John Eikenberry..................................................................................................................................1 1. Introduction..........................................................................................................................................1 2. Symbolic Systems (GOFAI)................................................................................................................1 3. Connectionism.....................................................................................................................................1 4. Evolutionary Computing......................................................................................................................1 5. Alife & Complex Systems...................................................................................................................1 6. Agents & Robotics...............................................................................................................................1 7. Statistical & Machine Learning...........................................................................................................2 8. Missing & Dead...................................................................................................................................2 1. Introduction.........................................................................................................................................2 -
1 COPYRIGHT STATEMENT This Copy of the Thesis Has Been
University of Plymouth PEARL https://pearl.plymouth.ac.uk 04 University of Plymouth Research Theses 01 Research Theses Main Collection 2012 Life Expansion: Toward an Artistic, Design-Based Theory of the Transhuman / Posthuman Vita-More, Natasha http://hdl.handle.net/10026.1/1182 University of Plymouth All content in PEARL is protected by copyright law. Author manuscripts are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author. COPYRIGHT STATEMENT This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognize that its copyright rests with its author and that no quotation from the thesis and no information derived from it may be published without the author’s prior consent. 1 Life Expansion: Toward an Artistic, Design-Based Theory of the Transhuman / Posthuman by NATASHA VITA-MORE A thesis submitted to the University of Plymouth in partial fulfillment for the degree of DOCTOR OF PHILOSOPHY School of Art & Media Faculty of Arts April 2012 2 Natasha Vita-More Life Expansion: Toward an Artistic, Design-Based Theory of the Transhuman / Posthuman The thesis’ study of life expansion proposes a framework for artistic, design-based approaches concerned with prolonging human life and sustaining personal identity. To delineate the topic: life expansion means increasing the length of time a person is alive and diversifying the matter in which a person exists. -
The Transhumanist Reader Is an Important, Provocative Compendium Critically Exploring the History, Philosophy, and Ethics of Transhumanism
TH “We are in the process of upgrading the human species, so we might as well do it E Classical and Contemporary with deliberation and foresight. A good first step is this book, which collects the smartest thinking available concerning the inevitable conflicts, challenges and opportunities arising as we re-invent ourselves. It’s a core text for anyone making TRA Essays on the Science, the future.” —Kevin Kelly, Senior Maverick for Wired Technology, and Philosophy “Transhumanism has moved from a fringe concern to a mainstream academic movement with real intellectual credibility. This is a great taster of some of the best N of the Human Future emerging work. In the last 10 years, transhumanism has spread not as a religion but as a creative rational endeavor.” SHU —Julian Savulescu, Uehiro Chair in Practical Ethics, University of Oxford “The Transhumanist Reader is an important, provocative compendium critically exploring the history, philosophy, and ethics of transhumanism. The contributors anticipate crucial biopolitical, ecological and planetary implications of a radically technologically enhanced population.” M —Edward Keller, Director, Center for Transformative Media, Parsons The New School for Design A “This important book contains essays by many of the top thinkers in the field of transhumanism. It’s a must-read for anyone interested in the future of humankind.” N —Sonia Arrison, Best-selling author of 100 Plus: How The Coming Age of Longevity Will Change Everything IS The rapid pace of emerging technologies is playing an increasingly important role in T overcoming fundamental human limitations. The Transhumanist Reader presents the first authoritative and comprehensive survey of the origins and current state of transhumanist Re thinking regarding technology’s impact on the future of humanity. -
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. -
Artificial General Intelligence and the Future of the Human Race Bryon Pavlacka
ARTIFICIAL GENERAL INTELLIGENCE AND THE FUTURE OF THE HUMAN RACE Bryon Pavlacka Artificial Intelligence is all around us. It manages be used against humanity. Of course, such threats are not your investments, makes the subway run on time, imaginary future possibilities. Narrow AI is already used diagnoses medical conditions, searches the internet, solves by the militaries of first world countries for war purposes. enormous systems of equations, and beats human players Consider drones such as the Northrop Grumman X-47B, at chess and Jeopardy. However, this “narrow AI,” designed an Unmanned Combat Aerial Vehicle that is being tested for solving specific, narrow problems, is something by the US Navy (DefenseTech.org, 2011). That’s right, there distinctly different from Artificial General Intelligence, or is no pilot. Of course, the drone can be given orders, but “AGI”, true thinking machines with human-like general the exact way in which those orders are carried out will intelligence (Wang, Goertzel, & Franklin, 2008, p. v). While be left up to the drone’s Narrow AI system. Whether such AGI is not rigidly defined, it is often envisioned as being systems will ever be extended toward general intelligence self-aware and capable of complex thought, and has is currently unknown. However, the US military has shown BSJ been a staple of science fiction, appearing prominently in interest in producing and controlling generally intelligent popular films such as 2001: A Space Odyssey, Terminator, killing machines as well, as made evident by a paper called and I, Robot. In each of these films, the machines go “Governing Lethal Behavior” by Ronald C. -
Letters to the Editor
Articles Letters to the Editor Research Priorities for is a product of human intelligence; we puter scientists, innovators, entrepre - cannot predict what we might achieve neurs, statisti cians, journalists, engi - Robust and Beneficial when this intelligence is magnified by neers, authors, professors, teachers, stu - Artificial Intelligence: the tools AI may provide, but the eradi - dents, CEOs, economists, developers, An Open Letter cation of disease and poverty are not philosophers, artists, futurists, physi - unfathomable. Because of the great cists, filmmakers, health-care profes - rtificial intelligence (AI) research potential of AI, it is important to sionals, research analysts, and members Ahas explored a variety of problems research how to reap its benefits while of many other fields. The earliest signa - and approaches since its inception, but avoiding potential pitfalls. tories follow, reproduced in order and as for the last 20 years or so has been The progress in AI research makes it they signed. For the complete list, see focused on the problems surrounding timely to focus research not only on tinyurl.com/ailetter. - ed. the construction of intelligent agents making AI more capable, but also on Stuart Russell, Berkeley, Professor of Com - — systems that perceive and act in maximizing the societal benefit of AI. puter Science, director of the Center for some environment. In this context, Such considerations motivated the “intelligence” is related to statistical Intelligent Systems, and coauthor of the AAAI 2008–09 Presidential Panel on standard textbook Artificial Intelligence: a and economic notions of rationality — Long-Term AI Futures and other proj - Modern Approach colloquially, the ability to make good ects on AI impacts, and constitute a sig - Tom Dietterich, Oregon State, President of decisions, plans, or inferences. -
Exploratory Engineering in AI
MIRI MACHINE INTELLIGENCE RESEARCH INSTITUTE Exploratory Engineering in AI Luke Muehlhauser Machine Intelligence Research Institute Bill Hibbard University of Wisconsin Madison Space Science and Engineering Center Muehlhauser, Luke and Bill Hibbard. 2013. “Exploratory Engineering in AI” Communications of the ACM, Vol. 57 No. 9, Pages 32–34. doi:10.1145/2644257 This version contains minor changes. Luke Muehlhauser, Bill Hibbard We regularly see examples of new artificial intelligence (AI) capabilities. Google’s self- driving car has safely traversed thousands of miles. Watson beat the Jeopardy! cham- pions, and Deep Blue beat the chess champion. Boston Dynamics’ Big Dog can walk over uneven terrain and right itself when it falls over. From many angles, software can recognize faces as well as people can. As their capabilities improve, AI systems will become increasingly independent of humans. We will be no more able to monitor their decisions than we are now able to check all the math done by today’s computers. No doubt such automation will produce tremendous economic value, but will we be able to trust these advanced autonomous systems with so much capability? For example, consider the autonomous trading programs which lost Knight Capital $440 million (pre-tax) on August 1st, 2012, requiring the firm to quickly raise $400 mil- lion to avoid bankruptcy (Valetkevitch and Mikolajczak 2012). This event undermines a common view that AI systems cannot cause much harm because they will only ever be tools of human masters. Autonomous trading programs make millions of trading decisions per day, and they were given sufficient capability to nearly bankrupt one of the largest traders in U.S. -
Künstliche Intelligenz IMPRESSUM Swissfuture Nr
swissfuture Magazin für Zukunftsmonitoring 02/18 Künstliche Intelligenz IMPRESSUM swissfuture Nr. 02/18 Offizielles Organ der swissfuture Schweizerische Vereinigung für Zukunftsforschung, Organe officiel de la Société suisse pour la recherche prospective 45. Jahrgang Herausgeber swissfuture Schweizerische Vereinigung für Zukunftsforschung c/o Büro für Kongressorganisation GmbH Claudia Willi Vonmattstrasse 26 6003 Luzern T: +41 (0)41 240 63 33 M: +41 (0)79 399 45 99 [email protected] www.swissfuture.ch Präsidium Cla Semadeni Chefredaktion Francis Müller Autoren und Autorinnen Michael Gebendorfer, Siim Karus, Kevin Kohler, Daniel Stanislaus Martel, Remo Reginold, Jean-Marc Rickli, Roland Ringgenberg, Regula Stämpfli, Karlheinz Steinmüller Lektorat und Korrektorat Jens Ossadnik Übersetzungen (Englisch) James Rumball Bildredaktion und Layout Andrea Mettler (andreamettler.ch) Umschlagbild Oliver Hoffmann – stock.adobe.com Druck UD Medien AG, Luzern Erscheinungsweise 4x jährlich Einzelexemplar CHF 30.- Mitgliedschaft swissfuture (inkl. Magazin) Einzelpersonen CHF 100.– Studierende CHF 30.– Firmen CHF 280.– Zielsetzung der Zeitschrift Das Magazin behandelt die transdisziplinäre Zukunftsforschung, die Früherkennung und die prospektiven Sozialwissenschaften. Es macht deren neuen Erkenntnisse der Fachwelt, Entscheidungsträgern aus Politik, Verwaltung und Wirtschaft sowie einer interessierten Öffentlichkeit zugänglich. SAGW Unterstützt durch die Schweizerische Akademie der Geistes- und Sozialwissenschaften (SAGW), Bern. www.sagw.ch ISSN 1661-3082 -
Patterns of Cognition: Cognitive Algorithms As Galois Connections
Patterns of Cognition: Cognitive Algorithms as Galois Connections Fulfilled by Chronomorphisms On Probabilistically Typed Metagraphs Ben Goertzel February 23, 2021 Abstract It is argued that a broad class of AGI-relevant algorithms can be expressed in a common formal framework, via specifying Galois connections linking search and optimization processes on directed metagraphs whose edge targets are labeled with probabilistic dependent types, and then showing these connections are fulfilled by processes involving metagraph chronomorphisms. Examples are drawn from the core cognitive algorithms used in the OpenCog AGI framework: Probabilistic logical inference, evolutionary program learning, pattern mining, agglomerative clustering, pattern mining and nonlinear-dynamical attention allocation. The analysis presented involves representing these cognitive algorithms as re- cursive discrete decision processes involving optimizing functions defined over metagraphs, in which the key decisions involve sampling from probability distri- butions over metagraphs and enacting sets of combinatory operations on selected sub-metagraphs. The mutual associativity of the combinatory operations involved in a cognitive process is shown to often play a key role in enabling the decomposi- tion of the process into folding and unfolding operations; a conclusion that has some practical implications for the particulars of cognitive processes, e.g. militating to- ward use of reversible logic and reversible program execution. It is also observed that where this mutual associativity holds, there is an alignment between the hier- arXiv:2102.10581v1 [cs.AI] 21 Feb 2021 archy of subgoals used in recursive decision process execution and a hierarchy of subpatterns definable in terms of formal pattern theory. Contents 1 Introduction 2 2 Framing Probabilistic Cognitive Algorithms as Approximate Stochastic Greedy or Dynamic-Programming Optimization 5 2.1 A Discrete Decision Framework Encompassing Greedy Optimization andStochasticDynamicProgramming . -
Singularitynet: Whitepaper
SingularityNET A Decentralized, Open Market and Network for AIs Whitepaper 2.0: February 2019 Abstract Artificial intelligence is growing more valuable and powerful every year and will soon dominate the internet. Visionaries like Vernor Vinge and Ray Kurzweil have predicted that a “technological singularity” will occur during this century. The SingularityNET platform brings blockchain and AI together to create a new AI fabric that delivers superior practical AI functionality today while moving toward the fulfillment of Singularitarian artificial general intelligence visions. Today’s AI tools are fragmented by a closed development environment. Most are developed by one company and perform one extremely narrow task, and there is no straightforward, standard way to plug two tools together. SingularityNET aims to become the leading protocol for networking AI and machine learning tools to form highly effective applications across vertical markets and ultimately generate coordinated artificial general intelligence. Most AI research today is controlled by a handful of corporations—those with the resources to fund development. Independent developers of AI tools have no readily available way to monetize their creations. Usually, their most lucrative option is to sell their tool to one of the big tech companies, leading to control of the technology becoming even more concentrated. SingularityNET’s open-source protocol and collection of smart contracts are designed to address these problems. Developers can launch their AI tools on the network, where they can interoperate with other AIs and with paying users. Not only does the SingularityNET platform give developers a commercial launchpad (much like app stores give mobile app developers an easy path to market), it also allows the AIs to interoperate, creating a more synergistic, broadly capable intelligence. -
Technological Enhancement and Criminal Responsibility1
THIS VERSION DOES NOT CONTAIN PAGE NUMBERS. PLEASE CONSULT THE PRINT OR ONLINE DATABASE VERSIONS FOR PROPER CITATION INFORMATION. ARTICLE HUMANS AND HUMANS+: TECHNOLOGICAL ENHANCEMENT AND CRIMINAL RESPONSIBILITY1 SUSAN W. BRENNER2 I. INTRODUCTION [G]radually, the truth dawned on me: that Man had not remained one species . .3 It has been approximately 30,000 years since our species—Homo sapiens sapiens—shared the earth with another member of the genus Homo.4 I note 1 It was only after I decided to use Humans+ as part of the title for this article that I discovered the very similar device used by the transhumanist organization, Humanity+. See Mission, HUMANITY PLUS, http://humanityplus.org/about/mission/ (last visited Feb. 25, 2013). 2 NCR Distinguished Professor of Law & Technology, University of Dayton School of Law, Dayton, Ohio, USA. Email: [email protected]. 3 H.G. WELLS, THE TIME MACHINE 59 (Frank D. McConnell ed. 1977). 4 See GRAHAM CONNAH, FORGOTTEN AFRICA: AN INTRODUCTION TO ITS ARCHAEOLOGY 7–16 (2004) (supporting emergence of genus Homo in Africa); CHRIS GOSDEN, PREHISTORY: A VERY SHORT INTRODUCTION xiv–xv, 39–42 (2003) (summarizing rise of Homo sapiens sapiens). “Taxonomy,” or “the study of classification,” involves the process of sorting plants and animals into categories, including species. STEPHEN JAY GOULD, EVER SINCE DARWIN: REFLECTIONS IN NATURAL HISTORY 231 (1977). The species Homo sapiens includes Homo sapiens sapiens (modern humans) as well as several “archaic” members of the species. See, e.g., William Howells, Getting Here: The Story of Human Evolution 122– 23 (Washington, DC: Compass Press 1993). See also R.A. -
Mapping the Landscape of Human- Level Artificial General Intelligence
Mapping the Landscape of Human- Level Artificial General Intelligence Sam S. Adams, Itamar Arel, Joscha Bach, Robert Coop, Rod Furlan, Ben Goertzel, J. Storrs Hall, Alexei Samsonovich, Matthias Scheutz, Matthew Schlesinger, Stuart C. Shapiro, John Sowa ■ We present the broad outlines of a roadmap toward human-level artificial general intelligence (henceforth, AGI). We begin by discussing AGI in general, adopting a pragmatic goal for its attainment and a necessary foundation of characteristics and requirements. An initial capability landscape will be presented, drawing on major themes from developmental psychology and illuminated by mathematical, physiological, and information-processing perspectives. The challenge of identifying appropriate tasks and environments for measuring AGI will be addressed, and seven scenarios will be presented as milestones suggesting a roadmap across the AGI landscape along with directions for future research and collaboration. This article is the result of an ongoing collaborative effort by the coauthors, preceding and during the AGI Roadmap Workshop held at the University of Tennessee, Knoxville in October 2009, and from many continuing discussions since then. Some of the ideas also trace back to discussions held during two Evaluation and Metrics for Human Level AI workshopa organized by John Laird and Pat Langley (one in Ann Arbor in late 2008, and one in Tempe in early 2009). Some of the conclusions of the Ann Arbor workshop were recorded (Laird et al. 2009). Inspiration was also obtained from discussion at the Future of AGI postconference workshop of the AGI-09 conference, triggered by Itamar Arel’s presentation AGI Roadmap (Arel 2009); and from an earlier article on AGI road-mapping (Arel and Livingston 2009).