Artificial Superintelligence A Futuristic Approach

A day does not go by without a news article reporting some amazing breakthrough in artificial intelligence (AI). Many philosophers, futurists, and AI researchers have conjectured that human-level AI will be developed in the next 20 to 200 years. If these predictions are correct, it raises new and sinister issues related to our future in the age of intelligent machines. Artificial Superintelligence: A Futuristic Approach directly addresses these issues and consolidates research aimed at making sure that emerging superintelligence is beneficial to humanity. While specific predictions regarding the consequences of superintelligent AI vary from potential economic hardship to the complete extinction of humankind, many researchers agree that the issue is of utmost importance and needs to be seriously addressed. Artificial Superintelligence: A Futuristic Approach discusses key topics such as: AI-Completeness theory and how it can be used to see if an artificial intelligent agent has attained human level intelligence Methods for safeguarding the invention of a superintelligent system that could theoretically be worth trillions of dollars Self-improving AI systems: definition, types, and limits The science of AI safety engineering, including machine ethics and robot rights Solutions for ensuring safe and secure confinement of superintelligent systems The future of superintelligence and why long-term prospects for humanity to remain as the dominant species on Earth are not great Artificial Superintelligence: A Futuristic Approach is designed to become a foundational text for the new science of AI safety engineering. AI researchers and students, computer security researchers, futurists, and philosophers should find this an invaluable resource.

PrefaceAcknowledgmentsAbout the AuthorAI-Completeness: The Problem Domain of Superintelligent MachinesIntroductionThe Theory of AI-CompletenessDefinitionsTuring Test as the First AI-Complete ProblemReducing Other Problems to a TTOther Probably AI-Complete ProblemsFirst AI-Hard Problem: ProgrammingBeyond AI-CompletenessConclusionsReferences The Space of Mind Designs and the Human Mental ModelIntroductionInfinitude of MindsSize, Complexity, and Properties of MindsSpace of Mind DesignsA Survey of TaxonomiesMind Cloning and Equivalence TestingAcross SubstratesConclusionsReferencesHow to Prove You Invented Superintelligence So No One Else Can Steal ItIntroduction and MotivationZero Knowledge ProofCaptchaAI-CompletenessSupercaptchaConclusionsReferencesWireheading, Addiction, and Mental Illness in MachinesIntroductionWireheading in MachinesSensory Illusions: A Form of Indirect WireheadingPotential Solutions to the Wireheading ProblemPerverse InstantiationConclusions and Future WorkReferencesOn the Limits of Recursively Self-Improving Artificially Intelligent SystemsIntroductionTaxonomy of Types of Self-ImprovementOn the Limits of Recursively Self-Improving Artificially Intelligent SystemsAnalysisRSI Convergence TheoremConclusionsReferencesSingularity Paradox and What to Do About ItIntroduction to the Singularity ParadoxMethods Proposed For Dealing with SPPrevention from DevelopmentRestricted DeploymentIncorporation into SocietySelf-MonitoringIndirect SolutionsAnalysis of SolutionsFuture Research DirectionsConclusionsReferencesSuperintelligence Safety EngineeringEthics and Intelligent SystemsArtificial Intelligence Safety EngineeringGrand ChallengeArtificial General Intelligence Research is UnethicalRobot RightsConclusionsReferencesArtificial Intelligence Confinement Problem (and Solution)IntroductionArtificial Intelligence Confinement ProblemHazardous SoftwareCritique of the Confinement ApproachPossible Escape PathsSocial Engineering AttacksSystem Resource AttacksBeyond Current Physics AttacksPseudoscientific AttacksExternal Causes of EscapeInformation In-LeakingCritique of the AI-Boxing CritiqueCountermeasures against EscapePreventing Social Engineering AttacksPreventing System Resource Attacks and Future ThreatPreventing External Causes of EscapePreventing Information In-LeakingAI Communication SecurityHow to Safely Communicate With a SuperintelligenceConclusions and Future WorkReferencesEfficiency Theory: A Unifying Theory for Information, Computation, and IntelligenceIntroductionEfficiency TheoryInformation and KnowledgeIntelligence and ComputationTime and SpaceCompressibility and RandomnessOracles and UndecidabilityIntractable and TractableConclusions and Future DirectionsReferencesControlling the Impact of Future SuperintelligenceWhy I Wrote This BookMachine Ethics Is a Wrong ApproachCan the Problem Be Avoided?References

Roman V. Yampolskiy holds a PhD from the Department of Computer Science and Engineering at the University at Buffalo (Buffalo, NY). There, he was a recipient of a four-year National Science Foundation (NSF) Integrative Graduate Education and Research Traineeship (IGERT) fellowship. Before beginning his doctoral studies, Dr. Yampolskiy received a BS/MS (High Honors) combined degree in computer science from the Rochester Institute of Technology in New York State. Dr. Yampolskiy’s main areas of interest are behavioral biometrics, digital forensics, pattern recognition, genetic algorithms, neural networks, artificial intelligence, and games. Dr. Yampolskiy is an author of over 100 publications, including multiple journal articles and books. His research has been cited by numerous scientists and profiled in popular magazines, both American and foreign (New Scientist, Poker Magazine, Science World Magazine), dozens of websites (BBC, MSNBC, Yahoo! News), and on radio (German National Radio, Alex Jones Show).