Stephen Hawking recently made headlines by noting, “The development of full artificial intelligence could spell the end of the human race.” Others, conversely, have trumpeted a new age of “superintelligence” in which smart devices will exponentially extend human capacities. No longer just a matter of science-fiction fantasy (2001, BLADE RUNNER, THE TERMINATOR, HER, etc.), it is time to seriously consider the reality of intelligent technology, many forms of which are already being integrated into our daily lives. In that spirit, John (...) Brockman, publisher of Edge (“the world’s smartest website” – THE GUARDIAN), asked the world’s most influential scientists, philosophers, and artists one of today’s most consequential questions: What do you think about machines that think? (shrink)

A New York Times Notable Book of 2012 Whether it’s in a cockpit at takeoff or the planning of an offensive war, a romantic relationship or a dispute at the office, there are many opportunities to lie and self-deceive—but deceit and self-deception carry the costs of being alienated from reality and can lead to disaster. So why does deception play such a prominent role in our everyday lives? In short, why do we deceive? In his bold new work, prominent biological (...) theorist Robert Trivers unflinchingly argues that self-deception evolved in the service of deceit—the better to fool others. We do it for biological reasons—in order to help us survive and procreate. From viruses mimicking host behavior to humans misremembering the details of a quarrel, science has proven that the deceptive one can always outwit the masses. But we undertake this deception at our own peril. Trivers has written an ambitious investigation into the evolutionary logic of lying and the costs of leaving it unchecked. (shrink)

Machines will attain human levels of intelligence by the year 2040, predicts robotics expert Hans Moravec. And by 2050, they will have far surpassed us. In this mind-bending new book, Hans Moravec takes the reader on a roller coaster ride packed with such startling predictions. He tells us, for instance, that in the not-too-distant future, an army of robots will displace workers, causing massive, unprecedented unemployment. But then, says Moravec, a period of very comfortable existence will follow, as humans benefit (...) from a fully automated economy. And eventually, as machines evolve far beyond humanity, robots will supplant us. But if Moravec predicts the end of the domination by human beings, his is not a bleak vision. Far from railing against a future in which machines rule the world, Moravec embraces it, taking the startling view that intelligent robots will actually be our evolutionary heirs. "Intelligent machines, which will grow from us, learn our skills, and share our goals and values, can be viewed as children of our minds." And since they are our children, we will want them to outdistance us. In fact, in a bid for immortality, many of our descendants will choose to transform into "ex humans," as they upload themselves into advanced computers. We will become our children and live forever. In his provocative new book, the highly anticipated follow-up to his bestselling volume Mind Children, Moravec charts the trajectory of robotics in breathtaking detail. A must read for artificial intelligence, technology, and computer enthusiasts, Moravec's freewheeling but informed speculations present a future far different than we ever dared imagine. (shrink)

In this article we argue that self-deception evolved to facilitate interpersonal deception by allowing people to avoid the cues to conscious deception that might reveal deceptive intent. Self-deception has two additional advantages: It eliminates the costly cognitive load that is typically associated with deceiving, and it can minimize retribution if the deception is discovered. Beyond its role in specific acts of deception, self-deceptive self-enhancement also allows people to display more confidence than is warranted, which has a host of social advantages. (...) The question then arises of how the self can be both deceiver and deceived. We propose that this is achieved through dissociations of mental processes, including conscious versus unconscious memories, conscious versus unconscious attitudes, and automatic versus controlled processes. Given the variety of methods for deceiving others, it should come as no surprise that self-deception manifests itself in a number of different psychological processes, and we discuss various types of self-deception. We then discuss the interpersonal versus intrapersonal nature of self-deception before considering the levels of consciousness at which the self can be deceived. Finally, we contrast our evolutionary approach to self-deception with current theories and debates in psychology and consider some of the costs associated with self-deception. (shrink)

This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...) is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)

Little, Brown, 1992 Review by Glenn Branch on Jul 5th 1999 Volume: 3, Number: 27.

This paper discusses the relation between intelligence and motivation in artificial agents, developing and briefly arguing for two theses. The first, the orthogonality thesis, holds (with some caveats) that intelligence and final goals (purposes) are orthogonal axes along which possible artificial intellects can freely vary—more or less any level of intelligence could be combined with more or less any final goal. The second, the instrumental convergence thesis, holds that as long as they possess a sufficient level of intelligence, agents having (...) any of a wide range of final goals will pursue similar intermediary goals because they have instrumental reasons to do so. In combination, the two theses help us understand the possible range of behavior of superintelligent agents, and they point to some potential dangers in building such an agent. (shrink)

This paper argues that at least one of the following propositions is true: the human species is very likely to go extinct before reaching a "posthuman" stage; any posthuman civilization is extremely unlikely to run a significant number of simulations of their evolutionary history ; we are almost certainly living in a computer simulation. It follows that the belief that there is a significant chance that we will one day become posthumans who run ancestor-simulations is false, unless we are currently (...) living in a simulation. A number of other consequences of this result are also discussed. (shrink)

I argue that at least one of the following propositions is true: the human species is very likely to become extinct before reaching a ’posthuman’ stage; any posthuman civilization is extremely unlikely to run a significant number of simulations of its evolutionary history ; we are almost certainly living in a computer simulation. It follows that the belief that there is a significant chance that we shall one day become posthumans who run ancestor-simulations is false, unless we are currently living (...) in a simulation. I discuss some consequences of this result. (shrink)

Das Ziel dieses Beitrags besteht darin, eine kurze Darstellung der "Selbstmodell-Theorie der Subjektivität" (SMT) anzubieten, die sich an naturwissenschaftlich orientierte Leser richtet, die selbst keine Philosophen sind, aber dennoch an philosophischen Theorien des Selbstbewusstseins interessiert sind.

Because of accelerating technological progress, humankind may be rapidly approaching a critical phase in its career. In addition to well-known threats such as nuclear holocaust, the propects of radically transforming technologies like nanotech systems and machine intelligence present us with unprecedented opportunities and risks. Our future, and whether we will have a future at all, may well be determined by how we deal with these challenges. In the case of radically transforming technologies, a better understanding of the transition dynamics from (...) a human to a "posthuman" society is needed. Of particular importance is to know where the pitfalls are: the ways in which things could go terminally wrong. While we have had long exposure to various personal, local, and endurable global hazards, this paper analyzes a recently emerging category: that of existential risks. These are threats that could case our extinction or destroy the potential of Earth - originating intelligent life. Some of these threats are relatively well known while others, including some of the gravest, have gone almost unrecognized. Existential risks have a cluster of features that make ordinary risk management ineffective. A final section of this paper discusses several ethical and policy implications. A clearer understanding of the threat picture will enable us to formulate better strategies. (shrink)

The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but we have cleverer brains. If machine brains one day come to surpass human brains in general intelligence, then this new superintelligence could become very powerful. As the fate of the gorillas now depends more on us humans than on the gorillas themselves, so the fate of (...) our species then would come to depend on the actions of the machine superintelligence. But we have one advantage: we get to make the first move. Will it be possible to construct a seed AI or otherwise to engineer initial conditions so as to make an intelligence explosion survivable? How could one achieve a controlled detonation? To get closer to an answer to this question, we must make our way through a fascinating landscape of topics and considerations. Read the book and learn about oracles, genies, singletons; about boxing methods, tripwires, and mind crime; about humanity's cosmic endowment and differential technological development; indirect normativity, instrumental convergence, whole brain emulation and technology couplings; Malthusian economics and dystopian evolution; artificial intelligence, and biological cognitive enhancement, and collective intelligence. (shrink)

This up-to-date introduction to decision theory offers comprehensive and accessible discussions of decision-making under ignorance and risk, the foundations of utility theory, the debate over subjective and objective probability, Bayesianism, causal decision theory, game theory, and social choice theory. No mathematical skills are assumed, and all concepts and results are explained in non-technical and intuitive as well as more formal ways. There are over 100 exercises with solutions, and a glossary of key terms and concepts. An emphasis on foundational aspects (...) of normative decision theory (rather than descriptive decision theory) makes the book particularly useful for philosophy students, but it will appeal to readers in a range of disciplines including economics, psychology, political science and computer science. • Has over 100 end of chapter review questions and exercises with solutions • Includes a chapter on how to draw a decision matrix • Explains the link between individual decision making, game theory and social choice theory Contents Preface; 1. Introduction; 2. The decision matrix; 3. Decisions under ignorance; 4. Decisions under risk; 5. Utility; 6. The mathematics of probability; 7. The philosophy of probability; 8. Why should we accept the preference axioms; 9. Causal vs. evidential decision theory; 10. Bayesian vs. non-Bayesian decision theory; 11. Game theory I: basic concepts and zero sum games; 12. Game theory II: nonzero sum and co-operative games; 13. Social choice theory; 14. Overview of descriptive decision theory; Appendix A. Glossary; Appendix B. Proof of the von Neumann-Morgenstern theorem; Further reading; Index. (shrink)

The book is an extended study of the problem of consciousness. After setting up the problem, I argue that reductive explanation of consciousness is impossible , and that if one takes consciousness seriously, one has to go beyond a strict materialist framework. In the second half of the book, I move toward a positive theory of consciousness with fundamental laws linking the physical and the experiential in a systematic way. Finally, I use the ideas and arguments developed earlier to defend (...) a form of strong artificial intelligence and to analyze some problems in the foundations of quantum mechanics. (shrink)

Sequential decision theory formally solves the problem of rational agents in uncertain worlds if the true environmental prior probability distribution is known. Solomonoff's theory of universal induction formally solves the problem of sequence prediction for unknown prior distribution. We combine both ideas and get a parameter-free theory of universal Artificial Intelligence. We give strong arguments that the resulting AIXI model is the most intelligent unbiased agent possible. We outline how the AIXI model can formally solve a number of problem classes, (...) including sequence prediction, strategic games, function minimization, reinforcement and supervised learning. The major drawback of the AIXI model is that it is uncomputable. To overcome this problem, we construct a modified algorithm AIXItl that is still effectively more intelligent than any other time t and length l bounded agent. The computation time of AIXItl is of the order t x 2^l. The discussion includes formal definitions of intelligence order relations, the horizon problem and relations of the AIXI theory to other AI approaches. (shrink)

What if we someday learn how to model small brain units, and so can "upload" ourselves into new computer brains? What if this happens before we learn how to make human-level artificial intelligences? The result could be a sharp transition to an upload-dominated world, with many dramatic consequences. In particular, fast and cheap replication may once again make Darwinian evolution of human values a powerful force in human history. With evolved values, most uploads would value life even when life is (...) hard or short, uploads would reproduce quickly, and wages would fall. But total wealth should rise, so we could all do better by accepting uploads, or at worse taxing them, rather than trying to delay or segregate them. (shrink)

What happens when machines become more intelligent than humans? One view is that this event will be followed by an explosion to ever-greater levels of intelligence, as each generation of machines creates more intelligent machines in turn. This intelligence explosion is now often known as the “singularity”. The basic argument here was set out by the statistician I.J. Good in his 1965 article “Speculations Concerning the First Ultraintelligent Machine”: Let an ultraintelligent machine be defined as a machine that can far (...) surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an “intelligence explosion”, and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make. The key idea is that a machine that is more intelligent than humans will be better than humans at designing machines. So it will be capable of designing a machine more intelligent than the most intelligent machine that humans can design. So if it is itself designed by humans, it will be capable of designing a machine more intelligent than itself. By similar reasoning, this next machine will also be capable of designing a machine more intelligent than itself. If every machine in turn does what it is capable of, we should expect a sequence of ever more intelligent machines. This intelligence explosion is sometimes combined with another idea, which we might call the “speed explosion”. The argument for a speed explosion starts from the familiar observation that computer processing speed doubles at regular intervals. Suppose that speed doubles every two years and will do so indefinitely. Now suppose that we have human-level artificial intelligence 1 designing new processors. Then faster processing will lead to faster designers and an ever-faster design cycle, leading to a limit point soon afterwards. The argument for a speed explosion was set out by the artificial intelligence researcher Ray Solomonoff in his 1985 article “The Time Scale of Artificial Intelligence”.1 Eliezer Yudkowsky gives a succinct version of the argument in his 1996 article “Staring at the Singularity”: “Computing speed doubles every two subjective years of work.. (shrink)

It is widely accepted that conscious experience has a physical basis. That is, the properties of experience (phenomenal properties, or qualia) systematically depend on physical properties according to some lawful relation. There are two key questions about this relation. The first concerns the strength of the laws: are they logically or metaphysically necessary, so that consciousness is nothing "over and above" the underlying physical process, or are they merely contingent laws like the law of gravity? This question about the strength (...) of the psychophysical link is the basis for debates over physicalism and property dualism. The second question concerns the shape of the laws: precisely how do phenomenal properties depend on physical properties? What sort of physical properties enter into the laws' antecedents, for instance; consequently, what sort of physical systems can give rise to conscious experience? It is this second question that I address in this paper. (shrink)

Responding to Chalmers' The Singularity , I argue that progress towards self-improving Ais is already substantially beyond what many futurists and philosophers are aware of. Instead of rehashing well-trodden topics of the previous millennium, let us start focusing on relevant new millennium results.

Robotics and artificial intelligence are beginning to fundamentally change the relative profitability and productivity of investments in capital versus human labor; creating technological unemployment at all levels of the workforce; from the North to the developing world. As robotics and expert systems become cheaper and more capable the percentage of the population that can find employment will also fall; stressing economies already trying to curtail "entitlements" and adopt austerity. Two additional technology-driven trends will exacerbate the structural unemployment crisis in the (...) coming decades; desktop manufacturing and anti-aging medicine. Desktop manufacturing threatens to disintermediate the half of all workers involved in translating ideas into products in the hands of consumers; while anti-aging therapies will increase the old age dependency ratio of retirees to tax-paying workers. Policies that are being proposed to protect or create employment will have only a temporary moderating effect on job loss. Over time these policies; which will impose raise costs; lower the quality of goods and services; and lower competitiveness; will become fiscally impossible and lose political support. In order to enjoy the benefits of technological innovation and longer; healthier lives we will need to combine policies that control the pace of replacing paid human labor with a universal basic income guarantee provided through taxation and the public ownership of wealth. The intensifying debate over the reform of "entitlements" will be the strategic opening for a campaign for BIG to replace disability and unemployment insurance; Social Security; and other elements of the welfare state. (shrink)

Computers have far to go to match human strengths, and our estimates will depend on analogy and extrapolation. Fortunately, these are grounded in the first bit of the journey, now behind us. Thirty years of computer vision reveals that 1 MIPS can extract simple features from real-time imagery--tracking a white line or a white spot on a mottled background. 10 MIPS can follow complex gray-scale patches--as smart bombs, cruise missiles and early self-driving vans attest. 100 MIPS can follow moderately unpredictable (...) features like roads--as recent long NAVLAB trips demonstrate. 1,000 MIPS will be adequate for coarse-grained three-dimensional spatial awareness--illustrated by several mid-resolution stereoscopic vision programs, including my own. 10,000 MIPS can find three-dimensional objects in clutter--suggested by several "bin-picking" and high-resolution stereo-vision demonstrations, which accomplish the task in an hour or so at 10 MIPS. The data fades there--research careers are too short, and computer memories too small, for significantly more elaborate experiments. (shrink)

_This paper outlines the case for believing that we will have superhuman artificial intelligence_ _within the first third of the next century. It looks at different estimates of the processing power of_ _the human brain; how long it will take until computer hardware achieve a similar performance;_ _ways of creating the software through bottom-up approaches like the one used by biological_ _brains; how difficult it will be for neuroscience figure out enough about how brains work to_ _make this approach work; (...) and how fast we can expect superintelligence to be developed once_ _there is human-level artificial intelligence._. (shrink)

Several authors have made the argument that because blind evolutionary processes produced human intelligence on Earth, it should be feasible for clever human engineers to create human-level artificial intelligence in the not-too-distant future. This evolutionary argument, however, has ignored the observation selection effect that guarantees that observers will see intelligent life having arisen on their planet no matter how hard it is for intelligent life to evolve on any given Earth-like planet. We explore how the evolutionary argument might be salvaged (...) from this objection, using a variety of considerations from observation selection theory and analysis of specific timing features and instances of convergent evolution in the terrestrial evolutionary record. We find that, depending on the resolution of disputed questions in observation selection theory, the objection can either be wholly or moderately defused, although other challenges for the evolutionary argument remain. (shrink)