Abstracts

Superstition and Forgetfulness – Two Essentials for Artificial General Intelligence
Sam Adams

Computer systems today have no conception of their own behavior, operational goals and constraints, or their relationship to other systems in their run time environment. Noted neurophysiologist Walter Freeman put it plainly, "Truly flexible and adaptive intelligence cannot operate in the real world without the construction of meaning. Systems that do not construct and maintain their own sense of meaning about their world are incapable of either truly understanding language or intelligently adapting and governing their own behavior." If we are ever to achieve either of these goals, let alone the "singularity", we have no choice but to overcome this barrier. We must discover a way to imbue computing systems with real understanding, human-style semantics, and give them similar cognitive capabilities comparable to the common sense reasoning of the human child at the very least. Research in Developmental Neurophysiology and Developmental Psychology as well as experience in developing the Joshua Blue project at IBM Research has revealed two surprising but essential characteristics for any system that can successfully bootstrap its own understanding and sense of meaning: Superstition and Forgetfulness. This talk will present evidence for this claim as well as discuss its implications for the successful attainment of Artificial General Intelligence.

The Singularity: A Period Not An Event
Rodney Brooks

Whatever writes future history will look back at what we are calling the singularity not as a single event but as a period of time. The singularity period will encompass a time where a collection of technologies were invented, developed, and deployed in fits and starts, driven not by the imperative of the singularity itself, but by the normal economic and sociological pressures of human affairs. A Hollywood treatment of the singularity would have a world just like today's, plus the singularity, as a singular event. In reality, the world will be changing continuously due to rapid growth in technologies that are both related and unrelated to the singularity itself. The future will be embedded in a different world than the one we inhabit. And the AI systems we create will not have the same desires, beliefs, and goals as today-us. Tomorrow-us will be much better equipped for the changes that will take place in our world. This talk will explore how things might unfold and how we will transform ourselves along the way.

Metaverse Singularity
Jamais Cascio

There are numerous scenarios for how the Singularity might transpire, but implicit in most is the notion that the technologies that trigger the Singularity themselves emerge from earlier generations of systems and tools. One particularly rich potential progenitor is the spectrum of technologies encompassed by the term "Metaverse." Building upon my work in the recently-published Metaverse Roadmap Overview, I trace how each of the four Metaverse scenarios – Augmented Reality, Lifelogging, Virtual Worlds and Mirror World – lead to very different types of Singularities. I look at the ways in which these different Singularity models might interact, and the implications each have for the likelihood of friendly and unfriendly AI.

Nine Years To a Positive Singularity – If We Really, Really Try
Ben Goertzel

Common wisdom holds that powerful artificial general intelligence is decades to centuries off. Even techno-futurist Ray Kurzweil projects a date of 2029 for human-level AI via human brain emulation. My contention, however, is that powerful and beneficial AGI could come much sooner – if sufficient attention and resources are devoted to the right approaches. My favored approach involves integrating probabilistic and evolutionary learning, artificial economics, and other cutting-edge computer science techniques in a cognitive architecture informed by cognitive science and systems theory; and then embedding this architecture in virtual agents that interact with humans and each other in online virtual worlds. Among other advantages, I argue that this sort of AGI architecture is intrinsically better suited for stably ethical behavior than more closely human brain based architectures, due to the presence of a coherent and logical goal system. Current prototype work will be discussed, aimed at actualizing this approach via the release of intelligent agents controlled by the Novamente AI Engine in Second Life and other virtual worlds. Of course, it is difficult to place any kind of reliable estimate on the course of development of this kind of technology, given the R&D that remains to be done, and the uncertainties regarding funding and other practical exigencies. But radical success within less than a decade does not seem an outrageously unlikely possibility, in the view of this AGI researcher and entrepreneur.

Asimov's Laws of Robotics – Revised
J. Storrs Hall

Isaac Asimov's Three Laws of Robotics are the classic, and by far the best known, attempt to formalize guidelines for the behavior of intelligent machines with respect to humans – a robotic ethic, if you will. Yet the Three Laws are widely misapprehended. Asimov's concept of the robotic mind was strongly cybernetic, a feedback-based, analog, circuit-like paradigm somewhat in contrast to modern symbolic AI. This has more in common with how a human's internal moral sense works than with text-based codes of ethics. Also, Asimov's robots lacked a key feature that will be one of the most important characteristics of the AIs of the coming Intellectual Revolution (Asimov's own phrase for what is now called the Singularity, by analogy to the Industrial Revolution). His robots did not improve themselves as fast as humans do, much less outstrip us at an accelerating pace. Furthermore, as a practical matter, there is virtually no chance that any single set or conception of robotic Laws will be uniformly implemented in all AIs. Thus it is necessary to consider a revised notion of robotic morality: one based on an understanding of the evolutionary origins of human morals and ethics; one which allows the robots that bear it to prosper in a world of others that do not; and one which is an evolutionarily stable strategy in the future ecosystem of mind.

Superintelligence, the Dilemma of Power, and the Transformation of Desire
Charles L. Harper, Jr.

I - Superintelligence: Consider the idea that increasing intelligence involves “phase transitions” (e.g., pre/post language). Consider the question: “What does a slug know of Mozart?” Let us suppose that humans are in a relation to the reality experienced by superintelligence as slugs are to Mozart’s musical creativity (MMC). What would be the analog to MMC for ourselves, conceived of as being like slugs? Of course we cannot even imagine an answer due to the nature of the question. It asks us to consider putative aspects of reality which by definition would be beyond our biological ability to conceptualize or experience. So, does reality include this kind of ontological “altitude” fundamentally exceeding our epistemological reference frame? Are Homo Sapiens primates correct to presume, unthinkingly, that we sit at the summit of an ontological Everest with no further vertical extension of the peak above us?

II - The Dilemma of Power: Francis Bacon’s vision has been accomplished far beyond his prophetic and progress-generating imagination ever could have foreseen. Therefore consider the ongoing Dilemma of Power: science and technology create new forms of “power” relatively rapidly, whereas cultures and civilizations do not so easily create the parallel capacities of stewardship required to utilize newly created powers for benevolent use and to restrain them from being used to serve malevolent ends. Therefore, if some groups are focused on massive acceleration of Bacon’s realized dream, then the key question remains: who will generate corresponding advances in the “rule of law” and in the human virtuousness that sustains it on all scales from that of interacting individuals to that of the whole planet?

III – The Transformation of Desire: People use power to pursue ends they desire. Therefore the increase of personal power calls for the transformation of personal desire. Science, however, knows next to nothing of the transformation of desire. Monks, hermits, fasters, counterculturals – the athletes of the spirit; these are the sorts of people who work on and know about the transformation of desire. A wise approach towards the development of superintelligence probably should include serious consideration on how to transform desire so that enhanced powers are not abused to serve un-enhanced desires. The transformation of desire for humans involves what in virtue ethics is called “habitus” – the formation of habituated character through devoted, willful practice within a space of real freedom. Virtue is not a matter of either knowledge or “programming.” And it also often is not limited to only individual lives. It occurs in group contexts such as families, teams, monastic orders, communities. Also, people who engage in the transformation of desire often are involved in worship and prayer. They seek inspiration and transformative power from God. In view of such issues, what would be the “transformation of desire” for a superintelligence?

Waiting for the Great Leap...Forward?
James Hughes

Sentient, self-willed, greater-than-human machine minds are very likely in the coming fifty years. But to ensure that they don't threaten the welfare of the rest of the minds on the planet a number of steps need to be taken. First, given their radically different architecture and origins, developing software capacity for recognizing and relating to, perhpas having empathy for, human sentience should be a design goal, even if machine minds are likely to evolve beyond human perspectives and emotional traits. Second, building on the global networks established to identify and respond to computer viruses, governments and cyber-security firms need to develop detectors for and counter-measures for self-willed machine intelligence that may emerge, evolve, or be accidentally or maliciously released. Those detectors and counter-measures may or may not involve machine minds as well. Third, human beings should aggressively pursue cognitive enhancement and cyber-augmentation in order to give them a competitive chance against machine minds, economically and in the event of conflict. Fourth, since machine intelligence, self-willed or zombie, is likely to displace the need for most human occupations by the middle of the century, industrialized countries will need to renegotiate the relationship between education, work, income, and retirement, extracting a general social wage from robotic productivity to lift all boats, not just those of the shrinking group of workers and owners of capital. Finally, in order to ensure that we do not re-capitulate slavery, we will need to be much clearer about what kinds of minds, organic and machine, have what kinds of responsibilities and are owed which kinds of rights. Machine minds with a capacity to understand and obey the obligations of a democratic polity should be granted the rights to own property, vote and so on. Minds wishing to exercise capacities as dangerous as weapons or motor vehicles, should be licensed to do so, while even more dangerous capacities (AI equivalents of bombs) will need to be restricted to control by, or be integrated into the functioning of, accountable democratic governance.

Innovative Applications of Early Stage AI
Neil Jacobstein

Early stage artificial intelligence has already produced a wide range of valuable but narrowly focused knowledge systems applications in industry and government. Many of these applications have performed complex tasks such as planning, monitoring, design, risk assessment, diagnosis, training, process control, classification, and analysis. For example, AAAI’s Innovative Applications of AI Conference has published hundreds of successful applications of AI. The applications are in fields as diverse as biotechnology, space flight, manufacturing, security, paleontology, construction, energy, music, military, intelligence, banking, telecommunications, news media, management, law, emergency services, agriculture, treaty verification, and many other areas. This talk will review the distribution of these applications across tasks and domains, and discuss the patterns that connect these applications: what worked, what didn’t, and what are the key trends. None of these systems exhibited general intelligence, but each documented our ability to codify and distribute human problem solving knowledge, and put it to work. The answer to the question about how far are we from advanced AI depends on the operational definition of “advanced”. It is clear from the knowledge systems produced thus far that even relatively straightforward applications can be valuable. The larger endeavor to produce AI systems that learn and reason at human levels and beyond is promising, and will require both enlightened research sponsorship and appropriate safeguards.

Dichotomy of Designed and Evolutionary Paths to AI Futures
Steve Jurvetson

How will we first build a general artificial intelligence that exceeds human intelligence? Some technologists advocate design; others prefer evolutionary search algorithms. Still others would selectively conflate the two, hoping to incorporate the best of both paradigms while avoiding their limitations. But while both processes are powerful, they are very different, and they are not easily combined. Rather, they present divergent paths. When we evolve a complex system, it is a black box defined by its interfaces. We cannot easily apply our design intuition to improve upon its inner workings. We can’t even partition its subsystems without a serious effort at reverse engineering. And until we can understand the interfaces between partitions, we can’t hope to transfer a subsystem from one evolved complex system to another (unless they have co-evolved). A grand engineering challenge therefore remains: can we integrate the evolutionary and design paths to exploit the best of both? Can we transcend human intelligence with an evolutionary algorithm yet maintain an element of control, or even a bias toward friendliness?

The History and Future of Technological Change
Peter Norvig

The invention of new technology is limited only by the laws of science and by the degree of ingenuity in the lab. But the proliferation of new technology into everyday life is a complex social process involving entrepreneurs, venture capitalists, international corporations, politicians, consumers, and dumb luck. It's hard to predict, especially the future, but by examining past and present examples of technological change, we can begin to come to grips with the possibility of abrupt change in the future.

The Nature of Self-Improving Artificial Intelligence
Stephen M. Omohundro

Can we predict the behavior of systems that modify themselves? Can we design them to embody our values even after many generations of self-improvement? This talk will present a framework for answering questions like these. It shows that self-improving systems converge on a specific cognitive architecture that arose out of von Neumann's foundational work on microeconomics. In these systems there is a universal principle which governs the organization of all levels of physical and computational resources. They exhibit four natural drives: 1) efficiency, 2) self-preservation, 3) resource acquisition, and 4) creativity. Unbridled, these lead to both desirable and undesirable behaviors.

The efficiency drive leads to algorithm optimization, data compression, atomically precise physical structures, reversible computation, adiabatic physical action, the virtualization of the physical, and governs a system's choice of memories, theorems, language, and logic. The self-preservation drive leads to defensive strategies such as "energy encryption" for hiding resources and promotes replication and game theoretic modelling. The resource acquisition drive leads to a variety of competitive behaviors and promotes rapid physical expansion and imperialism. The creativity drive leads to the development of new concepts, algorithms, theorems, devices, and processes.

The best of these traits could usher in a new era of peace and prosperity; the worst are characteristic of human psychopaths and could bring widespread destruction. How can we ensure that this technology acts in alignment with our highest values? We have leverage both in designing the systems' initial values and in creating the social context within which they operate. But we must have great clarity in imagining the future we want to create. We need not just a logical understanding of the technology but a deep introspection into what we cherish most. With both logic and inspiration we can work toward building a technology that empowers the human spirit rather than diminishing it.

Pathways to Advanced General Intelligence: Architecture, Development, and Funding
Barney Pell

While there is broad consensus among the AI community that we will have artificial general intelligence (AGI) within the century, there is little discussion about the alternate technical and economic pathways that will bring this about. I present a framework for comparing different approaches, in which we view any intelligent behavior as a combination of architecture and development, both of which can be characterized as more or less human-brain-like. Seen within this framework, one extreme strives for complete brain simulations that develop like human children. Another extreme strives for unconstrained engineered systems that acquire knowledge through diverse methods. I predict that the path to AGI will be based on a much richer interplay between these two extremes, in which top-down and bottom-up approaches meet in the middle.

The hybrid development path combines the benefits of both technical extremes. It also supports applications that create incremental business advantage for incremental improvements in AGI capability, thus driving business competition that accelerates the science. These applications include video games, virtual worlds, household robots, autonomous vehicles, search, and conversational interfaces.

Preparing for Bizarreness: Open Source Physical Security
Christine L. Peterson

Attempting to take action now to get ready for a world with strong AI is a highly daunting task. Nevertheless it is worth considering our options, especially any that are useful in the nearer term for other reasons. We can ask: In a world of powerful entities, how can individuals be protected?

The open source software experience inspires us to look for ways to transfer the advantages of that process to the physical world. Open source has been particularly speedy at correction of security vulnerabilities – precisely the kind of vulnerabilities we will need to guard against in a world of highly powerful entities of various kinds. We can begin now to extend the principles of open source into the physical world: we can start to make physical security "bottom-up", decentralized, collaborative, and transparent.

Machines of Loving Grace: Envisioning Advanced AI
Paul Saffo

A long-anticipated vision of advanced AI is on the verge of arriving late and in utterly unexpected ways. As we approach this event, a quick look through the rear-view mirror at earlier AI visions can do much to reduce the uncertainty around how things may unfold. Moreover, these earlier visions are a powerful reminder that we are not hapless bystanders, but active participants in what this future should look like. Just as William Gibson once served up the the vision of cyberspace that shaped the 1990s Internet revolution, a poet writing here in San Francisco almost exactly 40 years ago penned his vision for what a world of advanced AI should be.

Financial Markets and the Singularity
Peter Thiel

Over the past three decades, the financial markets experienced the largest and most violent series of booms and busts in history. Nothing in the orthodox literature predicted the market gyrations of the recent past; if anything, efficient market theorists would have anticipated a period of moderation as new technologies allowed participants to access and analyze data in unprecedented ways.

The markets’ bipolarism reflects the deep chasm between potential outcomes in a world of exponentiating technology. Every recent boom embodied hopes for a complete technological revolution; every bust was a story of unfulfilled promise. Today, the magnitude of booms and busts is extraordinary, suggesting that the world draws closer than ever to an epochal shift. But the markets have been unable to determine just how and when that shift will take place, and so every boom so far has been proved to be only a bubble. One distinct possibility is that the epochal shift the market senses but cannot identify is the arrival of the singularity as the transformational technological event of our time. But equally alarming is what is implicit in the deeper and deeper busts following each bubble: that the tensions in the world have reached a point where only a change of the greatest magnitude can provide resolution and that penalties for failing to cross that threshold will be high.

Increased Intelligence, Improved Life
Peter Voss

Artificial General Intelligence (AGI) promises unprecedented advances not only in science and technology, but also in ethics and social systems. However, business – and thus consumers – will be first to experience some of the enormous benefits of this emerging technology. This talk will explore some of these improvements, and try to make a case for how increased intelligence leads to improved morality.

The Road to Singularity: Comedic Complexity, Technological Thresholds, and Bioethical Broad Jumps
Wendell Wallach

The prospect of implementing higher order cognitive faculties in AI presumes that theories about the computational nature of mind are valid, that known technological issues can be solved, that there are no major surprise technological thresholds that will need to be crossed, and that computer scientists and public officials will find ways to navigate a broad array of ethical challenges. While some of these concerns have received considerable attention, others are just beginning to be noted. The ethical challenges, in particular, have not been well addressed. From robots carrying weapons, to moral decision making faculties for AI, to institutional review boards for robotic research, and political resistance to some categories of AI research, the bioethical challenges, if not addressed, could potentially undermine funding and public support for advanced AI systems. Progress in developing moral decision making faculties for computers is one area that engineers and designers can begin to tackle, and which will have a significant impact. The successful development of artificial moral agents (AMAs) is a major step that will help ameliorate other societal concerns regarding the development of advanced AI. The pathways for implementing moral decision making faculties in AI include top-down, bottom-up, and hybrid approaches. In addition, AMAs may require supra-rational faculties, such as social skills, emotions, consciousness, and a theory of mind.

Introducing the "Singularity": Three Major Schools of Thought
Eliezer Yudkowsky

Since the word "Singularity" was first introduced in the 1970s, several logically distinct concepts have attached themselves to the term. Today, the three major schools of thought are: Ray Kurzweil's Accelerating Change, which argues that future technological advances will predictably introduce changes greater than past technolgical advances. Vernor Vinge's Event Horizon, which argues that a future of smarter-than-human minds is weird in a way that goes beyond a future of amazin' gadgets with lotsa blinkin' lights. I. J. Good's Intelligence Explosion, which argues that minds creating technology to improve minds is a positive feedback cycle, a tipping point in which each intelligence increase paves the way for further increases. I introduce the three schools, their core arguments and bolder conjectures, and take note when they support or contradict each other.

The Challenge of Friendly AI
Eliezer Yudkowsky

Shaping a very powerful and general AI implies a different challenge, of greater moral and ethical depth, than programming a special-purpose domain-specific AI. Special-purpose AIs are controlled by human operators to human-chosen ends; a general AI may make plans in the real world according to its own, internal sense of purpose. But the danger of trying to impose our own values, eternally unchanged, upon the future, can be seen through the thought experiment of imagining the ancient Greeks trying to do the same. Human civilizations over centuries, and individual human beings over their own lifespans, directionally change their moral values. This makes the challenge of shaping a very powerful AI not-simple, to put it mildly.