What’s The Future Of The Sharing Economy?

As technology lets us share more and more items with greater and greater convenience, how far can the sharing economy go?

In 2009, I was a student in the inaugural graduate studies program of Singularity University. There we were challenged to come up with an idea that could impact 1 billion people within 10 years. Other groups chose to use 3-D printing to build homes in the developing world and mobile phones to create a better disaster response system. We chose to improve our transportation systems by empowering people everywhere to share their cars. This eventually became Getaround.

The Evolution of Sharing

A few years ago, no one would have thought peer-to-peer asset sharing would become such a big thing. With the immense popularity of Airbnb and the emergence of thousands of other sharing companies globally, 2012 has quickly become the year of sharing. Most articles on innovation list “sharing” as a game-changing idea or the hot trend to watch.

The hitch is, there’s nothing new about sharing. Individuals have been finding ways to increase their access to goods and services for some time. You needn’t go further than Small Town, USA, for proof. Chances are good you’ll find a library, laundromat, and what used to be a video rental store. That’s all the sharing economy.

For many years, these “classic” forms of sharing were part of everyday life. Individuals relied on public institutions and private corporations to maximize our access to things we couldn’t afford or didn’t see the value in purchasing ourselves. These organizations provided a formal framework in which to share, assuming the risk of owning the shared assets while enforcing rules and guidelines for participation.

The Present

More recently, there has been a surge in peer-to-peer sharing, and formal sharing institutions are quickly becoming a thing of the past. It doesn’t require an in-depth analysis to recognize the role of technology in this shift. What started online as the sharing of information has quickly turned into a full-fledged economy, with individuals sharing their homes, cars, and skills with the help of mobile devices.

As the sharing economy grows and individuals assume the risk of sharing personal property, they are turning to technology as a way to mitigate those risks. People renting their homes through services like Airbnb are relying on social network profiles and online reputations of potential renters to gauge who they should share their home with, while services such as TaskRabbit link directly into public records that allow them to perform background checks of potential "rabbits."

Other services have been using technology as a way to provide access to shared goods. Getaround, which enables people to rent cars from people nearby, allows users to grant and gain access to idle cars through mobile phones, allowing users to share assets regardless of geographic location.

This intersection of sharing and technology has contributed to an “own less, use more” mindset, backed by environmentalists and economists alike. By skipping platforms that require the production of new assets, like car rental agencies and hotels, we--as a society--are ultimately able to produce fewer goods while still having access to a broad variety of goods and services. The potential environmental impacts are significant: When measuring carbon emissions, home sharing is 66% more effective than hotels where as car sharing participants reduce their individual emissions by 40%.

Beyond its environmental impact, the sharing economy has been recognized as a way of empowering individuals to access more while owning less, stimulating local economies by keeping money spent in the community. Furthermore, while sharing supports local businesses, it also helps to forge new social networks, creating stronger, more tightly knit communities.

The Future

Today’s sharing economy was catalyzed by the social, economic, and technological trends of our time: The proliferation of social networks and mobile technology and a demand for environmentally responsible consumer products. Moving forward, these trends will continue to shape the way people share. While it’s impossible to predict the future, there are several technological advancements and trends on the horizon that are certain to impact sharing behavior.

Recent developments in the car industry provide some excellent insight into the opportunities ahead for other common consumer products. In recent years, connected cars have been a hot topic at automotive shows around the world. To date, the consumer-facing impact of this technology has been limited to new on-board “infotainment” centers allowing owners to connect to music, maps, and news online.

But as the connected car technology continues to advance, connected cars will likely find a place in the sharing economy, connecting drivers to passengers and passengers to cars. Not only will this technology make existing services like Zimride even easier to use, but it will also encourage car owners to maximize their resources by no longer riding alone, while also making money off their assets. The self-driving car is also going to have a large impact on the personal consumption of vehicles.

As someone dedicated to changing the way the world views, owns, and interacts with cars, these automotive advancements are vital. However, the larger trend of “designing for sharing” will have a major impact on how goods are consumed.

As more products are designed to interface directly with the Internet as well as with other products, it will become easier and easier to share an increasing number of goods and services. As assets become easier to track and easier to access, the process of sharing will be streamlined and the risks will be reduced.

The sky’s the limit for the sharing economy. Consumer behavior is shifting rapidly to be more selective, conscious, and community-based. Some of the major problems caused by hyper-consumption can be avoided by sharing more, and whatever people are willing to share, a good business can form to support this new behavior.

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In a 2010 New York Times feature on predicting the future, Ray Kurzweil, of Kurzweil’s law, said, “...It’s not just electronics and communications that follow [an] exponential course, [it’s also] health, medicine and its related field of biology...”

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Kurzweil Responds: Don't Underestimate the Singularity

Last week, Paul Allen and a colleague challenged the prediction that computers will soon exceed human intelligence. Now Ray Kurzweil, the leading proponent of the "Singularity," offers a rebuttal.

Although Paul Allen paraphrases my 2005 book, The Singularity Is Near, in the title of his essay (cowritten with his colleague Mark Greaves), it appears that he has not actually read the book. His only citation is to an essay I wrote in 2001 ("The Law of Accelerating Returns") and his article does not acknowledge or respond to arguments I actually make in the book.

When my 1999 book, The Age of Spiritual Machines, was published, and augmented a couple of years later by the 2001 essay, it generated several lines of criticism, such as Moore's law will come to an end, hardware capability may be expanding exponentially but software is stuck in the mud, the brain is too complicated, there are capabilities in the brain that inherently cannot be replicated in software, and several others. I specifically wrote The Singularity Is Near to respond to those critiques.

I cannot say that Allen would necessarily be convinced by the arguments I make in the book, but at least he could have responded to what I actually wrote. Instead, he offers de novo arguments as if nothing has ever been written to respond to these issues. Allen's descriptions of my own positions appear to be drawn from my 10-year-old essay. While I continue to stand by that essay, Allen does not summarize my positions correctly even from that essay.

Allen writes that "the Law of Accelerating Returns (LOAR). . . is not a physical law." I would point out that most scientific laws are not physical laws, but result from the emergent properties of a large number of events at a finer level. A classical example is the laws of thermodynamics (LOT). If you look at the mathematics underlying the LOT, they model each particle as following a random walk. So by definition, we cannot predict where any particular particle will be at any future time. Yet the overall properties of the gas are highly predictable to a high degree of precision according to the laws of thermodynamics. So it is with the law of accelerating returns. Each technology project and contributor is unpredictable, yet the overall trajectory as quantified by basic measures of price-performance and capacity nonetheless follow remarkably predictable paths.

If computer technology were being pursued by only a handful of researchers, it would indeed be unpredictable. But it's being pursued by a sufficiently dynamic system of competitive projects that a basic measure such as instructions per second per constant dollar follows a very smooth exponential path going back to the 1890 American census. I discuss the theoretical basis for the LOAR extensively in my book, but the strongest case is made by the extensive empirical evidence that I and others present.

Allen writes that "these 'laws' work until they don't." Here, Allen is confusing paradigms with the ongoing trajectory of a basic area of information technology. If we were examining the trend of creating ever-smaller vacuum tubes, the paradigm for improving computation in the 1950s, it's true that this specific trend continued until it didn't. But as the end of this particular paradigm became clear, research pressure grew for the next paradigm. The technology of transistors kept the underlying trend of the exponential growth of price-performance going, and that led to the fifth paradigm (Moore's law) and the continual compression of features on integrated circuits. There have been regular predictions that Moore's law will come to an end. The semiconductor industry's roadmap titled projects seven-nanometer features by the early 2020s. At that point, key features will be the width of 35 carbon atoms, and it will be difficult to continue shrinking them. However, Intel and other chip makers are already taking the first steps toward the sixth paradigm, which is computing in three dimensions to continue exponential improvement in price performance. Intel projects that three-dimensional chips will be mainstream by the teen years. Already three-dimensional transistors and three-dimensional memory chips have been introduced.

This sixth paradigm will keep the LOAR going with regard to computer price performance to the point, later in this century, where a thousand dollars of computation will be trillions of times more powerful than the human brain. [1] And it appears that Allen and I are at least in agreement on what level of computation is required to functionally simulate the human brain. [2]

Allen then goes on to give the standard argument that software is not progressing in the same exponential manner of hardware. In The Singularity Is Near, I address this issue at length, citing different methods of measuring complexity and capability in software that demonstrate a similar exponential growth. One recent study ("Report to the President and Congress, Designing a Digital Future: Federally Funded Research and Development in Networking and Information Technology" by the President's Council of Advisors on Science and Technology) states the following:

"Even more remarkable—and even less widely understood—is that in many areas, performance gains due to improvements in algorithms have vastly exceeded even the dramatic performance gains due to increased processor speed. The algorithms that we use today for speech recognition, for natural language translation, for chess playing, for logistics planning, have evolved remarkably in the past decade ... Here is just one example, provided by Professor Martin Grötschel of Konrad-Zuse-Zentrum für Informationstechnik Berlin. Grötschel, an expert in optimization, observes that a benchmark production planning model solved using linear programming would have taken 82 years to solve in 1988, using the computers and the linear programming algorithms of the day. Fifteen years later—in 2003—this same model could be solved in roughly one minute, an improvement by a factor of roughly 43 million. Of this, a factor of roughly 1,000 was due to increased processor speed, whereas a factor of roughly 43,000 was due to improvements in algorithms! Grötschel also cites an algorithmic improvement of roughly 30,000 for mixed integer programming between 1991 and 2008. The design and analysis of algorithms, and the study of the inherent computational complexity of problems, are fundamental subfields of computer science."

I cite many other examples like this in the book. [3]

Regarding AI, Allen is quick to dismiss IBM's Watson as narrow, rigid, and brittle. I get the sense that Allen would dismiss any demonstration short of a valid passing of the Turing test. I would point out that Watson is not so narrow. It deals with a vast range of human knowledge and is capable of dealing with subtle forms of language, including puns, similes, and metaphors. It's not perfect, but neither are humans, and it was good enough to get a higher score than the best two human Jeopardy! players put together.

Allen writes that Watson was put together by the scientists themselves, building each link of narrow knowledge in specific areas. Although some areas of Watson's knowledge were programmed directly, according to IBM, Watson acquired most of its knowledge on its own by reading natural language documents such as encyclopedias. That represents its key strength. It not only is able to understand the convoluted language in Jeopardy! queries (answers in search of a question), but it acquired its knowledge by reading vast amounts of natural-language documents. IBM is now working with Nuance (a company I originally founded as Kurzweil Computer Products) to have Watson read tens of thousands of medical articles to create a medical diagnostician.

A word on the nature of Watson's "understanding" is in order here. A lot has been written that Watson works through statistical knowledge rather than "true" understanding. Many readers interpret this to mean that Watson is merely gathering statistics on word sequences. The term "statistical information" in the case of Watson refers to distributed coefficients in self-organizing methods such as Markov models. One could just as easily refer to the distributed neurotransmitter concentrations in the human cortex as "statistical information." Indeed, we resolve ambiguities in much the same way that Watson does by considering the likelihood of different interpretations of a phrase.

Allen writes: "Every structure [in the brain] has been precisely shaped by millions of years of evolution to do a particular thing, whatever it might be. It is not like a computer, with billions of identical transistors in regular memory arrays that are controlled by a CPU with a few different elements. In the brain, every individual structure and neural circuit has been individually refined by evolution and environmental factors."

Allen's statement that every structure and neural circuit is unique is simply impossible. That would mean that the design of the brain would require hundreds of trillions of bytes of information. Yet the design of the brain (like the rest of the body) is contained in the genome. And while the translation of the genome into a brain is not straightforward, the brain cannot have more design information than the genome. Note that epigenetic information (such as the peptides controlling gene expression) do not appreciably add to the amount of information in the genome. Experience and learning do add significantly to the amount of information, but the same can be said of AI systems. I show in The Singularity Is Near that after lossless compression (due to massive redundancy in the genome), the amount of design information in the genome is about 50 million bytes, roughly half of which pertains to the brain. [4] That's not simple, but it is a level of complexity we can deal with and represents less complexity than many software systems in the modern world.

How do we get on the order of 100 trillion connections in the brain from only tens of millions of bytes of design information? Obviously, the answer is through redundancy. There are on the order of a billion pattern-recognition mechanisms in the cortex. They are interconnected in intricate ways, but even in the connections there is massive redundancy. The cerebellum also has billions of repeated patterns of neurons. It is true that the massively repeated structures in the brain learn different items of information as we learn and gain experience, but the same thing is true of artificially intelligent systems such as Watson.

Dharmendra S. Modha, manager of cognitive computing for IBM Research, writes: "...neuroanatomists have not found a hopelessly tangled, arbitrarily connected network, completely idiosyncratic to the brain of each individual, but instead a great deal of repeating structure within an individual brain and a great deal of homology across species ... The astonishing natural reconfigurability gives hope that the core algorithms of neurocomputation are independent of the specific sensory or motor modalities and that much of the observed variation in cortical structure across areas represents a refinement of a canonical circuit; it is indeed this canonical circuit we wish to reverse engineer."

Allen articulates what I describe in my book as the "scientist's pessimism." Scientists working on the next generation are invariably struggling with that next set of challenges, so if someone describes what the technology will look like in 10 generations, their eyes glaze over. One of the pioneers of integrated circuits was describing to me recently the struggles to go from 10 micron (10,000-nanometer) feature sizes to five-micron (5,000 nanometers) features over 30 years ago. They were cautiously confident of this goal, but when people predicted that someday we would actually have circuitry with feature sizes under one micron (1,000 nanometers), most of the scientists struggling to get to five microns thought that was too wild to contemplate. Objections were made on the fragility of circuitry at that level of precision, thermal effects, and so on. Well, today, Intel is starting to use chips with 22-nanometer gate lengths.

We saw the same pessimism with the genome project. Halfway through the 15-year project, only 1 percent of the genome had been collected, and critics were proposing basic limits on how quickly the genome could be sequenced without destroying the delicate genetic structures. But the exponential growth in both capacity and price performance continued (both roughly doubling every year), and the project was finished seven years later. The project to reverse-engineer the human brain is making similar progress. It is only recently, for example, that we have reached a threshold with noninvasive scanning techniques that we can see individual interneuronal connections forming and firing in real time.

Allen's "complexity brake" confuses the forest with the trees. If you want to understand, model, simulate, and re-create a pancreas, you don't need to re-create or simulate every organelle in every pancreatic Islet cell. You would want, instead, to fully understand one Islet cell, then abstract its basic functionality, and then extend that to a large group of such cells. This algorithm is well understood with regard to Islet cells. There are now artificial pancreases that utilize this functional model being tested. Although there is certainly far more intricacy and variation in the brain than in the massively repeated Islet cells of the pancreas, there is nonetheless massive repetition of functions.

Allen mischaracterizes my proposal to learn about the brain from scanning the brain to understand its fine structure. It is not my proposal to simulate an entire brain "bottom up" without understanding the information processing functions. We do need to understand in detail how individual types of neurons work, and then gather information about how functional modules are connected. The functional methods that are derived from this type of analysis can then guide the development of intelligent systems. Basically, we are looking for biologically inspired methods that can accelerate work in AI, much of which has progressed without significant insight as to how the brain performs similar functions. From my own work in speech recognition, I know that our work was greatly accelerated when we gained insights as to how the brain prepares and transforms auditory information.

The way that these massively redundant structures in the brain differentiate is through learning and experience. The current state of the art in AI does, however, enable systems to also learn from their own experience. The Google self-driving cars (which have driven over 140,000 miles through California cities and towns) learn from their own driving experience as well as from Google cars driven by human drivers. As I mentioned, Watson learned most of its knowledge by reading on its own.

It is true that Watson is not quite at human levels in its ability to understand human language (if it were, we would be at the Turing test level now), yet it was able to defeat the best humans. This is because of the inherent speed and reliability of memory that computers have. So when a computer does reach human levels, which I believe will happen by the end of the 2020s, it will be able to go out on the Web and read billions of pages as well as have experiences in online virtual worlds. Combining human-level pattern recognition with the inherent speed and accuracy of computers will be very powerful. But this is not an alien invasion of intelligence machines—we create these tools to make ourselves smarter. I think Allen will agree with me that this is what is unique about the human species: we build these tools to extend our own reach.

Ray Kurzweil is an inventor and author. His last piece for Technology Review was about fighting the aging process.

[1] Chapter 2, The Singularity Is Near by Ray Kurzweil, Viking, 2005.

[2] See Endnote 2 in "The Singularity Isn't Near" by Paul G. Allen and Mark Greaves.

[3] Chapter 9, The Singularity Is Near.

[4] Chapter 4, The Singularity Is Near.
 

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William Haseltine, a biotech pioneer, once observed, “…The nature of life is not mortality. It’s immortality. DNA is an immortal molecule. That molecule first appeared perhaps 3.5 billion years ago. That selfsame molecule, through duplication, is around today …. It’s true that we run down, but we talked about projecting way into the future the ability to alter that. First to extend our lives two- or threefold. And perhaps, if we understand the brain well enough, to extend both our body and our brain indefinitely. And I don’t think that will be an unnatural process…”

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As Nobel laureate Richard Feynman once said, “…There is nothing in biology yet found that indicates the inevitability of death. This suggests to me that is not all inevitable and that it is only a matter of time before biologists discover what it is that is causing us the trouble and that this terrible universal disease or temporariness of the human’s body will be cured…”

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Scientific American and The Immortal Ambitions of Ray Kurzweil: A Review of Transcendent Man

Against a swirling montage of cosmic birth and destruction, and newsreel-style stills from his personal history, the celebrated inventor and futurist Ray Kurzweil sits in silhouette, contemplating death. He broods over mortality's toll in waste and pain, and the hopelessness and loss that people must experience in their last moments of life. "It's such a profoundly sad, lonely feeling that I really can't bear it," he admits.

Then, cheerfully, he adds, "So I go back to thinking about how I'm not going to die."

That opening sequence of Transcendent Man, the new documentary by director Barry Ptolemy that profiles Kurzweil and his ideas, neatly distills the sometimes jarring predictions and preoccupations of its subject. The film is about Kurzweil's belief that within just a few decades technology will allow human beings to transcend the physical and intellectual limitations of their biology. It also paints Kurzweil as a brilliant man who has personally always risen above the skepticism and misunderstanding of his doubters.

Cleverly edited and entertaining, Transcendent Man is unfortunately also too starstruck and reverent toward Kurzweil for its own good. It wants in part to be a movie about ideas, but frustratingly, it refuses to truly challenge any of those it raises—whether supportive or critical of him. Given that the film's theme is the salvation or destruction of the human race, its lack of commitment to a perspective other than innocent wonder is unsatisfying.

Kurzweil has always been propelled by powerful ideas, as the film makes clear. A recipient of the National Medal of Technology, he has been a pioneer in optical character recognition, speech recognition and other technologies, starting with his invention of a computer that composed music when he was just 17. His study of innovation in the 1980s convinced him that what he calls a "law of accelerating returns" governs progress, meaning that technology advances at an exponentially increasing rate. (The doubling of transistors on computer chips every 18 months, widely known as Moore's law, is one example of such an increase.)

Kurzweil popularized the concept of accelerating returns in his books The Age of Intelligent Machines (MIT Press, 1990) and The Age of Spiritual Machines: When Computers Exceed Human Intelligence (Viking, 1999), in which he predicted what the consequences of that rate of progress would be in the decades to come. He revisited and doubled down on that thesis in 2005 with The Singularity Is Near (Viking), a manifesto arguing that by mid-century history would reach a "technological singularity": an inflection point when artificial and enhanced intelligences would take control of further progress and usher in a kind of earthly nirvana. Genetics, nanotechnology and robotics would put immortality, infinite resources and boundless intelligence at the disposal of humanity and its sentient creations.

Dizzying as this vision can be, Transcendent Man does a good job of introducing viewers to it through well-chosen visuals and sound bites. Director Barry Ptolemy says that when he read The Singularity Is Near, he was convinced that it was one of the most profound books ever written and that he had to make a film about it. With Kurzweil's cooperation, Ptolemy spent two years following the futurist across five continents as he went about his multiple businesses and preached the creed of exponential progress.

Notwithstanding Kurzweil's certainty, many people are unpersuaded by his ideas—particularly in some of the medical and technical fields that he says will soon be transformed, and even among thinkers who respect him otherwise. As Neil Gershenfeld, director of the Center for Bits and Atoms at the Massachusetts Institute of Technology, remarks on camera, "What Ray does consistently is to take a whole bunch of steps that everybody agrees on and take principles for extrapolating that everybody agrees on and show they lead to things that nobody agrees on," because "they just seem crazy."

As seen in the film, Kurzweil's response to those who don't share his perspective on technologically enhanced transcendence, particularly on the life-extension topic, is not unkind but patronizing. He realizes, he says, that people feel "threatened" by these ideas but that they will eventually accept the incremental realizations of that progress. He never seems to credit that well-informed people might disagree or disapprove of his views for reasons that have nothing to do with their own fallibility or weakness—but rather that they might be right and he might be wrong.

Similarly, Kurzweil views his own rejection of death as the only appropriate response. People who say they have learned to accept mortality are fooling themselves, he tells the camera; society numbly glorifies death because it has surrendered to it. The possibility that Kurzweil's stubborn disdain for death might spring from neurotic denial rather than from intellectual independence is apparently absurd to him.

Indeed, Kurzweil's attitude toward the idea of his own fallibility was on display in the question-and-answer session after the New York City screening of Transcendent Man. An audience member asked him about what he had gotten wrong over the years. Kurzweil mentioned that he had recently written a 150-page review of his predictions to date and concluded that about 86 percent of them were correct. (Disclosure: having taken my own look at his predictions, I have a rather different assessment—see here, here and here.) Pressed to name something he had gotten wrong, Kurzweil mentioned that he had predicted self-piloting cars to be common by now. But he hastened to point to out Google had recently tested its own autonomous vehicles that had driven themselves over 225,000 kilometers on busy roads, which meant that such vehicles would indeed be coming, just not for a few more years.

That is Kurzweil's view of his failures in a nutshell: to him, his errors are simply predictions for which essential correctness has not yet been demonstrated.

Kurzweil's manner—undemonstrative, measured, confidently detached—can seem cold, especially when he talks so matter-of-factly about shucking off the human condition as we know it. With good reason, the filmmakers work to find the warmer, quirkier soul inside Kurzweil—and to some degree they succeed. They reveal the inventor and futurist as a loving family man who has worn a Mickey Mouse watch for 30 years and lives in a beautiful house adorned with hundreds of awards and honors, a poster of Alanis Morissette and roughly 300 cat figurines. He is someone who declared early in life that he would transform the lives of the blind and deaf with his inventions, and the warm receptions that he receives from groups with those disabilities prove he made good on that promise.

Still, at times the film may work to make Kurzweil more relatable than he is. After the New York screening an audience member asked Kurzweil why it was hurtful when people called him a "crackpot." "On what basis do you think it bothers me?" Kurzweil replied. The viewer pointed out that it happened in the film during a radio call-in show, and the camera seemed to freeze on his sad expression. "The film didn't show my actual reaction," Kurzweil said. Ptolemy, who was also on stage, did not comment.

The emotional spine of the film is Kurzweil's love for his father, a composer whose "genius was thwarted" in life, he says, and who died at 58 of heart disease. The film weds Kurzweil's refusal to accept death's inevitability to his quest for immortality, which he believes advances in medicine and technology will achieve before he himself dies. In effect, the film dares viewers to draw the pop psychology conclusion that Kurzweil's faith in techno-immortality is really a fantasy he's projected to avoid confronting his fears of death—an opinion that Kurzweil would surely dispute.

Therein lies the biggest flaw in the movie: it refuses to ask that question and challenge Kurzweil's own narrative about his beliefs. Kurzweil acknowledges that his father's death was momentous for him (and credits the film with helping him realize it), but he never concedes or even addresses on camera whether that fact might bear on his certainty that the Singularity will arrive during his lifetime.

The film is evenhanded enough to give some of Kurzweil's more respectful critics a chance to air their disagreements with him, but it never shows anyone arguing directly with Kurzweil, so viewers are left with no sense of who might have the better-reasoned perspective. The film seems dedicated to this hands-off approach. Ptolemy followed Kurzweil for two years and was clearly immersed in those ideas; surely he must have his own opinion of them. But if so, he keeps it under wraps.

As a result, the film fails to show that resistance to his ideas is often based on more than uninformed incredulity and that the science on which Kurzweil stands is sometimes rather flimsy. For example, Kurzweil states that biological evolution shows the same exponential rate of change that technology does—a claim that many biologists consider nonsensical. He confidently foresees uploading human consciousness and memories into computers but doesn't engage with extensive objections to that possibility raised by neuroscientists. He talks about "reprogramming [his] biochemistry" with pills and supplements but doesn't note that the science behind that regimen sometimes relies on a selective reading of the research literature. He speaks assuredly about genes as "software" but glosses over the problems with that metaphor.

The absence of a challenge in the film is sorely missed everywhere, but especially in Kurzweil's poignant, bizarre belief that technology will someday help him resurrect his father. With degraded DNA scavenged from his father's grave, memories plucked from the brains of those who knew him, and information in the man's papers and music (which Kurzweil has scrupulously warehoused), post-Singularity technology will supposedly be able to whip up a replica of the man.

It is hard to know where to begin in pointing out the problems with that plan. But technical and philosophical reservations aside, what does it say about Kurzweil's personality that he would consider such a thin simulacrum to be his father, or even an appealing proxy for him? A more incisive documentary would want to know.

Kurzweil and Transcendent Man want to evangelize that technology will help human beings rise above the limitations of their biology and become something literally more divine. Yet Kurzweil comes across as naively uninterested in the philosophical and practical implications of that possibility—not unaware of them, but blithely optimistic that the problems will work out. And paradoxically, in a film about an expansion of what it could mean to be human the protagonist sometimes seems so emotionally off-kilter that his own humanity feels unrealized.

Futurist Kevin Kelly—who is no stranger to wild technological extrapolations, as in his 2010 book What Technology Wants (Viking)—thinks that Kurzweil is probably right about where the technology is heading but far too optimistic about how soon immortality and other dreams will be realized. In the film he describes Kurzweil as "more a poet than a mechanic," and adds that Kurzweil's unswerving commitment to his ideas makes him a kind of "modern-day prophet…that's wrong."

Kelly's assessment may be the canniest of any in the film. Kurzweil is devoutly sure that the angels of exponential progress will triumph over all doubt. He intends to see nanotech-embodied intelligence expanding outward, inhabiting every speck of matter in the cosmos until the universe itself springs into consciousness. His eye is on the long game, the infinitely long game that he intends to witness personally. Those critics who join him in eternity will come to realize that he was the one who saw it first and best—a singular distinction, if you will.

"Does God exist?" Kurzweil asks rhetorically in the film. "I would say, 'Not yet.'" The wittiness of the joke almost hides the immodesty at its core.

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Indispensable Question: Has the Technological Singularity started to influence our lives already? Hence:

Rodney Brooks writes, “…Over the next ten to twenty years, there will be a cultural shift, in which we will adopt robotic technology, silicon, and steel into our bodies to improve what we can do and understand the world …. We may able to have a wireless Internet connection installed directly into our brains …. Fifty years from now, we can expect to see radical alterations of human bodies through genetic modification …. The human menagerie will expand in ways unimaginable to us today …. We will no longer find ourselves by Darwinian evolution…”

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“…Why not learn from nature and biology? Hence, copy nature and biology!...”

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“…consciousness is actually the sum of many separate algorithms and techniques that nature stumbled upon over millions of years….”

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Dr. Henry Mintzberg argues that judging (qualitative analyses) is more important than measuring (quantitative analyzes). While Michael LeBouef observes, “…What gets rewarded gets done…”

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The pace of technological change is quickening — radically.

Ray Kurzweil states, "... A lot of people, sophisticated scientists included, take a linear perspective .... They assume the current [technological] tools will continue [along with] the current pace of progress..."

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Futurist Sees Machines, Humans Merging in 2045

Ray Kurzweil, an inventor and futurist, has stumbled on a discovery of earth-shattering importance. It is the arrival of "singularity," and according to him it will happen in 2045.

"Gradually," he writes at the beginning of "The Singularity Is Near," "I've become aware of a transforming event looming in the first half of the 21st century ... the impending Singularity in our future is increasingly transforming every institution and aspect of human life, from sexuality to spirituality."

Singularity, Kurzweil says, is a development "representing a profound and disruptive transformation in human capability" and a "radical upgrading of our bodies' physical and mental systems."

What are its elements? Kurzweil maintains that the first half of the 21st century will be characterized by three overlapping revolutions: human genetics, robotics or artificial intelligence, and nanotechnology.

Biotechnology, advances in genomics and gene therapies will enable us to turn off disease and aging and thus live for much longer. Because we soon will be able to "reverse-engineer the brain" and simulate its functions, he claims, technology will increasingly merge with human intelligence to create something with greater capacity and speed. Nanotechnology, the science of small things, will enable us "to redesign and rebuild -- molecule by molecule -- our bodies and brains and the world with which we interact, going far beyond the limitations of biology."

Kurzweil knows a lot about new technology, and he knows how to make it sound fun. He is dazzling in his enthusiasm for things to come, and he has a grasp of the exciting developments pulsing through the intersection of science and technology. He recognizes technology's power to improve the lot of humankind and is skeptical of the doom-mongers who argue that it will lead to overpopulation or mass unemployment.

New technologies, Kurzweil recognizes, usually create new jobs for those displaced by it. Cloning, for example, is not as scary as it is made to sound, and might even offer solutions for world hunger, creating meat and other protein sources in a factory without animals by cloning animal muscle tissue.

But what is the evidence for "singularity" itself? Kurzweil has borrowed the metaphor from mathematics and physics, where it means something that has reached the stage of being infinite. He recognizes that singularity does not amount to anything that might be described as "infinite" in the social sphere, but he still believes that the metaphor is appropriate. Humans, he too often forgets, have always sought to transcend biology.

Kurzweil thinks we are turning into cyborgs -- part human, part machine -- but any old man with a walking stick might be seen as a cyborg too. Technology, it is important to remember, conducts its way through society as a series of quantitative heaves rather than a qualitative leap. He thinks that the exponentially increasing processing power of computers can help us understand the speed of social change. The changes he describes might look fast on paper, but they filter through to social life at a snail's pace. Many of them do not make it at all because of a lack of investment or human enthusiasm.

Throughout his book Kurzweil capitalizes singularity. He even has a name for someone who is a follower of the faith: "I regard someone who understands the Singularity and who reflects on its implications for his or her own life as a 'singularitarian.' "

He pays lip service to a kind of humanism -- "we will transcend biology, but not our humanity" -- but sounds like a religious evangelist, or a New Ager who has spent too long in front of a computer. Being human, Kurzweil rightly points out, "means being part of a civilization that seeks to extend its boundaries." Is a human modified by technology no longer human? he wonders. The doom-mongers make it sound like a slippery slope, but Kurzweil envisages it as a kind of Second Coming, a technological Noah's ark through which only true believers will pass.

Kurzweil pays tribute to the notion of human consciousness but seems to regard it as a lost cause in the long run. His determination to keep humans central to his vision is admirable but is not borne out by the thrust of his work, which suggests that he takes his spiritual sustenance from the machine part of the equation.

For Kurzweil, all that remains is an ethical problem, of how humanity adapts to the new post-singular world in which we have become outsmarted by machines. His metaphor of singularity plays well in the science-fiction community, among Hollywood scriptwriters in need of inspiration and among military spooks whose job it is to think ahead of the curve -- Kurzweil is one of five members of the science advisory group for the U.S. Army.

For us ordinary mortals, it is singularly unhelpful.

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Ray Kurzweil Talks About 'Singularity' and Theory's Critics

Ray Kurzweil believes computers will soon think like humans and ultimately merge with us, a notion he has dubbed "the singularity."

That idea persuaded the former inventor in 2007 to form Singularity University, an institution housed at the NASA Research Park on Moffett Field in Mountain View, which teaches students about artificial intelligence and other topics straight out of science fiction.

While the institution isn't accredited and offers short programs rather than a four-year degree, it has attracted lecturers and advisers such as Autodesk Inc. Chief Executive Carl Bass and Google Inc. Chief Internet Evangelist Vint Cerf. The notion of the singularity previously spawned the Singularity Institute, an artificial-intelligence research group in San Francisco.

Mr. Kurzweil's artificial-intelligence theories have made him something of a lightning rod among Silicon Valley technologists. He draws praise and funding from the likes of Google co-founder and CEO Larry Page and investor Peter Thiel. But others such as Microsoft Corp. co-founder Paul Allen and Lotus 1-2-3 designer Mitch Kapor dismiss Mr. Kurzweil's ideas, arguing, in part, that the way humans process information may not be analogous to how computers do so—which means human consciousness can't necessarily be reproduced digitally.

Mr. Kurzweil, 64 years old, who lives in the suburbs of Boston and regularly travels to the Bay Area for his work at the university and institute, discussed his predictions and his status as a polarizing figure in a recent interview:

WSJ: There are plenty of universities in the Bay Area that teach computer science, neuroscience, all the fields you're exploring at Singularity University. What kind of gap does Singularity University fill?

Mr. Kurzweil: There are lots of universities that teach this subject matter in a traditional way—basically, looking at the current state of knowledge. Singularity University is really devoted to understanding the phenomenon of exponential growth and how that is transforming one field after another. Computation and communication are obvious ones, but biology, health and medicine are others. The point is that health and medicine are now information technologies, and once an area becomes an information technology it progresses exponentially and not linearly.

The other key difference is that the students learn primarily through learning: The students self-organize into teams and take on some world challenge and start a project intended to last a long time. One project is to provide inexpensive housing for the developing world by building houses Lego-style using three-dimensional printing.

WSJ: What do you expect the most prominent companies in Silicon Valley to be making in 20 years?

Mr. Kurzweil: There are several different fields that are quite revolutionary. One area is biotechnology—technologies to really change the information processes underlying our bodies to program our bodies away from diseases and aging. You and I are walking around with outdated technology in our bodies. Twenty years from now, we'll really have a way to radically change those processes.

Another area is artificial intelligence. Twenty years from now you won't have to ask computers for help. The computer will be listening in on you and determining what you need. And we'll have virtual reality—you and I could have sat together in a virtual living room or taken a virtual walk on a Mediterranean beach.

WSJ: You have some famous proponents in the Bay Area, but you also have some vocal critics like Mitch Kapor and Paul Allen. Can you respond to the idea that the brain's workings are so different from that of a computer that they would be impossible to simulate?

Mr. Kurzweil: My critics are thinking linearly and imagining continued linear progress, but that's not true. [Progress will be] exponential: It makes an enormous difference. People also say the brain is too complex. Well, it's a complicated area, but there's a tremendous amount of redundancy—the complexity is more apparent than real. It's a level of complexity that we can handle.

WSJ: Where is the most interesting artificial-intelligence research taking place?

Mr. Kurzweil:This type of research is being done all over the world.The most sophisticated is being done in the United States, most significantly in Silicon Valley. Larry Page has a strong personal interest in AI. Search engines are going to understand what you mean and not just look at words. Look at Watson [the IBM computer that won Jeopardy]. It dealt with questions that were extremely subtle, dealt with puns, innuendo and metaphors.

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The new overlords ─ Man and technology are evolving together in radical new ways

CAN machines surpass humans in intelligence? People were shocked in 1997 when IBM’s Deep Blue computer beat Garry Kasparov, a Russian grandmaster, at chess. But winning a board game is a trivial task compared with understanding the complexities and idiosyncrasies of human speech. The company has now developed Watson, a supercomputer it thinks is capable of understanding “natural language”.

To put this claim to the test, IBM arranged for its creation to compete in “Jeopardy!”, an American quiz show known for using clues and wordplay that even bright humans struggle to understand. In the contest, televised in America in February, Watson trounced the two most successful previous champions of the quiz.

This victory fits nicely into Ray Kurzweil’s vision. An inventor and futurist, he has long predicted the rise of intelligent machines. “Transcendent Man”, a new documentary film, probes his breathtaking, possibly balmy, vision of the future.

Mr Kurzweil leads an influential cabal of techno-optimists, a group that includes Silicon Valley stars, scientific grandees and even the Obama administration’s chief information officer, Vivek Kundra. They believe mankind is heading for a glorious post-biological era known as the Singularity. Thanks to implants and other enhancements, humans will improve along with machines. But artificial intelligence will inevitably surpass the human kind—and will do so, according to Mr Kurzweil’s calculations, as early as 2029.

Predicting what will happen after that point is difficult, he argues, because we cannot hope to predict the behaviour or evolution of hyper-intelligent machines. But he insists that “the intelligence that will emerge will continue to represent the human civilisation, which is already a human-machine civilisation.”

Mr Kurzweil’s journey as a futurist began when he became intrigued by rapid advances in computing capacity. Scrutinising the progress in other realms of modern technology, he found the same explosive growth. This “law of accelerating returns” underpins the modern digital economy.

He argues that this technological acceleration affects many industries. For example, the rate of expansion of solar energy has been doubling every two years for the past two decades which, he insists, means that solar power will meet all energy needs in 20 years. When the human genome project started, sceptics argued it would take centuries to scan an entire human genome using prevailing technologies; in fact, thanks to exponential advances in sequencing technology, it was done in less than 15 years.

But what if the biggest breakthroughs come in improving man himself? Some technology experts think mankind will transform itself into a fitter, smarter and better-looking species in coming decades—a blink of an eye in evolutionary terms. Juan Enriquez and Steve Gullans argue in “Homo Evolutis”, a new electronic book, that the leapfrogging advances seen today in biotechnology, gene therapy, epigenetics, proteomics and a myriad of related fields are turbocharging evolution itself. “Forget the Singularity—biology will trump technology,” insists Mr Enriquez.

The authors argue that mankind has at last become the first species capable of deliberately directing its own evolution. Some of this is being done to improve looks or athletic performance; other techniques are extending life or growing vital organs. Along the way the human species is being changed. There is no master plan, the authors insist, as it is “not one technology, government, company, region or discipline that is driving speciation.”

As with Mr Kurzweil’s forecasts for machine super-intelligence and post-biological bodies, these predictions raise hackles in the scientific establishment. But even if the futurists are wrong about the pace of change, they may turn out to be right about the direction. In his final “Jeopardy!” answer, one of the human contestants conceded defeat by scribbling a cheeky line from “The Simpsons” television show: “I, for one, welcome our new computer overlords.”

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The Future Is Now? Pretty Soon, at Least

Before we get to Ray Kurzweil’s plan for upgrading the “suboptimal software” in your brain, let me pass on some of the cheery news he brought to the World Science Festival last week in New York.

Do you have trouble sticking to a diet? Have patience. Within 10 years, Dr. Kurzweil explained, there will be a drug that lets you eat whatever you want without gaining weight.

Worried about greenhouse gas emissions? Have faith. Solar power may look terribly uneconomical at the moment, but with the exponential progress being made in nanoengineering, Dr. Kurzweil calculates that it’ll be cost-competitive with fossil fuels in just five years, and that within 20 years all our energy will come from clean sources.

Are you depressed by the prospect of dying? Well, if you can hang on another 15 years, your life expectancy will keep rising every year faster than you’re aging. And then, before the century is even half over, you can be around for the Singularity, that revolutionary transition when humans and/or machines start evolving into immortal beings with ever-improving software.

At least that’s Dr. Kurzweil’s calculation. It may sound too good to be true, but even his critics acknowledge he’s not your ordinary sci-fi fantasist. He is a futurist with a track record and enough credibility for the National Academy of Engineering to publish his sunny forecast for solar energy.

He makes his predictions using what he calls the Law of Accelerating Returns, a concept he illustrated at the festival with a history of his own inventions for the blind. In 1976, when he pioneered a device that could scan books and read them aloud, it was the size of a washing machine.

Two decades ago he predicted that “early in the 21st century” blind people would be able to read anything anywhere using a handheld device. In 2002 he narrowed the arrival date to 2008. On Thursday night at the festival, he pulled out a new gadget the size of a cellphone, and when he pointed it at the brochure for the science festival, it had no trouble reading the text aloud.

This invention, Dr. Kurzweil said, was no harder to anticipate than some of the predictions he made in the late 1980s, like the explosive growth of the Internet in the 1990s and a computer chess champion by 1998. (He was off by a year — Deep Blue’s chess victory came in 1997.)

“Certain aspects of technology follow amazingly predictable trajectories,” he said, and showed a graph of computing power starting with the first electromechanical machines more than a century ago. At first the machines’ power doubled every three years; then in midcentury the doubling came every two years (the rate that inspired Moore’s Law); now it takes only about a year.

Dr. Kurzweil has other graphs showing a century of exponential growth in the number of patents issued, the spread of telephones, the money spent on education. One graph of technological changes goes back millions of years, starting with stone tools and accelerating through the development of agriculture, writing, the Industrial Revolution and computers. (For details, see nytimes.com/tierneylab.)

Now, he sees biology, medicine, energy and other fields being revolutionized by information technology. His graphs already show the beginning of exponential progress in nanotechnology, in the ease of gene sequencing, in the resolution of brain scans. With these new tools, he says, by the 2020s we’ll be adding computers to our brains and building machines as smart as ourselves.

This serene confidence is not shared by neuroscientists like Vilayanur S. Ramachandran, who discussed future brains with Dr. Kurzweil at the festival. It might be possible to create a thinking, empathetic machine, Dr. Ramachandran said, but it might prove too difficult to reverse-engineer the brain’s circuitry because it evolved so haphazardly.

“My colleague Francis Crick used to say that God is a hacker, not an engineer,” Dr. Ramachandran said. “You can do reverse engineering, but you can’t do reverse hacking.”

Dr. Kurzweil’s predictions come under intense scrutiny in the engineering magazine IEEE Spectrum, which devotes its current issue to the Singularity. Some of the experts writing in the issue endorse Dr. Kurzweil’s belief that conscious, intelligent beings can be created, but most think it will take more than a few decades.

He is accustomed to this sort of pessimism and readily acknowledges how complicated the brain is. But if experts in neurology and artificial intelligence (or solar energy or medicine) don’t buy his optimistic predictions, he says, that’s because exponential upward curves are so deceptively gradual at first.

“Scientists imagine they’ll keep working at the present pace,” he told me after his speech. “They make linear extrapolations from the past. When it took years to sequence the first 1 percent of the human genome, they worried they’d never finish, but they were right on schedule for an exponential curve. If you reach 1 percent and keep doubling your growth every year, you’ll hit 100 percent in just seven years.”

Dr. Kurzweil is so confident in these curves that he has made a $10,000 bet with Mitch Kapor, the creator of Lotus software. By 2029, Dr. Kurzweil wagers, a computer will pass the Turing Test by carrying on a conversation that is indistinguishable from a human’s.

I’m not as confident those graphs are going to hold up for fields besides computer science, so I’d be leery of betting on a date. But if I had to take sides in the 2029 wager, I’d put my money on Dr. Kurzweil. He could be right once again about a revolution coming sooner than expected. And I’d hate to bet against the chance to be around for this one.

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How Climate Change is Shaping the Future of Business

This article is one in a series of updates from WRI’s Next Practice research team to highlight tools and guidance for developing corporate sustainability strategies. It builds on previous themes - Filling the Sustainability Innovation Gap and Mining Megatrends for Innovation - with examples of recent research and evidence that help build the business case for sustainability.

A recent KPMG report highlights ten “sustainability megaforces” that will shape markets in the decades to come. The list includes population growth, energy and fuel, ecosystems decline, and material resource scarcity, among others. These interconnected trends will create risks and opportunities for business. In response, companies need new strategies, particularly for market impacts relating to what KPMG calls the “megaforce” influencing all others: climate change.

Forward-thinking companies are starting to draw links between climate change and other major trends that impact business. Adapting for a Green Economy, a report released in June 2011 by WRI, the UN Global Compact, Oxfam and the UN Environment Programme, showed that many companies recognize climate change as a major strategic threat, as well as an opportunity. However, few have been able to design a strategic response or even fully explore how long-term climate risks will affect their markets.

Another recent report, the Carbon Disclosure Project’s analysis of FTSE 100 companies, found that nearly 80 percent view climate change as a substantive risk to their business. However, less than half of the companies surveyed had incorporated adaptive measures into their overall strategies so far.

For example, Ford Motor Company highlights climate change among the big trends shaping its strategy for future markets:
Global temperatures may continue to rise unless we stabilize greenhouse gases. Erratic weather patterns may impact water availability. And increasing global populations, coupled with improved standards of living worldwide, will put added strains on natural resources.

WRI’s work with companies on climate change has highlighted a need to turn information and awareness into strategic action and innovation (see below). Leading companies recognize that they will need new strategies and partners to effectively respond to climate change and other “sustainability megaforces.”

Key steps to consider in creating those strategies
Step 1

Gather and synthesize information. There is a lot of data out there – new reports seem to come out each day with compelling insights about how trends are shaping future markets. Companies need ways to monitor and integrate this information, gathering input from various internal and external experts. Shared insights can inform more robust, long-term, adaptive strategies for climate change and other sustainability priorities.

For example, a business unit in a pharmaceutical company may be thinking about future market needs. It would be valuable to have a means of gathering input from a diverse set colleagues. The business can then benefit from insights not just on basic health trends, but also the implications of growing cities, information technology and logistics, climate change (e.g., increasing temperatures, air quality impacts), and related natural resource constraints (e.g., fuel costs, water availability).

Step 2

Recognize threats, opportunities, and uncertainties. Climate change affects companies’ long-term business interests through both physical impacts (e.g., sea level rise, increased flood risk) and market impacts (e.g., growing demand for clean energy). As KPMG’s report emphasizes, companies need to think broadly about the external changes and identify climate impacts that directly or indirectly shape business risks and opportunities.

Consider the implications of increasing climate variability and weather extremes. Flooding in Thailand last year shut down production facilities for companies like Western Digital, a manufacturer of disk drives for computers. Other companies like Apple, Dell, and Intel, far removed from the flooding, felt the impacts as shortages and costs rippled through the global supply chain. In addition to risks, companies may also find opportunities to provide or invest in climate-resilient infrastructure solutions to help the region manage future flood risks.

Similarly, a company may not manufacture solar panels or wind turbines, but it can still find business opportunities with a growing demand for clean energy. Companies like Google are investing heavily to accelerate innovation and deployment of renewable energy, which helps reduce uncertainty for long-term energy supplies (and can provide a healthy return).
Step 3

Find new partners and new ways to collaborate. Climate change and other sustainability “megaforces” are bigger than any one company, which means that finding both traditional and non-traditional partners is essential.

Companies like Ford make efforts to gather input from outside stakeholders and incorporate them into a materiality matrix. Ford is also working with a range of partners that include companies like Best Buy and experts at the University of Michigan and Georgia Tech. These partnerships have helped the company understand how climate change can shape future products, facilities, supply chains and customer needs.

Creative collaborations like this allow companies to identify and develop actionable strategies to address the long-term threats, opportunities and uncertainties.

If KPMG’s report is any indication, “sustainability megaforces” will shape how companies build and protect business value for years to come. Companies with innovative strategies and partnerships to tackle the challenges associated with climate change will be more resilient and can find opportunities to lead tomorrow’s markets.

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Inventor Ray Kurzweil observed, “…It’s not going to be an invasion of intelligent machines coming over the horizon. We’re going to merge with this technology …. We’re going to put these intelligent devices in our bodies and brains to make us live longer and healthier….”

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“…Common sense is just the ‘rules of the games,’ rather than the rules of strategy and planning…”

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 “….Predicting the future, that is, creating multiple models that approximate future events….”

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Sensing the Future?

Theoretical physicist Michio Kaku Ph.D. wrote, “…Humans, however, have a very well-developed sense of the future and continually make plans. We continually run simulations of reality in our heads. In fact, we can contemplate plans far beyond our lifetimes. We judge other humans, in fact, by their ability to predict evolving situations and formulate concrete strategies. An important pat of leadership is to anticipate future situations, weigh possible outcomes, and set concrete goals accordingly….”

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How Are We “Reinventing Life”? (1957)

Sir Julian Sorell Huxley (22 June 1887 – 14 February 1975) said,  “…It is as if a man had been suddenly appointed managing director of the biggest business of all, the business of evolution ─ appointed without being asked if he wanted it, and without proper warning and preparation. What is more, he can’t refuse the job. Whether he wants to or not, whether he is conscious of what he is doing or not, he is in point of fact determining the future direction of evolution on this earth. That is his inescapable destiny, and the sooner he realizes and starts believing it, the better for all concerned….” Source: ISBN-13: 978-1937109004

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Scientists Worry Machines May Outsmart Man (New York Times)

A robot that can open doors and find electrical outlets to recharge itself. Computer viruses that no one can stop. Predator drones, which, though still controlled remotely by humans, come close to a machine that can kill autonomously.

Impressed and alarmed by advances in artificial intelligence, a group of computer scientists is debating whether there should be limits on research that might lead to loss of human control over computer-based systems that carry a growing share of society’s workload, from waging war to chatting with customers on the phone.

Their concern is that further advances could create profound social disruptions and even have dangerous consequences.

As examples, the scientists pointed to a number of technologies as diverse as experimental medical systems that interact with patients to simulate empathy, and computer worms and viruses that defy extermination and could thus be said to have reached a “cockroach” stage of machine intelligence.

While the computer scientists agreed that we are a long way from Hal, the computer that took over the spaceship in “2001: A Space Odyssey,” they said there was legitimate concern that technological progress would transform the work force by destroying a widening range of jobs, as well as force humans to learn to live with machines that increasingly copy human behaviors.

The researchers — leading computer scientists, artificial intelligence researchers and roboticists who met at the Asilomar Conference Grounds on Monterey Bay in California — generally discounted the possibility of highly centralized superintelligences and the idea that intelligence might spring spontaneously from the Internet. But they agreed that robots that can kill autonomously are either already here or will be soon.

They focused particular attention on the specter that criminals could exploit artificial intelligence systems as soon as they were developed. What could a criminal do with a speech synthesis system that could masquerade as a human being? What happens if artificial intelligence technology is used to mine personal information from smart phones?

The researchers also discussed possible threats to human jobs, like self-driving cars, software-based personal assistants and service robots in the home. Just last month, a service robot developed by Willow Garage in Silicon Valley proved it could navigate the real world.

A report from the conference, which took place in private on Feb. 25, is to be issued later this year. Some attendees discussed the meeting for the first time with other scientists this month and in interviews.

The conference was organized by the Association for the Advancement of Artificial Intelligence, and in choosing Asilomar for the discussions, the group purposefully evoked a landmark event in the history of science. In 1975, the world’s leading biologists also met at Asilomar to discuss the new ability to reshape life by swapping genetic material among organisms. Concerned about possible biohazards and ethical questions, scientists had halted certain experiments. The conference led to guidelines for recombinant DNA research, enabling experimentation to continue.

The meeting on the future of artificial intelligence was organized by Eric Horvitz, a Microsoft researcher who is now president of the association.

Dr. Horvitz said he believed computer scientists must respond to the notions of superintelligent machines and artificial intelligence systems run amok.

The idea of an “intelligence explosion” in which smart machines would design even more intelligent machines was proposed by the mathematician I. J. Good in 1965. Later, in lectures and science fiction novels, the computer scientist Vernor Vinge popularized the notion of a moment when humans will create smarter-than-human machines, causing such rapid change that the “human era will be ended.” He called this shift the Singularity.

This vision, embraced in movies and literature, is seen as plausible and unnerving by some scientists like William Joy, co-founder of Sun Microsystems. Other technologists, notably Raymond Kurzweil, have extolled the coming of ultrasmart machines, saying they will offer huge advances in life extension and wealth creation.

“Something new has taken place in the past five to eight years,” Dr. Horvitz said. “Technologists are providing almost religious visions, and their ideas are resonating in some ways with the same idea of the Rapture.”

The Kurzweil version of technological utopia has captured imaginations in Silicon Valley. This summer an organization called the Singularity University began offering courses to prepare a “cadre” to shape the advances and help society cope with the ramifications.

“My sense was that sooner or later we would have to make some sort of statement or assessment, given the rising voice of the technorati and people very concerned about the rise of intelligent machines,” Dr. Horvitz said.

The A.A.A.I. report will try to assess the possibility of “the loss of human control of computer-based intelligences.” It will also grapple, Dr. Horvitz said, with socioeconomic, legal and ethical issues, as well as probable changes in human-computer relationships. How would it be, for example, to relate to a machine that is as intelligent as your spouse?

Dr. Horvitz said the panel was looking for ways to guide research so that technology improved society rather than moved it toward a technological catastrophe. Some research might, for instance, be conducted in a high-security laboratory.

The meeting on artificial intelligence could be pivotal to the future of the field. Paul Berg, who was the organizer of the 1975 Asilomar meeting and received a Nobel Prize for chemistry in 1980, said it was important for scientific communities to engage the public before alarm and opposition becomes unshakable.

“If you wait too long and the sides become entrenched like with G.M.O.,” he said, referring to genetically modified foods, “then it is very difficult. It’s too complex, and people talk right past each other.”

Tom Mitchell, a professor of artificial intelligence and machine learning at Carnegie Mellon University, said the February meeting had changed his thinking. “I went in very optimistic about the future of A.I. and thinking that Bill Joy and Ray Kurzweil were far off in their predictions,” he said. But, he added, “The meeting made me want to be more outspoken about these issues and in particular be outspoken about the vast amounts of data collected about our personal lives.”

Despite his concerns, Dr. Horvitz said he was hopeful that artificial intelligence research would benefit humans, and perhaps even compensate for human failings. He recently demonstrated a voice-based system that he designed to ask patients about their symptoms and to respond with empathy. When a mother said her child was having diarrhea, the face on the screen said, “Oh no, sorry to hear that.”

A physician told him afterward that it was wonderful that the system responded to human emotion. “That’s a great idea,” Dr. Horvitz said he was told. “I have no time for that.”

Global Source and/or and/or more resources and/or read more: http://goo.gl/HKcYU ─ Publisher and/or Author and/or Managing Editor:__Andres Agostini ─ @Futuretronium at Twitter! │ Futuretronium Supranational Initiative │ Futuretronium Book at http://goo.gl/JujXk ─ www.FUTURE-OBSERVATORY.blogspot.com

Peter Drucker observed, "…Knowledge [- that dynamo that non-linearly accelerates the driving forces of disruptive changed change -] has to be [incessantly] improved, [perpetually] challenged, and increased constantly [for Life], or it vanishes. (Accordingly, when a given knowledge is outsmarted, it immediately goes obsoledge)…"

Global Source and/or and/or more resources and/or read more: http://goo.gl/HKcYU ─ Publisher and/or Author and/or Managing Editor:__Andres Agostini ─ @Futuretronium at Twitter! │ Futuretronium Supranational Initiative │ Futuretronium Book at http://goo.gl/JujXk ─ www.FUTURE-OBSERVATORY.blogspot.com

 “…I don’t really think our bodies are going to have any secrets left within this century. And so, anything that we can manage to think about will probably have a reality….” ─ David Baltimore, Nobel Laureate

Global Source and/or and/or more resources and/or read more: http://goo.gl/HKcYU ─ Publisher and/or Author and/or Managing Editor:__Andres Agostini ─ @Futuretronium at Twitter! │ Futuretronium Supranational Initiative │ Futuretronium Book at http://goo.gl/JujXk ─ www.FUTURE-OBSERVATORY.blogspot.com

 “…No one has the guts to say it, but if we could make better human beings by knowing how to add genes, why shouldn’t we?...” ─ James Watson, Nobel Laureate

Global Source and/or and/or more resources and/or read more: http://goo.gl/HKcYU ─ Publisher and/or Author and/or Managing Editor:__Andres Agostini ─ @Futuretronium at Twitter! │ Futuretronium Supranational Initiative │ Futuretronium Book at http://goo.gl/JujXk ─ www.FUTURE-OBSERVATORY.blogspot.com

 “...I don’t think the time is quite right, but it’s close. I’m afraid, unfortunately, that I’m in the last generation to die...” ─ Gerald Sussman

Global Source and/or and/or more resources and/or read more: http://goo.gl/HKcYU ─ Publisher and/or Author and/or Managing Editor:__Andres Agostini ─ @Futuretronium at Twitter! │ Futuretronium Supranational Initiative │ Futuretronium Book at http://goo.gl/JujXk ─ www.FUTURE-OBSERVATORY.blogspot.com